count: 48
list:
- accessibility: null
  additionDate: '2017-03-01T14:15:32Z'
  biotoolsCURIE: biotools:meta-snp
  biotoolsID: meta-snp
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-ITA-BOLOGNA
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole:
    - Support
    url: http://www.biocomp.unibo.it
  - email: emidio.capriotti@gmail.com
    fundrefid: null
    gridid: null
    name: Emidio Capriotti
    note: null
    orcidid: http://orcid.org/0000-0002-2323-0963
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Primary contact
    url: null
  description: Meta-predictor of disease causing variants.
  documentation:
  - note: null
    type:
    - General
    url: http://snps.biofold.org/meta-snp/pages/help.html
  download: []
  editPermission:
    authors:
    - ELIXIR-ITA-BOLOGNA
    - emidio
    type: group
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  elixirNode:
  - Italy
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Mutation ID
        uri: http://edamontology.org/data_2209
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: null
    operation:
    - term: Variant classification
      uri: http://edamontology.org/operation_3225
    output:
    - data:
        term: Disease report
        uri: http://edamontology.org/data_1622
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: http://snps.biofold.org/meta-snp
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-07T13:24:51.212872Z'
  license: null
  link: []
  maturity: Mature
  name: Meta-SNP
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: null
    metadata:
      abstract: 'In recent years the number of human genetic variants deposited into
        the publicly available databases has been increasing exponentially. The latest
        version of dbSNP, for example, contains ~50 million validated Single Nucleotide
        Variants (SNVs). SNVs make up most of human variation and are often the primary
        causes of disease. The non-synonymous SNVs (nsSNVs) result in single amino
        acid substitutions and may affect protein function, often causing disease.
        Although several methods for the detection of nsSNV effects have already been
        developed, the consistent increase in annotated data is offering the opportunity
        to improve prediction accuracy. Here we present a new approach for the detection
        of disease-associated nsSNVs (Meta-SNP) that integrates four existing methods:
        PANTHER, PhD-SNP, SIFT and SNAP. We first tested the accuracy of each method
        using a dataset of 35,766 disease-annotated mutations from 8,667 proteins
        extracted from the SwissVar database. The four methods reached overall accuracies
        of 64%-76% with a Matthew''s correlation coefficient (MCC) of 0.38-0.53. We
        then used the outputs of these methods to develop a machine learning based
        approach that discriminates between disease-associated and polymorphic variants
        (Meta-SNP). In testing, the combined method reached 79% overall accuracy and
        0.59 MCC, ~3% higher accuracy and ~0.05 higher correlation with respect to
        the best-performing method. Moreover, for the hardest-to-define subset of
        nsSNVs, i.e. variants for which half of the predictors disagreed with the
        other half, Meta-SNP attained 8% higher accuracy than the best predictor.
        Here we find that the Meta-SNP algorithm achieves better performance than
        the best single predictor. This result suggests that the methods used for
        the prediction of variant-disease associations are orthogonal, encoding different
        biologically relevant relationships. Careful combination of predictions from
        various resources is therefore a good strategy for the selection of high reliability
        predictions. Indeed, for the subset of nsSNVs where all predictors were in
        agreement (46% of all nsSNVs in the set), our method reached 87% overall accuracy
        and 0.73 MCC. Meta-SNP server is freely accessible at http://snps.biofold.org/meta-snp.'
      authors:
      - name: Capriotti E.
      - name: Altman R.B.
      - name: Bromberg Y.
      citationCount: 186
      date: '2013-01-01T00:00:00Z'
      journal: BMC genomics
      title: Collective judgment predicts disease-associated single nucleotide variants.
    note: null
    pmcid: PMC3839641
    pmid: '23819846'
    type:
    - Primary
    version: '1.0'
  relation: []
  toolType:
  - Web service
  topic:
  - term: Protein properties
    uri: http://edamontology.org/topic_0123
  - term: Pathology
    uri: http://edamontology.org/topic_0634
  validated: 1
  version:
  - '1.0'
- accessibility: null
  additionDate: '2016-04-15T11:52:42Z'
  biotoolsCURIE: biotools:comparems2
  biotoolsID: comparems2
  collectionID:
  - ms-utils
  - Proteomics
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: lumc.nl
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Support
    url: https://www.lumc.nl
  - email: magnus.palmblad@gmail.com
    fundrefid: null
    gridid: null
    name: Magnus Palmblad
    note: null
    orcidid: http://orcid.org/0000-0002-5865-8994
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Primary contact
    - Documentor
    url: https://github.com/magnuspalmblad
  - email: null
    fundrefid: null
    gridid: null
    name: Rob Marissen
    note: null
    orcidid: https://orcid.org/0000-0002-1220-9173
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/524D
  description: compareMS2 is a tool for comparing sets of (tandem) mass spectra for
    clustering samples, molecular phylogenetics, identification of biological species
    or tissues, and quality control. compareMS2 currently consumes Mascot Generic
    Format, or MGF, and produces output in a variety of common image and distance
    matrix formats.
  documentation:
  - note: null
    type:
    - General
    - Command-line options
    url: http://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - General
    - User manual
    - Command-line options
    - Installation instructions
    url: https://github.com/524D/compareMS2
  download:
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Binaries
    url: http://www.ms-utils.org/compareMS2.html
    version: '1.0'
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Source code
    url: https://github.com/524D/compareMS2/tree/main/src
    version: '2.0'
  - note: null
    type: Binaries
    url: https://github.com/524D/compareMS2/tree/main
    version: '2.0'
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Netherlands
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Phylogenetic tree visualisation
      uri: http://edamontology.org/operation_0567
    output:
    - data:
        term: Species tree
        uri: http://edamontology.org/data_3272
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Distance matrix
        uri: http://edamontology.org/data_2855
      format:
      - term: mega
        uri: http://edamontology.org/format_1991
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: newick
        uri: http://edamontology.org/format_1910
  homepage: https://github.com/524D/compareMS2
  homepage_status: 0
  language:
  - C
  - JavaScript
  lastUpdate: '2024-02-13T15:35:10.776331Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/524D/compareMS2
  - note: null
    type:
    - Software catalogue
    url: https://www.ms-utils.org/compareMS2.html
  maturity: Mature
  name: compareMS2
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1002/rcm.6162
    metadata:
      abstract: 'Rationale: Molecular phylogenetics is the study of evolution and
        relatedness of organisms or genes. Mass spectrometry is used routinely for
        bacterial identification and has also been used for phylogenetic analysis,
        for instance from bone material. Unfortunately, only a small fraction of the
        acquired tandem mass spectra allow direct interpretation. Methods: We describe
        a new algorithm and software for molecular phylogenetics using pairwise comparisons
        of tandem mass spectra from enzymatically digested proteins. The spectra need
        not be annotated and all acquired data is used in the analysis. To demonstrate
        the method, we analyzed tryptic digests of sera from four great apes and two
        other primates. Results: The distribution of spectra dot products for thousands
        of tandem mass spectra collected from two samples provides a measure on the
        fraction of shared peptides between the two samples. When inverted, this becomes
        a distance metric. By pairwise comparison between species and averaging over
        four individuals per species, it was possible to reconstruct the unique correct
        phylogenetic tree for the great apes and other primates. Conclusions: The
        new method described here has several attractive features compared with existing
        methods, among them simplicity, the unbiased use of all acquired data rather
        than a small subset of spectra, and the potential use of heavily degraded
        proteins or proteins with a priori unknown modifications. © 2012 John Wiley
        & Sons, Ltd.'
      authors:
      - name: Palmblad M.
      - name: Deelder A.M.
      citationCount: 28
      date: '2012-04-15T00:00:00Z'
      journal: Rapid Communications in Mass Spectrometry
      title: Molecular phylogenetics by direct comparison of tandem mass spectra
    note: null
    pmcid: null
    pmid: '22368051'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1021/acs.jproteome.2c00457
    metadata:
      abstract: It has long been known that biological species can be identified from
        mass spectrometry data alone. Ten years ago, we described a method and software
        tool, compareMS2, for calculating a distance between sets of tandem mass spectra,
        as routinely collected in proteomics. This method has seen use in species
        identification and mixture characterization in food and feed products, as
        well as other applications. Here, we present the first major update of this
        software, including a new metric, a graphical user interface and additional
        functionality. The data have been deposited to ProteomeXchange with dataset
        identifier PXD034932.
      authors:
      - name: Marissen R.
      - name: Varunjikar M.S.
      - name: Laros J.F.J.
      - name: Rasinger J.D.
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 2
      date: '2023-02-03T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry
        Datasets'
    note: null
    pmcid: PMC9903320
    pmid: '36173614'
    type:
    - Other
    version: '2.0'
  - doi: 10.1021/acs.jproteome.1c00528
    metadata:
      abstract: Science is full of overlooked and undervalued research waiting to
        be rediscovered. Proteomics is no exception. In this perspective, we follow
        the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing
        tryptic peptides across animal species. This pioneering work directly led
        to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics.
        In the decades following, proteins continued to provide essential clues on
        evolutionary history. While technology has continued to improve, contemporary
        proteomics has strayed from this larger biological context, rarely comparing
        species or asking how protein structure, function, and interactions have evolved.
        Here we recombine proteomics with molecular phylogenetics, highlighting the
        value of framing proteomic results in a larger biological context and how
        almost forgotten research, though technologically surpassed, can still generate
        new ideas and illuminate our work from a different perspective. Though it
        is infeasible to read all research published on a large topic, looking up
        older papers can be surprisingly rewarding when rediscovering a "gem"at the
        end of a long citation chain, aided by digital collections and perpetually
        helpful librarians. Proper literature study reduces unnecessary repetition
        and allows research to be more insightful and impactful by truly standing
        on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/)
        as dataset MSV000087993.
      authors:
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 1
      date: '2021-10-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics
        Experiments in the Light of Proteomics'
    note: null
    pmcid: PMC8491155
    pmid: '34523928'
    type:
    - Review
    version: '2.0'
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - '1.0'
  - '2.0'
- accessibility: null
  additionDate: '2015-02-05T13:24:16Z'
  biotoolsCURIE: biotools:reditools
  biotoolsID: reditools
  collectionID:
  - ELIXIR-ITA-CNR
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-ITA-CNR
    note: null
    orcidid: https://orcid.org/0000-0002-6549-0114
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: ernesto.picardi@uniba.it
    fundrefid: null
    gridid: null
    name: Ernesto Picardi
    note: null
    orcidid: https://orcid.org/0000-0002-6549-0114
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://www.uniba.it/docenti/picardi-ernesto/en
  description: Python scripts to detect RNA editing in deep transcriptome sequencing
    data (RNAseq)
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/BioinfoUNIBA/REDItools
  download: []
  editPermission:
    authors:
    - ELIXIR-ITA-BARI
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: REDItoolDnaRna.py -i rnaseq.bam -f myreference.fa -o myoutputfolder
    input:
    - data:
        term: Alignment
        uri: http://edamontology.org/data_1916
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
    note: Run REDItools on RNA sequences
    operation:
    - term: Analysis
      uri: http://edamontology.org/operation_2945
    output:
    - data:
        term: Text data
        uri: http://edamontology.org/data_2526
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://github.com/BioinfoUNIBA/REDItools
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-02-09T14:59:52.330758Z'
  license: MIT
  link: []
  maturity: Mature
  name: REDItools
  operatingSystem:
  - Linux
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_012133
    version: null
  owner: ELIXIR-ITA-CNR
  publication:
  - doi: 10.1093/bioinformatics/btt287
    metadata:
      abstract: 'The reliable detection of RNA editing sites from massive sequencing
        data remains challenging and, although several methodologies have been proposed,
        no computational tools have been released to date. Here, we introduce REDItools
        a suite of python scripts to perform high-throughput investigation of RNA
        editing using next-generation sequencing data.Availability and implementation:
        REDItools are in python programming language and freely available at http://code.google.
        com/p/reditools/.Contact: or graziano.pesole@uniba.itSupplementary information:
        Supplementary data are available at Bioinformatics online. © 2013 The Author
        2013. Published by Oxford University Press. All rights reserved. For Permissions,
        please e-mail: journals.permissions@oup.com.'
      authors:
      - name: Picardi E.
      - name: Pesole G.
      citationCount: 201
      date: '2013-07-15T00:00:00Z'
      journal: Bioinformatics
      title: 'REDItools: High-throughput RNA editing detection made easy'
    note: null
    pmcid: null
    pmid: '23742983'
    type:
    - Primary
    version: 1.0-1.3
  - doi: 10.1186/s12859-020-03562-x
    metadata:
      abstract: 'Background: RNA editing is a widespread co-/post-transcriptional
        mechanism that alters primary RNA sequences through the modification of specific
        nucleotides and it can increase both the transcriptome and proteome diversity.
        The automatic detection of RNA-editing from RNA-seq data is computational
        intensive and limited to small data sets, thus preventing a reliable genome-wide
        characterisation of such process. Results: In this work we introduce HPC-REDItools,
        an upgraded tool for accurate RNA-editing events discovery from large dataset
        repositories. Availability: https://github.com/BioinfoUNIBA/REDItools2. Conclusions:
        HPC-REDItools is dramatically faster than the previous version, REDItools,
        enabling big-data analysis by means of a MPI-based implementation and scaling
        almost linearly with the number of available cores.'
      authors:
      - name: Flati T.
      - name: Gioiosa S.
      - name: Spallanzani N.
      - name: Tagliaferri I.
      - name: Diroma M.A.
      - name: Pesole G.
      - name: Chillemi G.
      - name: Picardi E.
      - name: Castrignano T.
      citationCount: 21
      date: '2020-08-21T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'HPC-REDItools: A novel HPC-aware tool for improved large scale RNA-editing
        analysis'
    note: null
    pmcid: PMC7446188
    pmid: '32838738'
    type: []
    version: '2.0'
  - doi: 10.1038/s41596-019-0279-7
    metadata:
      abstract: RNA editing is a widespread post-transcriptional mechanism able to
        modify transcripts through insertions/deletions or base substitutions. It
        is prominent in mammals, in which millions of adenosines are deaminated to
        inosines by members of the ADAR family of enzymes. A-to-I RNA editing has
        a plethora of biological functions, but its detection in large-scale transcriptome
        datasets is still an unsolved computational task. To this aim, we developed
        REDItools, the first software package devoted to the RNA editing profiling
        in RNA-sequencing (RNAseq) data. It has been successfully used in human transcriptomes,
        proving the tissue and cell type specificity of RNA editing as well as its
        pervasive nature. Outcomes from large-scale REDItools analyses on human RNAseq
        data have been collected in our specialized REDIportal database, containing
        more than 4.5 million events. Here we describe in detail two bioinformatic
        procedures based on our computational resources, REDItools and REDIportal.
        In the first procedure, we outline a workflow to detect RNA editing in the
        human cell line NA12878, for which transcriptome and whole genome data are
        available. In the second procedure, we show how to identify dysregulated editing
        at specific recoding sites in post-mortem brain samples of Huntington disease
        donors. On a 64-bit computer running Linux with ≥32 GB of random-access memory
        (RAM), both procedures should take ~76 h, using 4 to 24 cores. Our protocols
        have been designed to investigate RNA editing in different organisms with
        available transcriptomic and/or genomic reads. Scripts to complete both procedures
        and a docker image are available at https://github.com/BioinfoUNIBA/REDItools.
      authors:
      - name: Lo Giudice C.
      - name: Tangaro M.A.
      - name: Pesole G.
      - name: Picardi E.
      citationCount: 69
      date: '2020-03-01T00:00:00Z'
      journal: Nature Protocols
      title: Investigating RNA editing in deep transcriptome datasets with REDItools
        and REDIportal
    note: null
    pmcid: null
    pmid: '31996844'
    type: []
    version: null
  - doi: 10.1007/978-1-0716-1307-8_14
    metadata:
      abstract: RNA editing by A-to-I deamination is a relevant co/posttranscriptional
        modification carried out by ADAR enzymes. In humans, it has pivotal cellular
        effects and its deregulation has been linked to a variety of human disorders
        including neurological and neurodegenerative diseases and cancer. Despite
        its biological relevance, the detection of RNA editing variants in large transcriptome
        sequencing experiments (RNAseq) is yet a challenging computational task. To
        drastically reduce computing times we have developed a novel REDItools version
        able to identify A-to-I events in huge amount of RNAseq data employing High
        Performance Computing (HPC) infrastructures. Here we show how to use REDItools
        v2 in HPC systems.
      authors:
      - name: Giudice C.L.
      - name: Mansi L.
      - name: Flati T.
      - name: Gioiosa S.
      - name: Chillemi G.
      - name: Libro P.
      - name: Castrignano T.
      - name: Pesole G.
      - name: Picardi E.
      citationCount: 1
      date: '2021-01-01T00:00:00Z'
      journal: Methods in Molecular Biology
      title: RNA Editing Detection in HPC Infrastructures
    note: null
    pmcid: null
    pmid: '33835447'
    type:
    - Usage
    version: null
  - doi: 10.1002/0471250953.bi1212s49
    metadata:
      abstract: RNAediting is a post-transcriptional/co-transcriptional molecular
        phenomenon whereby a genetic message is modified from the corresponding DNA
        template by means of substitutions, insertions, and/or deletions. It occurs
        in a variety of organisms and different cellular locations through evolutionally
        and biochemically unrelated proteins. RNA editing has a plethora of biological
        effects including the modulation of alternative splicing and fine-tuning of
        gene expression. RNA editing events by base substitutions can be detected
        on a genomic scale by NGS technologies through the REDItools package, an ad
        hoc suite of Python scripts to study RNA editing using RNA-Seq and DNA-Seq
        data or RNA-Seq data alone. REDItools implement effective filters to minimize
        biases due to sequencing errors, mapping errors, and SNPs. The package is
        freely available at Google Code repository (http://code.google.com/p/reditools/)
        and released under the MIT license. In the present unit we show three basic
        protocols corresponding to three main REDItools scripts.
      authors:
      - name: Picardi E.
      - name: D'Erchia A.M.
      - name: A. Antonio
      - name: G. Graziano
      citationCount: 25
      date: '2015-01-01T00:00:00Z'
      journal: Current Protocols in Bioinformatics
      title: Using REDItools to detect RNA editing events in NGS datasets
    note: null
    pmcid: null
    pmid: '25754992'
    type:
    - Usage
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 1
  version:
  - '1.3'
  - '2.0'
- accessibility: null
  additionDate: '2024-01-18T10:05:20.317333Z'
  biotoolsCURIE: biotools:mass_dynamics
  biotoolsID: mass_dynamics
  collectionID: []
  community: null
  confidence_flag: null
  cost: null
  credit: []
  description: A software platform for analysis and visualization of label-free and
    tandem mass tag (TMT) data-dependent acquisition (DDA) bottom-up proteomics data,
    including pathway and gene set enrichment analyses.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format: []
    note: null
    operation:
    - term: Analysis
      uri: http://edamontology.org/operation_2945
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format: []
  homepage: https://massdynamics.com/
  homepage_status: 0
  language: []
  lastUpdate: '2024-01-18T12:57:09.002286Z'
  license: null
  link: []
  maturity: null
  name: Mass Dynamics
  operatingSystem: []
  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1021/acs.jproteome.1c00683
    metadata:
      abstract: 'Label-free quantification (LFQ) of shotgun proteomics data is a popular
        and robust method for the characterization of relative protein abundance between
        samples. Many analytical pipelines exist for the automation of this analysis,
        and some tools exist for the subsequent representation and inspection of the
        results of these pipelines. Mass Dynamics 1.0 (MD 1.0) is a web-based analysis
        environment that can analyze and visualize LFQ data produced by software such
        as MaxQuant. Unlike other tools, MD 1.0 utilizes a cloud-based architecture
        to enable researchers to store their data, enabling researchers to not only
        automatically process and visualize their LFQ data but also annotate and share
        their findings with collaborators and, if chosen, to easily publish results
        to the community. With a view toward increased reproducibility and standardization
        in proteomics data analysis and streamlining collaboration between researchers,
        MD 1.0 requires minimal parameter choices and automatically generates quality
        control reports to verify experiment integrity. Here, we demonstrate that
        MD 1.0 provides reliable results for protein expression quantification, emulating
        Perseus on benchmark datasets over a wide dynamic range. The MD 1.0 platform
        is available globally via: https://app.massdynamics.com/.'
      authors:
      - name: Bloom J.
      - name: Triantafyllidis A.
      - name: Quaglieri A.
      - name: Burton Ngov P.
      - name: Infusini G.
      - name: Webb A.
      citationCount: 1
      date: '2021-11-05T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'Mass Dynamics 1.0: A Streamlined, Web-Based Environment for Analyzing,
        Sharing, and Integrating Label-Free Data'
    note: null
    pmcid: null
    pmid: '34647461'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1101/2022.12.12.517480
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: '2.0'
  relation: []
  toolType: []
  topic: []
  validated: 0
  version:
  - '1.0'
  - '2.0'
- accessibility: Open access
  additionDate: '2023-07-25T12:35:27.605861Z'
  biotoolsCURIE: biotools:macpepdb_-_mass_centric_peptide_database
  biotoolsID: macpepdb_-_mass_centric_peptide_database
  collectionID:
  - CUBiMed.RUB
  - BioInfra.Prot
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Julian Uszkoreit
    note: null
    orcidid: http://orcid.org/0000-0001-7522-4007
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: dirk.winkelhardt@rub.de
    fundrefid: null
    gridid: null
    name: Dirk Winkelhardt
    note: null
    orcidid: https://orcid.org/0000-0001-8770-2221
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: PD Dr. Martin Eisenacher
    note: null
    orcidid: https://orcid.org/0000-0003-2687-7444
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: A Database to Quickly Access All Tryptic Peptides of the UniProtKB
  documentation:
  - note: null
    type:
    - API documentation
    url: https://macpepdb.mpc.rub.de/docs/api
  - note: null
    type:
    - Installation instructions
    url: https://github.com/mpc-bioinformatics/macpepdb/blob/main/Readme.md
  download: []
  editPermission:
    authors:
    - di_hardt
    - julianu
    - BioInfra.Prot
    type: group
  elixirCommunity: []
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://macpepdb.mpc.rub.de/
  homepage_status: 0
  language:
  - Python
  - JavaScript
  - SQL
  lastUpdate: '2023-11-29T13:25:34.614492Z'
  license: null
  link:
  - note: Backend implementation written in Flask
    type:
    - Repository
    url: https://github.com/mpc-bioinformatics/macpepdb
  - note: Frontend implementation written in NuxtJS
    type:
    - Repository
    url: https://github.com/mpc-bioinformatics/macpepdb
  maturity: Mature
  name: MaCPepDB - Mass Centric Peptide Database
  operatingSystem: []
  otherID: []
  owner: di_hardt
  publication:
  - doi: 10.1021/acs.jproteome.0c00967
    metadata:
      abstract: Protein sequence databases play a crucial role in the majority of
        the currently applied mass-spectrometry-based proteomics workflows. Here UniProtKB
        serves as one of the major sources, as it combines the information of several
        smaller databases and enriches the entries with additional biological information.
        For the identification of peptides in a sample by tandem mass spectra, as
        generated by data-dependent acquisition, protein sequence databases provide
        the basis for most spectrum identification search engines. In addition, for
        targeted proteomics approaches like selected reaction monitoring (SRM) and
        parallel reaction monitoring (PRM), knowledge of the peptide sequences, their
        masses, and whether they are unique for a protein is essential. Because most
        bottom-up proteomics approaches use trypsin to cleave the proteins in a sample,
        the tryptic peptides contained in a protein database are of great interest.
        We present a database, called MaCPepDB (mass-centric peptide database), that
        consists of the complete tryptic digest of the Swiss-Prot and TrEMBL parts
        of UniProtKB. This database is especially designed to not only allow queries
        of peptide sequences and return the respective information about connected
        proteins and thus whether a peptide is unique but also allow queries of specific
        masses of peptides or precursors of MS/MS spectra. Furthermore, posttranslational
        modifications can be considered in a query as well as different mass deviations
        for posttranslational modifications. Hence the database can be used by a sequence
        query not only to, for example, check in which proteins of the UniProt database
        a tryptic peptide can be found but also to find possibly interfering peptides
        in PRM/SRM experiments using the mass query. The complete database contains
        currently 5 939 244 990 peptides from 185 561 610 proteins (UniProt version
        2020_03), for which a single query usually takes less than 1 s. For easy exploration
        of the data, a web interface was developed. A REST application programming
        interface (API) for programmatic and workflow access is also available at
        https://macpepdb.mpc.rub.de.
      authors:
      - name: Uszkoreit J.
      - name: Winkelhardt D.
      - name: Barkovits K.
      - name: Wulf M.
      - name: Roocke S.
      - name: Marcus K.
      - name: Eisenacher M.
      citationCount: 4
      date: '2021-04-02T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'MaCPepDB: A Database to Quickly Access All Tryptic Peptides of the UniProtKB'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: '1.0'
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version:
  - 2.3.0
- accessibility: Open access
  additionDate: '2021-05-17T08:32:18Z'
  biotoolsCURIE: biotools:lineagespot
  biotoolsID: lineagespot
  collectionID:
  - COVID-19
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: fpsom@certh.gr
    fundrefid: null
    gridid: null
    name: Fotis E. Psomopoulos
    note: null
    orcidid: https://orcid.org/0000-0002-0222-4273
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Nikolaos Pechlivanis,
    note: null
    orcidid: https://orcid.org/0000-0003-2502-612X
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Maria Tsagiopoulou
    note: null
    orcidid: https://orcid.org/0000-0002-1653-0327
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: Lineagespot is a framework written in R, and aims to identify and assign
    different SARS-CoV-2 lineages based on a single variant file (i.e., variant calling
    format).
  documentation: []
  download: []
  editPermission:
    authors:
    - ELIXIR-CZ
    type: group
  elixirCommunity: []
  elixirNode:
  - Greece
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Variant calling
      uri: http://edamontology.org/operation_3227
    output: []
  homepage: https://github.com/BiodataAnalysisGroup/lineagespot
  homepage_status: 0
  language:
  - R
  lastUpdate: '2023-11-03T00:00:55.232555Z'
  license: MIT
  link: []
  maturity: Emerging
  name: lineagespot
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: fpsom
  publication:
  - doi: 10.1038/s41598-022-06625-6
    metadata: null
    note: null
    pmcid: PMC8854625
    pmid: '35177697'
    type: []
    version: '1.0'
  relation: []
  toolType:
  - Library
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  - term: Evolutionary biology
    uri: http://edamontology.org/topic_3299
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  validated: 0
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2018-02-02T09:49:44Z'
  biotoolsCURIE: biotools:v-pipe
  biotoolsID: v-pipe
  collectionID:
  - COVID-19
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: susana.posada@bsse.ethz.ch
    fundrefid: null
    gridid: null
    name: Susana Posada Céspedes
    note: null
    orcidid: https://orcid.org/0000-0002-7459-8186
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/sposadac
  - email: david.seifert@bsse.ethz.ch
    fundrefid: null
    gridid: null
    name: David Seifert
    note: null
    orcidid: https://orcid.org/0000-0003-4739-5110
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/SoapZA
  - email: niko.beerenwinkel@bsse.ethz.ch
    fundrefid: null
    gridid: null
    name: Niko Beerenwinkel
    note: null
    orcidid: https://orcid.org/0000-0002-0573-6119
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: https://bsse.ethz.ch/cbg/group/people/person-detail.html?persid=149417
  - email: ivan.topolsky@sib.swiss
    fundrefid: null
    gridid: null
    name: Ivan Topolsky
    note: null
    orcidid: https://orcid.org/0000-0002-7561-0810
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: https://www.sib.swiss/directory?cn=ivan%20topolsky
  - email: null
    fundrefid: null
    gridid: null
    name: Computational Biology Group
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole: []
    url: https://bsse.ethz.ch/cbg
  - email: null
    fundrefid: null
    gridid: null
    name: D-BSSE
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole: []
    url: https://bsse.ethz.ch/
  - email: null
    fundrefid: null
    gridid: grid.5801.c
    name: ETHZ
    note: null
    orcidid: null
    rorid: 05a28rw58
    typeEntity: Institute
    typeRole: []
    url: https://ethz.ch/de.html
  - email: null
    fundrefid: null
    gridid: grid.419765.8
    name: SIB Swiss Institute of Bioinformatics
    note: null
    orcidid: null
    rorid: 002n09z45
    typeEntity: Institute
    typeRole: []
    url: https://www.sib.swiss/
  - email: v-pipe@bsse.ethz.ch
    fundrefid: null
    gridid: null
    name: V-pipe Dev Team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Bioinformatics pipeline for the analysis of next-generation sequencing
    data derived from intra-host viral populations.
  documentation:
  - note: null
    type:
    - General
    url: https://cbg-ethz.github.io/V-pipe/usage/
  - note: Getting Started
    type:
    - User manual
    url: https://github.com/cbg-ethz/V-pipe/blob/master/README.md
  - note: User configurable options
    type:
    - User manual
    url: https://github.com/cbg-ethz/V-pipe/blob/master/config/README.md
  - note: V-pipe as a benchmark tool
    type:
    - Other
    url: https://github.com/cbg-ethz/V-pipe/wiki/benchmark
  - note: customize the workflow
    type:
    - Other
    url: https://github.com/cbg-ethz/V-pipe/wiki/snakemake
  - note: Video introduction to V-pipe
    type:
    - Training material
    url: https://youtu.be/qHEUVJZsgE4
  - note: 'Tutorial: how to use V-pipe (specifically for SARS-CoV-2 data).'
    type:
    - Training material
    url: https://cbg-ethz.github.io/V-pipe/tutorial/sars-cov2/
  - note: 'Webinar: Applying V-pipe to SARS-Coronavirus-2 data'
    type:
    - Training material
    url: https://youtu.be/pIby1UooK94
  download:
  - note: GitHub repository
    type: Source code
    url: https://github.com/cbg-ethz/V-pipe
    version: null
  - note: Docker image
    type: Container file
    url: https://github.com/cbg-ethz/V-pipe/pkgs/container/v-pipe
    version: null
  - note: Snakedeploy workflow
    type: Tool wrapper (Other)
    url: https://snakemake.github.io/snakemake-workflow-catalog/?usage=cbg-ethz/V-pipe
    version: null
  editPermission:
    authors:
    - ELIXIR-CZ
    type: group
  elixirCommunity: []
  elixirNode:
  - Switzerland
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: 'curl -O ''https://raw.githubusercontent.com/cbg-ethz/V-pipe/master/utils/quick_install.sh''

      bash quick_install.sh -b sars-cov2 -p V-pipe-installation/ -w working/

      cd V-pipe-installation/working/

      mkdir -p samples/patient_1/20200409/raw_data

      cp ~/Download/reads_R{1,2}.fastq.gz samples/patient_1/20200409/raw_data/

      ./vpipe -p --cores 2


      ls samples/patient_1/20200409/variants/SNVs/snvs.vcf

      ls samples//variants/SNVs/REGION_*/support/*.fasgz'
    input:
    - data:
        term: Nucleic acid sequence (raw)
        uri: http://edamontology.org/data_2975
      format: []
    note: Please consult wiki or tutorial for the directory structure of the raw reads
      input.
    operation:
    - term: Read pre-processing
      uri: http://edamontology.org/operation_3219
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    - term: Genetic variation analysis
      uri: http://edamontology.org/operation_3197
    output:
    - data:
        term: Genotype/phenotype report
        uri: http://edamontology.org/data_0920
      format:
      - term: VCF
        uri: http://edamontology.org/format_3016
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://cbg-ethz.github.io/V-pipe/
  homepage_status: 0
  language:
  - Shell
  - Python
  lastUpdate: '2023-11-02T19:54:55.052030Z'
  license: Apache-2.0
  link:
  - note: GitHub issue tracker
    type:
    - Issue tracker
    url: https://github.com/cbg-ethz/V-pipe/issues
  - note: Sympa ETHZ mailing list
    type:
    - Mailing list
    url: https://sympa.ethz.ch/sympa/info/v-pipe-users
  - note: GitHub repository
    type:
    - Repository
    url: https://github.com/cbg-ethz/V-pipe
  - note: ExPASy - SIB Bioinformatics Resource Portal
    type:
    - Software catalogue
    url: https://www.expasy.org/resources/v-pipe
  - note: SIB Software Resource
    type:
    - Software catalogue
    url: https://www.sib.swiss/services/open-software-and-databases#v-pipe
  - note: WorkflowHub
    type:
    - Software catalogue
    url: https://workflowhub.eu/workflows/301
  maturity: Mature
  name: V-pipe
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: DrYak
  publication:
  - doi: 10.1093/bioinformatics/btab015
    metadata: null
    note: null
    pmcid: null
    pmid: '33471068'
    type:
    - Primary
    version: 1.0, 2.0
  - doi: 10.20944/preprints202005.0376.v1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Review
    version: null
  - doi: 10.1016/j.virusres.2016.09.016
    metadata: null
    note: null
    pmcid: null
    pmid: '27693290'
    type:
    - Other
    version: null
  - doi: 10.3390/v10050256
    metadata: null
    note: null
    pmcid: PMC5977249
    pmid: '29757994'
    type:
    - Other
    version: null
  - doi: 10.1093/infdis/jiz094
    metadata: null
    note: null
    pmcid: PMC8289377
    pmid: '30835266'
    type:
    - Usage
    version: null
  - doi: 10.2807/1560-7917.es.2020.25.32.2001410
    metadata: null
    note: V-pipe was used to process a major part of the Swiss samples in this pan-European
      study.
    pmcid: PMC7427299
    pmid: '32794443'
    type:
    - Usage
    version: sars-cov2
  - doi: 10.1101/2020.10.12.335919
    metadata: null
    note: Raw reads from SRA public data and Swiss cohort were processed using V-pipe
    pmcid: null
    pmid: null
    type:
    - Usage
    version: sars-cov2
  - doi: 10.1101/2020.10.14.20212621
    metadata: null
    note: V-pipe was used to process a major part of the Swiss samples
    pmcid: null
    pmid: null
    type:
    - Usage
    version: sars-cov2
  - doi: 10.1101/2021.01.08.21249379
    metadata: null
    note: The waste water samples were analyzed using V-pipe and additional custom
      scripts.
    pmcid: null
    pmid: null
    type:
    - Usage
    version: sars-cov2-dev
  - doi: 10.1016/j.epidem.2021.100480
    metadata: null
    note: V-pipe is used within the S3C (Swiss SARS-CoV-2 Sequencing Consortium) to
      provide sequences.
    pmcid: PMC8452947
    pmid: '34488035'
    type:
    - Usage
    version: sars-cov2
  - doi: 10.3390/v13030496
    metadata: null
    note: V-pipe and the S3C (Swiss SARS-CoV-2 Sequencing Consortium) infrastructure
      were used to QA and pre-process the sequencing data.
    pmcid: PMC8002591
    pmid: '33802899'
    type:
    - Usage
    version: sars-cov2
  - doi: 10.1016/j.coviro.2021.06.002
    metadata: null
    note: Diversity measures used in V-pipe
    pmcid: null
    pmid: '34153841'
    type:
    - Method
    version: v2.99.2
  relation:
  - biotoolsID: shorah
    type: uses
  - biotoolsID: haploclique
    type: uses
  - biotoolsID: quasirecomb
    type: uses
  - biotoolsID: bwa
    type: uses
  - biotoolsID: prinseq
    type: uses
  - biotoolsID: MAFFT
    type: uses
  - biotoolsID: samtools
    type: uses
  - biotoolsID: picard_samtofastq
    type: uses
  - biotoolsID: snakemake
    type: uses
  - biotoolsID: bioconda
    type: uses
  toolType:
  - Command-line tool
  - Workflow
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Population genetics
    uri: http://edamontology.org/topic_3056
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Virology
    uri: http://edamontology.org/topic_0781
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  validated: 1
  version:
  - v2.99.2
  - v2.99.1
  - v2.99.0
  - v2.0
  - v1.0
- accessibility: Open access
  additionDate: '2023-09-26T23:32:38.521840Z'
  biotoolsCURIE: biotools:planetmicrobe
  biotoolsID: planetmicrobe
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: bhurwitz@arizona.edu
    fundrefid: null
    gridid: null
    name: Bonnie Hurwitz
    note: Professor at the University of Arizona known for her work in cyberinfrastructure
      development.
    orcidid: https://orcid.org/0000-0001-8699-957X
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.hurwitzlab.org/
  - email: aponsero@arizona.edu
    fundrefid: null
    gridid: null
    name: Alise Ponsero
    note: null
    orcidid: https://orcid.org/0000-0002-4125-7561
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: kblumberg@arizona.edu
    fundrefid: null
    gridid: null
    name: Kai Blumberg
    note: null
    orcidid: https://orcid.org/0000-0002-3410-4655
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: mattmiller899@arizona.edu
    fundrefid: null
    gridid: null
    name: Matthew Miller
    note: null
    orcidid: https://orcid.org/0000-0002-3491-8763
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: mbomhoff@arizona.edu
    fundrefid: null
    gridid: null
    name: Matthew Bomhoff
    note: null
    orcidid: https://orcid.org/0000-0002-8014-9184
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: kyclark@arizona.edu
    fundrefid: null
    gridid: null
    name: Ken Youens-Clark
    note: null
    orcidid: https://orcid.org/0000-0001-9961-144X
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: Enabling the discovery and integration of oceanographic ‘omics, environmental
    and physiochemical data layers.
  documentation:
  - note: Documentation on how to use the website
    type:
    - General
    url: https://hurwitzlab.gitbook.io/planet-microbe-documentation/
  download:
  - note: Source code for the website
    type: Source code
    url: https://github.com/hurwitzlab/planet-microbe-app
    version: '1.0'
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    - term: Sequence clustering
      uri: http://edamontology.org/operation_0291
    - term: Aggregation
      uri: http://edamontology.org/operation_3436
    - term: Sequence annotation
      uri: http://edamontology.org/operation_0361
    output: []
  homepage: https://www.planetmicrobe.org/
  homepage_status: 0
  language:
  - Elm
  lastUpdate: '2023-09-26T23:32:38.524518Z'
  license: MIT
  link:
  - note: Planet Microbe Application
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-app
  - note: Planet Microbe frictionless data packages
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-datapackages
  - note: Planet Microbe ontology
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-ontology
  - note: Functional Annotation Pipeline
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-functional-annotation
  - note: Semantic web analysis
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-semantic-web-analysis
  maturity: Mature
  name: Planet Microbe
  operatingSystem:
  - Linux
  otherID: []
  owner: bhurwitz
  publication:
  - doi: 10.1093/nar/gkaa637
    metadata:
      abstract: In recent years, large-scale oceanic sequencing efforts have provided
        a deeper understanding of marine microbial communities and their dynamics.
        These research endeavors require the acquisition of complex and varied datasets
        through large, interdisciplinary and collaborative efforts. However, no unifying
        framework currently exists for the marine science community to integrate sequencing
        data with physical, geological, and geochemical datasets. Planet Microbe is
        a web-based platform that enables data discovery from curated historical and
        ongoing oceanographic sequencing efforts. In Planet Microbe, each 'omics sample
        is linked with other biological and physiochemical measurements collected
        for the same water samples or during the same sample collection event, to
        provide a broader environmental context. This work highlights the need for
        curated aggregation efforts that can enable new insights into high-quality
        metagenomic datasets. Planet Microbe is freely accessible from https://www.planetmicrobe.org/.
      authors:
      - name: Ponsero A.J.
      - name: Bomhoff M.
      - name: Blumberg K.
      - name: Youens-Clark K.
      - name: Herz N.M.
      - name: Wood-Charlson E.M.
      - name: Delong E.F.
      - name: Hurwitz B.L.
      citationCount: 11
      date: '2021-01-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Planet Microbe: A platform for marine microbiology to discover and analyze
        interconnected ''omics and environmental data'''
    note: In recent years, large-scale oceanic sequencing efforts have provided a
      deeper understanding of marine microbial communities and their dynamics. These
      research endeavors require the acquisition of complex and varied datasets through
      large, interdisciplinary and collaborative efforts. However, no unifying framework
      currently exists for the marine science community to integrate sequencing data
      with physical, geological, and geochemical datasets. Planet Microbe is a web-based
      platform that enables data discovery from curated historical and on-going oceanographic
      sequencing efforts. In Planet Microbe, each 'omics sample is linked with other
      biological and physiochemical measurements collected for the same water samples
      or during the same sample collection event, to provide a broader environmental
      context. This work highlights the need for curated aggregation efforts that
      can enable new insights into high-quality metagenomic datasets.
    pmcid: PMC7778950
    pmid: '32735679'
    type:
    - Primary
    version: '1.0'
  relation: []
  toolType:
  - Bioinformatics portal
  topic:
  - term: Marine biology
    uri: http://edamontology.org/topic_3387
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  validated: 0
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2023-09-26T23:26:58.411470Z'
  biotoolsCURIE: biotools:planet_microbe
  biotoolsID: planet_microbe
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: bhurwitz@arizona.edu
    fundrefid: null
    gridid: null
    name: Bonnie Hurwitz
    note: Professor at the University of Arizona known for her work in cyberinfrastructure
      development.
    orcidid: https://orcid.org/0000-0001-8699-957X
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.hurwitzlab.org/
  - email: aponsero@arizona.edu
    fundrefid: null
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    name: Alise Ponsero
    note: null
    orcidid: https://orcid.org/0000-0002-4125-7561
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: kblumberg@arizona.edu
    fundrefid: null
    gridid: null
    name: Kai Blumberg
    note: null
    orcidid: https://orcid.org/0000-0002-3410-4655
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: mattmiller899@arizona.edu
    fundrefid: null
    gridid: null
    name: Matthew Miller
    note: null
    orcidid: https://orcid.org/0000-0002-3491-8763
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: mbomhoff@arizona.edu
    fundrefid: null
    gridid: null
    name: Matthew Bomhoff
    note: null
    orcidid: https://orcid.org/0000-0002-8014-9184
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: kyclark@arizona.edu
    fundrefid: null
    gridid: null
    name: Ken Youens-Clark
    note: null
    orcidid: https://orcid.org/0000-0001-9961-144X
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: Enabling the discovery and integration of oceanographic ‘omics, environmental
    and physiochemical data layers.
  documentation: []
  download:
  - note: Source code for the website
    type: Source code
    url: https://github.com/hurwitzlab/planet-microbe-app
    version: '1.0'
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    - term: Sequence clustering
      uri: http://edamontology.org/operation_0291
    - term: Aggregation
      uri: http://edamontology.org/operation_3436
    - term: Sequence annotation
      uri: http://edamontology.org/operation_0361
    output: []
  homepage: https://www.planetmicrobe.org/
  homepage_status: 0
  language:
  - Elm
  lastUpdate: '2023-09-26T23:26:58.414386Z'
  license: MIT
  link:
  - note: Planet Microbe Application
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-app
  - note: Planet Microbe frictionless data packages
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-datapackages
  - note: Planet Microbe ontology
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-ontology
  - note: Functional Annotation Pipeline
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-functional-annotation
  - note: Semantic web analysis
    type:
    - Repository
    url: https://github.com/hurwitzlab/planet-microbe-semantic-web-analysis
  maturity: Mature
  name: Planet Microbe
  operatingSystem:
  - Linux
  otherID: []
  owner: bhurwitz
  publication:
  - doi: 10.1093/nar/gkaa637
    metadata:
      abstract: In recent years, large-scale oceanic sequencing efforts have provided
        a deeper understanding of marine microbial communities and their dynamics.
        These research endeavors require the acquisition of complex and varied datasets
        through large, interdisciplinary and collaborative efforts. However, no unifying
        framework currently exists for the marine science community to integrate sequencing
        data with physical, geological, and geochemical datasets. Planet Microbe is
        a web-based platform that enables data discovery from curated historical and
        ongoing oceanographic sequencing efforts. In Planet Microbe, each 'omics sample
        is linked with other biological and physiochemical measurements collected
        for the same water samples or during the same sample collection event, to
        provide a broader environmental context. This work highlights the need for
        curated aggregation efforts that can enable new insights into high-quality
        metagenomic datasets. Planet Microbe is freely accessible from https://www.planetmicrobe.org/.
      authors:
      - name: Ponsero A.J.
      - name: Bomhoff M.
      - name: Blumberg K.
      - name: Youens-Clark K.
      - name: Herz N.M.
      - name: Wood-Charlson E.M.
      - name: Delong E.F.
      - name: Hurwitz B.L.
      citationCount: 11
      date: '2021-01-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Planet Microbe: A platform for marine microbiology to discover and analyze
        interconnected ''omics and environmental data'''
    note: In recent years, large-scale oceanic sequencing efforts have provided a
      deeper understanding of marine microbial communities and their dynamics. These
      research endeavors require the acquisition of complex and varied datasets through
      large, interdisciplinary and collaborative efforts. However, no unifying framework
      currently exists for the marine science community to integrate sequencing data
      with physical, geological, and geochemical datasets. Planet Microbe is a web-based
      platform that enables data discovery from curated historical and on-going oceanographic
      sequencing efforts. In Planet Microbe, each 'omics sample is linked with other
      biological and physiochemical measurements collected for the same water samples
      or during the same sample collection event, to provide a broader environmental
      context. This work highlights the need for curated aggregation efforts that
      can enable new insights into high-quality metagenomic datasets.
    pmcid: PMC7778950
    pmid: '32735679'
    type:
    - Primary
    version: '1.0'
  relation: []
  toolType:
  - Bioinformatics portal
  topic:
  - term: Marine biology
    uri: http://edamontology.org/topic_3387
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  validated: 0
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2016-03-17T13:51:10Z'
  biotoolsCURIE: biotools:webnma
  biotoolsID: webnma
  collectionID:
  - BiB tools
  - CBU tools
  - UiB tools
  - ELIXIR-NO
  - ELIXIR-Norway
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: Nathalie.Reuter@uib.no
    fundrefid: null
    gridid: null
    name: Nathalie Reuter
    note: null
    orcidid: https://orcid.org/0000-0002-3649-7675
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    url: http://www.cbu.uib.no/reuter/
  - email: null
    fundrefid: null
    gridid: null
    name: Sandhya P Tiwari
    note: null
    orcidid: https://orcid.org/0000-0002-0747-3826
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Kidane M Tekle
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Tristan Cragnolini
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Svenn H Grindhaug
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Lars Skjærven
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Gisle Salensminde
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Edvin Fuglebakk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Siv M Hollup
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Department of Molecular Biology, University of Bergen, Norway
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Computational Biology Unit, Department of Informatics, University of Bergen,
      Norway
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: UiB
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  description: WEBnm@ provides quick, automated computation and analysis of low-frequency
    normal modes for protein structures.
  documentation:
  - note: null
    type:
    - Quick start guide
    url: http://apps.cbu.uib.no/webnma3/howto/single
  - note: null
    type:
    - FAQ
    url: http://apps.cbu.uib.no/webnma3/qanda
  - note: null
    type:
    - General
    - Citation instructions
    url: http://apps.cbu.uib.no/webnma3/about
  download: []
  editPermission:
    authors:
    - eca008
    type: group
  elixirCommunity:
  - 3D-BioInfo
  elixirNode:
  - Norway
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: Constructs elastic network model from alpha carbon coordinates of the protein,
      and computes properties to describe large scale conformations. Computes normal
      modes, fluctuation profiles, inter-residue correlations, conformational overlap
      analysis and vector field representations. Structural amino acid profiles, and
      normal mode characteristics describing protein motion, visualized in plots and
      decorated structure visualizations. White space delimited tabular data for normal
      modes and the provided plots
    operation:
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Protein flexibility and motion analysis
      uri: http://edamontology.org/operation_0244
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
    - data:
        term: Sequence profile
        uri: http://edamontology.org/data_1354
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  - cmd: null
    input:
    - data:
        term: Structure alignment
        uri: http://edamontology.org/data_0886
      format:
      - term: FASTA-like (text)
        uri: http://edamontology.org/format_2200
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: Performs comparative analysis of the normal modes of protein structures.
      Computes the Bhattacharyya Coefficient (BC) and the Root Mean Squared Inner
      Product (RMSIP) of aligned parts of the proteins. Alignment of sets of proteins
      to be compared. Multiple protein structures Heatmaps, dendrograms and structural
      amino acid profiles for visual comparison of structural similarity. White space
      delimited tabular data for the provided plots
    operation:
    - term: Protein structure comparison
      uri: http://edamontology.org/operation_2487
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
    - data:
        term: Structural profile
        uri: http://edamontology.org/data_0889
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: http://apps.cbu.uib.no/webnma
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2023-08-02T12:26:28.035500Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    - Issue tracker
    url: https://github.com/reuter-group/webnma3
  - note: Helpdesk and support for ELIXIR Norway services.
    type:
    - Helpdesk
    url: https://elixir.no/helpdesk
  maturity: Mature
  name: WEBnma
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: UiB
  publication:
  - doi: 10.1186/s12859-014-0427-6
    metadata:
      abstract: 'Background: Normal mode analysis (NMA) using elastic network models
        is a reliable and cost-effective computational method to characterise protein
        flexibility and by extension, their dynamics. Further insight into the dynamics-function
        relationship can be gained by comparing protein motions between protein homologs
        and functional classifications. This can be achieved by comparing normal modes
        obtained from sets of evolutionary related proteins. Results: We have developed
        an automated tool for comparative NMA of a set of pre-aligned protein structures.
        The user can submit a sequence alignment in the FASTA format and the corresponding
        coordinate files in the Protein Data Bank (PDB) format. The computed normalised
        squared atomic fluctuations and atomic deformation energies of the submitted
        structures can be easily compared on graphs provided by the web user interface.
        The web server provides pairwise comparison of the dynamics of all proteins
        included in the submitted set using two measures: the Root Mean Squared Inner
        Product and the Bhattacharyya Coefficient. The Comparative Analysis has been
        implemented on our web server for NMA, WEBnmat, which also provides recently
        upgraded functionality for NMA of single protein structures. This includes
        new visualisations of protein motion, visualisation of inter-residue correlations
        and the analysis of conformational change using the. In addition, programmatic
        access to WEBnmat is now available through a SOAP-based web service. WEBnmat
        is available at. Conclusion: WEBnmat v2.0 is an online tool offering unique
        capability for comparative NMA on multiple protein structures. Along with
        a convenient web interface, powerful computing resources, and several methods
        for mode analyses, WEBnmat facilitates the assessment of protein flexibility
        within protein families and superfamilies. These analyses can give a good
        view of how the structures move and how the flexibility is conserved over
        the different structures.'
      authors:
      - name: Tiwari S.P.
      - name: Fuglebakk E.
      - name: Hollup S.M.
      - name: Skjaerven L.
      - name: Cragnolini T.
      - name: Grindhaug S.H.
      - name: Tekle K.M.
      - name: Reuter N.
      citationCount: 70
      date: '2014-12-30T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'WEBnmat v2.0: Web server and services for comparing protein flexibility'
    note: null
    pmcid: PMC4339738
    pmid: '25547242'
    type:
    - Primary
    version: '2.0'
  - doi: 10.1186/1471-2105-6-52
    metadata:
      abstract: 'Background: Normal mode analysis (NMA) has become the method of choice
        to investigate the slowest motions in macromolecular systems. NMA is especially
        useful for large biomolecular assemblies, such as transmembrane channels or
        virus capsids. NMA relies on the hypothesis that the vibrational normal modes
        having the lowest frequencies (also named soft modes) describe the largest
        movements in a protein and are the ones that are functionally relevant. Results:
        We developed a web-based server to perform normal modes calculations and different
        types of analyses. Starting from a structure file provided by the user in
        the PDB format, the server calculates the normal modes and subsequently offers
        the user a series of automated calculations; normalized squared atomic displacements,
        vector field representation and animation of the first six vibrational modes.
        Each analysis is performed independently from the others and results can be
        visualized using only a web browser. No additional plug-in or software is
        required. For users who would like to analyze the results with their favorite
        software, raw results can also be downloaded. The application is available
        on http://www.bioinfo.no/tools/normalmodes. We present here the underlying
        theory, the application architecture and an illustration of its features using
        a large transmembrane protein as an example. Conclusion: We built an efficient
        and modular web application for normal mode analysis of proteins. Non specialists
        can easily and rapidly evaluate the degree of flexibility of multi-domain
        protein assemblies and characterize the large amplitude movements of their
        domains. © 2005 Hollup et al; licensee BioMed Central Ltd.'
      authors:
      - name: Hollup S.M.
      - name: Salensminde G.
      - name: Reuter N.
      citationCount: 103
      date: '2005-03-11T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'WEBnm@: A web application for normal mode analyses of proteins'
    note: null
    pmcid: PMC1274249
    pmid: '15762993'
    type:
    - Primary
    version: '1.0'
  relation:
  - biotoolsID: numpy
    type: uses
  - biotoolsID: biopython
    type: uses
  - biotoolsID: matplotlib
    type: uses
  - biotoolsID: mustang
    type: uses
  - biotoolsID: dssp
    type: uses
  toolType:
  - Web API
  - Suite
  topic:
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Protein folds and structural domains
    uri: http://edamontology.org/topic_0736
  validated: 1
  version:
  - '3.5'
next: ?page=2
previous: null
