count: 1968
list:
- accessibility: Open access
  additionDate: '2024-03-12T10:56:44.977314Z'
  biotoolsCURIE: biotools:lorikeet
  biotoolsID: lorikeet
  collectionID: []
  community: null
  confidence_flag: null
  cost: null
  credit: []
  description: Tools for M. tuberculosis DNA fingerprinting (spoligotyping)
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    output: []
  homepage: https://github.com/AbeelLab/lorikeet
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-03-12T10:56:44.980036Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: lorikeet
  operatingSystem: []
  otherID: []
  owner: rlibouban
  publication: []
  relation: []
  toolType:
  - Bioinformatics portal
  topic:
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  validated: 0
  version:
  - '20'
- accessibility: Open access
  additionDate: '2021-01-18T10:10:48Z'
  biotoolsCURIE: biotools:ape
  biotoolsID: ape
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: v.kasalica@esciencecenter.nl
    fundrefid: null
    gridid: null
    name: Vedran Kasalica
    note: null
    orcidid: https://orcid.org/0000-0002-0097-1056
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: anna-lena.lamprecht@uni-potsdam.de
    fundrefid: null
    gridid: null
    name: Anna-Lena Lamprecht
    note: null
    orcidid: https://orcid.org/0000-0003-1953-5606
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: APE (the Automated Pipeline Explorer) as a command-line tool and API
    for automated composition of scientific workflows. APE is easily configured to
    a new application domain by providing it with a domain ontology and semantically
    annotated tools. It can then be used to synthesize purpose-specific workflows
    based on a specification of the available workflow inputs, desired outputs and
    possibly additional constraints.
  documentation:
  - note: null
    type:
    - API documentation
    url: https://ape-framework.readthedocs.io/
  download:
  - note: Download APE java library or the CLI
    type: Software package
    url: https://mvnrepository.com/artifact/io.github.sanctuuary/APE/2.1.7
    version: 2.1.7
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Retention time prediction
      uri: http://edamontology.org/operation_3633
    - term: Enrichment analysis
      uri: http://edamontology.org/operation_3501
    output: []
  homepage: https://github.com/sanctuuary/APE/
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-03-11T13:20:47.095494Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/sanctuuary/ape
  maturity: Mature
  name: APE
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: VKasalica
  publication:
  - doi: 10.1007/978-3-030-50436-6_34
    metadata:
      abstract: Automated workflow composition is bound to take the work with scientific
        workflows to the next level. On top of today’s comprehensive eScience infrastructure,
        it enables the automated generation of possible workflows for a given specification.
        However, functionality for automated workflow composition tends to be integrated
        with one of the many available workflow management systems, and is thus difficult
        or impossible to apply in other environments. Therefore we have developed
        APE (the Automated Pipeline Explorer) as a command-line tool and API for automated
        composition of scientific workflows. APE is easily configured to a new application
        domain by providing it with a domain ontology and semantically annotated tools.
        It can then be used to synthesize purpose-specific workflows based on a specification
        of the available workflow inputs, desired outputs and possibly additional
        constraints. The workflows can further be transformed into executable implementations
        and/or exported into standard workflow formats. In this paper we describe
        APE v1.0 and discuss lessons learned from applications in bioinformatics and
        geosciences.
      authors:
      - name: Kasalica V.
      - name: Lamprecht A.-L.
      citationCount: 10
      date: '2020-01-01T00:00:00Z'
      journal: Lecture Notes in Computer Science (including subseries Lecture Notes
        in Artificial Intelligence and Lecture Notes in Bioinformatics)
      title: 'Ape: A command-line tool and api for automated workflow composition'
    note: null
    pmcid: PMC7304703
    pmid: null
    type:
    - Primary
    version: null
  - doi: 10.1021/ACS.JPROTEOME.0C00983
    metadata:
      abstract: The bio.tools registry is a main catalogue of computational tools
        in the life sciences. More than 17 000 tools have been registered by the international
        bioinformatics community. The bio.tools metadata schema includes semantic
        annotations of tool functions, that is, formal descriptions of tools' data
        types, formats, and operations with terms from the EDAM bioinformatics ontology.
        Such annotations enable the automated composition of tools into multistep
        pipelines or workflows. In this Technical Note, we revisit a previous case
        study on the automated composition of proteomics workflows. We use the same
        four workflow scenarios but instead of using a small set of tools with carefully
        handcrafted annotations, we explore workflows directly on bio.tools. We use
        the Automated Pipeline Explorer (APE), a reimplementation and extension of
        the workflow composition method previously used. Moving "into the wild"opens
        up an unprecedented wealth of tools and a huge number of alternative workflows.
        Automated composition tools can be used to explore this space of possibilities
        systematically. Inevitably, the mixed quality of semantic annotations in bio.tools
        leads to unintended or erroneous tool combinations. However, our results also
        show that additional control mechanisms (tool filters, configuration options,
        and workflow constraints) can effectively guide the exploration toward smaller
        sets of more meaningful workflows.
      authors:
      - name: Kasalica V.
      - name: Schwammle V.
      - name: Palmblad M.
      - name: Ison J.
      - name: Lamprecht A.-L.
      citationCount: 7
      date: '2021-04-02T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'APE in the Wild: Automated Exploration of Proteomics Workflows in the
        bio.tools Registry'
    note: null
    pmcid: PMC8041394
    pmid: '33720735'
    type:
    - Benchmarking study
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Library
  topic:
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 1
  version:
  - 2.1.7
- accessibility: Open access
  additionDate: '2024-03-07T20:51:08.529472Z'
  biotoolsCURIE: biotools:oncoanalyser
  biotoolsID: oncoanalyser
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: Oncoanalyser is an nf-core Nextflow implementation of the tools developed
    by Hartwig Medical Foundation. The workflow is designed to comprehensively detect
    all variant types (SNV. MNV, InDel, SV, CNV, Fusions, Viral insertions, Telomere
    length, Genetic Immune Escape, mutational processes) as well as key tumor characteristics
    (purity, ploidy, TMB, MSI) from data derived from different short read platforms.
    The tooling is optimised for paired whole genome samples (90x tumor, 30x normal)
    but can be run on exome or panel (targeted) data. There is support for GRCh37
    and GRCh38 human reference genome builds.
  documentation: []
  download: []
  editPermission:
    authors:
    - jdeligt
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/nf-core/oncoanalyser/tree/dev
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-03-07T20:51:08.540443Z'
  license: GPL-3.0
  link:
  - note: GitHub page for issue tracking of Nextflow workflow implementation
    type:
    - Issue tracker
    - Repository
    url: https://github.com/nf-core/oncoanalyser/tree/dev
  - note: GitHub repository of underlying tools with issue tracking
    type:
    - Repository
    - Issue tracker
    url: https://github.com/hartwigmedical/hmftools
  maturity: Mature
  name: oncoanalyser
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: jdeligt
  publication: []
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Oncology
    uri: http://edamontology.org/topic_2640
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  validated: 0
  version:
  - '5.34'
- accessibility: Open access
  additionDate: '2024-03-07T16:28:23.426656Z'
  biotoolsCURIE: biotools:coredetector
  biotoolsID: coredetector
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: mario.fruzangohar@adelaide.edu.au
    fundrefid: null
    gridid: null
    name: Mario Fruzangohar
    note: null
    orcidid: https://orcid.org/0000-0003-3525-8338
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Julian Taylor
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Flexible and efficient program for core-genome alignment of evolutionary
    diverse genomes.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genome alignment
      uri: http://edamontology.org/operation_3182
    - term: Pairwise sequence alignment
      uri: http://edamontology.org/operation_0491
    - term: Global alignment
      uri: http://edamontology.org/operation_0496
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    output: []
  homepage: https://github.com/mfruzan/CoreDetector
  homepage_status: 0
  language:
  - Java
  - Bash
  - Perl
  - Python
  lastUpdate: '2024-03-07T16:28:23.438352Z'
  license: MIT
  link: []
  maturity: null
  name: CoreDetector
  operatingSystem:
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIOINFORMATICS/BTAD628
    metadata:
      abstract: 'Motivation: Whole genome alignment of eukaryote species remains an
        important method for the determination of sequence and structural variations
        and can also be used to ascertain the representative non-redundant core-genome
        sequence of a population. Many whole genome alignment tools were first developed
        for the more mature analysis of prokaryote species with few current tools
        containing the functionality to process larger genomes of eukaryotes as well
        as genomes of more divergent species. In addition, the functionality of these
        tools becomes computationally prohibitive due to the significant compute resources
        needed to handle larger genomes. Results: In this research, we present CoreDetector,
        an easy-to-use general-purpose program that can align the core-genome sequences
        for a range of genome sizes and divergence levels. To illustrate the flexibility
        of CoreDetector, we conducted alignments of a large set of closely related
        fungal pathogen and hexaploid wheat cultivar genomes as well as more divergent
        fly and rodent species genomes. In all cases, compared to existing multiple
        genome alignment tools, CoreDetector exhibited improved flexibility, efficiency,
        and competitive accuracy in tested cases. Availability and implementation:
        CoreDetector was developed in the cross platform, and easily deployable, Java
        language. A packaged pipeline is readily executable in a bash terminal without
        any external need for Perl or Python environments. Installation, example data,
        and usage instructions for CoreDetector are freely available from https://github.com/mfruzan/CoreDetector.'
      authors:
      - name: Fruzangohar M.
      - name: Moolhuijzen P.
      - name: Bakaj N.
      - name: Taylor J.
      citationCount: 0
      date: '2023-11-01T00:00:00Z'
      journal: Bioinformatics
      title: 'CoreDetector: a flexible and efficient program for core-genome alignment
        of evolutionary diverse genomes'
    note: null
    pmcid: PMC10663985
    pmid: '37878789'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Structural variation
    uri: http://edamontology.org/topic_3175
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-03-06T14:09:29.041228Z'
  biotoolsCURIE: biotools:starpep
  biotoolsID: starpep
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: ymarrero77@yahoo.es
    fundrefid: null
    gridid: null
    name: Yovani Marrero-Ponce
    note: null
    orcidid: https://orcid.org/0000-0003-2721-1142
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Longendri Aguilera-Mendoza
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: StarPep toolbox is a software for studying the antimicrobial peptides'
    (AMPs) chemical space with molecular network-based representations and similarity
    searching models. This application aims to contribute to peptide drug repurposing,
    development, and optimization.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Small molecule design
      uri: http://edamontology.org/operation_4009
    - term: Aggregation
      uri: http://edamontology.org/operation_3436
    - term: Clustering
      uri: http://edamontology.org/operation_3432
    output: []
  homepage: https://github.com/Grupo-Medicina-Molecular-y-Traslacional/StarPep
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-03-06T14:09:29.044226Z'
  license: Apache-2.0
  link: []
  maturity: null
  name: StarPep Toolbox
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIOINFORMATICS/BTAD506
    metadata:
      abstract: 'Motivation: Antimicrobial peptides (AMPs) are promising molecules
        to treat infectious diseases caused by multi-drug resistance pathogens, some
        types of cancer, and other conditions. Computer-aided strategies are efficient
        tools for the high-throughput screening of AMPs. Results: This report highlights
        StarPep Toolbox, an open-source and user-friendly software to study the bioactive
        chemical space of AMPs using complex network-based representations, clustering,
        and similarity-searching models. The novelty of this research lies in the
        combination of network science and similarity-searching techniques, distinguishing
        it from conventional methods based on machine learning and other computational
        approaches. The network-based representation of the AMP chemical space presents
        promising opportunities for peptide drug repurposing, development, and optimization.
        This approach could serve as a baseline for the discovery of a new generation
        of therapeutics peptides.'
      authors:
      - name: Aguilera-Mendoza L.
      - name: Ayala-Ruano S.
      - name: Martinez-Rios F.
      - name: Chavez E.
      - name: Garcia-Jacas C.R.
      - name: Brizuela C.A.
      - name: Marrero-Ponce Y.
      citationCount: 0
      date: '2023-08-01T00:00:00Z'
      journal: Bioinformatics
      title: 'StarPep Toolbox: an open-source software to assist chemical space analysis
        of bioactive peptides and their functions using complex networks'
    note: null
    pmcid: PMC10469104
    pmid: '37603724'
    type: []
    version: null
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Infectious disease
    uri: http://edamontology.org/topic_3324
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-02-25T15:05:48.723683Z'
  biotoolsCURIE: biotools:biolegato
  biotoolsID: biolegato
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: brian.fristensky@umanitoba.ca
    fundrefid: null
    gridid: null
    name: Brian Fristensky
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: BioLegato is a generic graphical user interface (GUI), in essence,
    a program that runs other programs. Data are displayed and selected in a canvas.
    A program is chosen from dropdown menus, parameters are set in a pop up menu,
    and the program launched by issuing a shell command to the system. Thus, any program,
    from a simple shell script to a complex analytical pipeline, can be launched from
    BioLegato.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Transcriptome assembly
      uri: http://edamontology.org/operation_3258
    output: []
  homepage: https://github.com/bfristensky/BioLegato/wiki
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-02-25T15:05:48.726827Z'
  license: CC-BY-NC-4.0
  link: []
  maturity: null
  name: BioLegato
  operatingSystem: []
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1186/S12859-023-05436-4
    metadata:
      abstract: 'Background: Biologists are faced with an ever-changing array of complex
        software tools with steep learning curves, often run on High Performance Computing
        platforms. To resolve the tradeoff between analytical sophistication and usability,
        we have designed BioLegato, a programmable graphical user interface (GUI)
        for running external programs. Results: BioLegato can run any program or pipeline
        that can be launched as a command. BioLegato reads specifications for each
        tool from files written in PCD, a simple language for specifying GUI components
        that set parameters for calling external programs. Thus, adding new tools
        to BioLegato can be done without changing the BioLegato Java code itself.
        The process is as simple as copying an existing PCD file and modifying it
        for the new program, which is more like filling in a form than writing code.
        PCD thus facilitates rapid development of new applications using existing
        programs as building blocks, and getting them to work together seamlessly.
        Conclusion: BioLegato applies Object-Oriented concepts to the user experience
        by organizing applications based on discrete data types and the methods relevant
        to that data. PCD makes it easier for BioLegato applications to evolve with
        the succession of analytical tools for bioinformatics. BioLegato is applicable
        not only in biology, but in almost any field in which disparate software tools
        need to work as an integrated system.'
      authors:
      - name: Alvare G.
      - name: Roche-Lima A.
      - name: Fristensky B.
      citationCount: 0
      date: '2023-12-01T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'BioLegato: a programmable, object-oriented graphic user interface'
    note: null
    pmcid: PMC10441721
    pmid: '37605108'
    type: []
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Computer science
    uri: http://edamontology.org/topic_3316
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-02-25T14:21:46.268659Z'
  biotoolsCURIE: biotools:omicssuite
  biotoolsID: omicssuite
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: OmicsSuite (https://omicssuite.github.io, https://github.com/OmicsSuite/),
    original name BioSciTools, a desktop program developed based on Java 11, aims
    to make new exploration and contribution to bioinformatics, and realize data analysis
    and visualization in the fields of sequence analysis, multi-omics (transcriptomics,
    genomics, protein omics, metabolomics, single cell), microbiology, clinical, etc.
  documentation: []
  download:
  - note: GitHub download page
    type: Downloads page
    url: https://omicssuite.github.io
    version: 1.4.0
  - note: SourceForge download
    type: Binaries
    url: https://sourceforge.net/projects/omicssuite-github-io/files/latest/download
    version: 1.4.0
  - note: ALiYun Drive
    type: Binaries
    url: https://www.aliyundrive.com/s/Defuhf7FVGw
    version: 1.4.0
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Alignment
        uri: http://edamontology.org/data_1916
      format: []
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format: []
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format: []
    - data:
        term: Matrix
        uri: http://edamontology.org/data_2082
      format: []
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format: []
    - data:
        term: Text data
        uri: http://edamontology.org/data_2526
      format: []
    note: null
    operation:
    - term: Analysis
      uri: http://edamontology.org/operation_2945
    - term: Alignment
      uri: http://edamontology.org/operation_2928
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: Binary format
        uri: http://edamontology.org/format_2333
      - term: RDF format
        uri: http://edamontology.org/format_2376
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://github.com/OmicsSuite/
  homepage_status: 0
  language:
  - Java
  - Python
  - R
  - JavaScript
  lastUpdate: '2024-02-25T14:22:11.738545Z'
  license: GPL-3.0
  link:
  - note: GitHub Organization
    type:
    - Repository
    url: https://github.com/OmicsSuite/
  - note: OmicsSuite Website
    type:
    - Helpdesk
    url: https://omicssuite.github.io
  - note: OmicsSuite Courses
    type:
    - Social media
    url: https://space.bilibili.com/34105515
  - note: OmicsSuite Paper
    type:
    - Helpdesk
    url: https://doi.org/10.1093/hr/uhad195
  maturity: Emerging
  name: OmicsSuite
  operatingSystem:
  - Windows
  otherID: []
  owner: benben.miao
  publication:
  - doi: 10.1093/hr/uhad195
    metadata:
      abstract: 'With the advancements in high-throughput sequencing technologies
        such as Illumina, PacBio, and 10X Genomics platforms, and gas/liquid chromatography-mass
        spectrometry, large volumes of biological data in multiple formats can now
        be obtained through multi-omics analysis. Bioinformatics is constantly evolving
        and seeking breakthroughs to solve multi-omics problems; however, it is challenging
        for most experimental biologists to analyse data using command-line interfaces,
        coding, and scripting. Based on experience with multi-omics, we have developed
        OmicsSuite, a desktop suite that comprehensively integrates statistics and
        multi-omics analysis and visualization. The suite has 175 sub-applications
        in 12 categories, including Sequence, Statistics, Algorithm, Genomics, Transcriptomics,
        Enrichment, Proteomics, Metabolomics, Clinical, Microorganism, Single Cell,
        and Table Operation. We created the user interface with Sequence View, Table
        View, and intelligent components based on JavaFX and the popular Shiny framework.
        The multi-omics analysis functions were developed based on BioJava and 300+
        packages provided by the R CRAN and Bioconductor communities, and it encompasses
        over 3000 adjustable parameter interfaces. OmicsSuite can directly read multi-omics
        raw data in FastA, FastQ, Mutation Annotation Format, mzML, Matrix, and HDF5
        formats, and the programs emphasize data transfer directions and pipeline
        analysis functions. OmicsSuite can produce pre-publication images and tables,
        allowing users to focus on biological aspects. OmicsSuite offers multi-omics
        step-by-step workflows that can be easily applied to horticultural plant breeding
        and molecular mechanism studies in plants. It enables researchers to freely
        explore the molecular information contained in multi-omics big data (Source:
        https://github.com/OmicsSuite/, Website: https://omicssuite.github.io, v1.3.9).'
      authors:
      - name: Miao B.-B.
      - name: Dong W.
      - name: Gu Y.-X.
      - name: Han Z.-F.
      - name: Luo X.
      - name: Ke C.-H.
      - name: You W.-W.
      citationCount: 0
      date: '2023-11-01T00:00:00Z'
      journal: Horticulture Research
      title: 'OmicsSuite: a customized and pipelined suite for analysis and visualization
        of multi-omics big data'
    note: 'Ben-ben Miao, Wei Dong, Yi-xin Gu, Zhao-fang Han, Xuan Luo, Cai-huan Ke,
      Wei-wei You, OmicsSuite: a customized and pipelined suite for analysis and visualization
      of multi-omics big data, Horticulture Research, 2023;, uhad195, https://doi.org/10.1093/hr/uhad195.'
    pmcid: null
    pmid: null
    type:
    - Method
    version: 1.4.0
  relation: []
  toolType:
  - Desktop application
  - Suite
  - Bioinformatics portal
  - Plug-in
  - Web application
  - Workbench
  - Workflow
  topic:
  - term: Biology
    uri: http://edamontology.org/topic_3070
  - term: Omics
    uri: http://edamontology.org/topic_3391
  - term: Mathematics
    uri: http://edamontology.org/topic_3315
  validated: 0
  version:
  - 1.4.0
- accessibility: Open access
  additionDate: '2023-03-05T10:26:21.069202Z'
  biotoolsCURIE: biotools:bioscitools
  biotoolsID: bioscitools
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: OmicsSuite (https://omicssuite.github.io, https://github.com/OmicsSuite/),
    original name BioSciTools, a desktop program developed based on Java 11, aims
    to make new exploration and contribution to bioinformatics, and realize data analysis
    and visualization in the fields of sequence analysis, multi-omics (transcriptomics,
    genomics, protein omics, metabolomics, single cell), microbiology, clinical, etc.
  documentation: []
  download:
  - note: GitHub download page
    type: Downloads page
    url: https://omicssuite.github.io
    version: 1.4.0
  - note: SourceForge download
    type: Binaries
    url: https://sourceforge.net/projects/omicssuite-github-io/files/latest/download
    version: 1.4.0
  - note: ALiYun Drive
    type: Binaries
    url: https://www.aliyundrive.com/s/Defuhf7FVGw
    version: 1.4.0
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Alignment
        uri: http://edamontology.org/data_1916
      format: []
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format: []
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format: []
    - data:
        term: Matrix
        uri: http://edamontology.org/data_2082
      format: []
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format: []
    - data:
        term: Text data
        uri: http://edamontology.org/data_2526
      format: []
    note: null
    operation:
    - term: Analysis
      uri: http://edamontology.org/operation_2945
    - term: Alignment
      uri: http://edamontology.org/operation_2928
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: Binary format
        uri: http://edamontology.org/format_2333
      - term: RDF format
        uri: http://edamontology.org/format_2376
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://github.com/OmicsSuite/
  homepage_status: 0
  language:
  - Java
  - Python
  - R
  - JavaScript
  lastUpdate: '2024-02-25T14:20:44.230314Z'
  license: GPL-3.0
  link:
  - note: GitHub Organization
    type:
    - Repository
    url: https://github.com/OmicsSuite/
  - note: OmicsSuite Website
    type:
    - Helpdesk
    url: https://omicssuite.github.io
  - note: OmicsSuite Courses
    type:
    - Social media
    url: https://space.bilibili.com/34105515
  - note: OmicsSuite Paper
    type:
    - Helpdesk
    url: https://doi.org/10.1093/hr/uhad195
  maturity: Emerging
  name: OmicsSuite
  operatingSystem:
  - Windows
  otherID: []
  owner: benben.miao
  publication:
  - doi: 10.1093/hr/uhad195
    metadata:
      abstract: 'With the advancements in high-throughput sequencing technologies
        such as Illumina, PacBio, and 10X Genomics platforms, and gas/liquid chromatography-mass
        spectrometry, large volumes of biological data in multiple formats can now
        be obtained through multi-omics analysis. Bioinformatics is constantly evolving
        and seeking breakthroughs to solve multi-omics problems; however, it is challenging
        for most experimental biologists to analyse data using command-line interfaces,
        coding, and scripting. Based on experience with multi-omics, we have developed
        OmicsSuite, a desktop suite that comprehensively integrates statistics and
        multi-omics analysis and visualization. The suite has 175 sub-applications
        in 12 categories, including Sequence, Statistics, Algorithm, Genomics, Transcriptomics,
        Enrichment, Proteomics, Metabolomics, Clinical, Microorganism, Single Cell,
        and Table Operation. We created the user interface with Sequence View, Table
        View, and intelligent components based on JavaFX and the popular Shiny framework.
        The multi-omics analysis functions were developed based on BioJava and 300+
        packages provided by the R CRAN and Bioconductor communities, and it encompasses
        over 3000 adjustable parameter interfaces. OmicsSuite can directly read multi-omics
        raw data in FastA, FastQ, Mutation Annotation Format, mzML, Matrix, and HDF5
        formats, and the programs emphasize data transfer directions and pipeline
        analysis functions. OmicsSuite can produce pre-publication images and tables,
        allowing users to focus on biological aspects. OmicsSuite offers multi-omics
        step-by-step workflows that can be easily applied to horticultural plant breeding
        and molecular mechanism studies in plants. It enables researchers to freely
        explore the molecular information contained in multi-omics big data (Source:
        https://github.com/OmicsSuite/, Website: https://omicssuite.github.io, v1.3.9).'
      authors:
      - name: Miao B.-B.
      - name: Dong W.
      - name: Gu Y.-X.
      - name: Han Z.-F.
      - name: Luo X.
      - name: Ke C.-H.
      - name: You W.-W.
      citationCount: 0
      date: '2023-11-01T00:00:00Z'
      journal: Horticulture Research
      title: 'OmicsSuite: a customized and pipelined suite for analysis and visualization
        of multi-omics big data'
    note: 'Ben-ben Miao, Wei Dong, Yi-xin Gu, Zhao-fang Han, Xuan Luo, Cai-huan Ke,
      Wei-wei You, OmicsSuite: a customized and pipelined suite for analysis and visualization
      of multi-omics big data, Horticulture Research, 2023;, uhad195, https://doi.org/10.1093/hr/uhad195.'
    pmcid: null
    pmid: null
    type:
    - Method
    version: 1.4.0
  relation: []
  toolType:
  - Desktop application
  - Suite
  - Bioinformatics portal
  - Plug-in
  - Web application
  - Workbench
  - Workflow
  topic:
  - term: Biology
    uri: http://edamontology.org/topic_3070
  - term: Omics
    uri: http://edamontology.org/topic_3391
  - term: Mathematics
    uri: http://edamontology.org/topic_3315
  validated: 0
  version:
  - 1.4.0
- accessibility: null
  additionDate: '2024-02-23T09:13:36.249995Z'
  biotoolsCURIE: biotools:operon_finder
  biotoolsID: operon_finder
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: spkanaujia@iitg.ac.in
    fundrefid: null
    gridid: null
    name: Shankar Prasad Kanaujia
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: A deep learning-based web server for accurate prediction of prokaryotic
    operons.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Operon prediction
      uri: http://edamontology.org/operation_0435
    - term: Operon drawing
      uri: http://edamontology.org/operation_0579
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output: []
  homepage: https://www.iitg.ac.in/spkanaujia/operonfinder.html
  homepage_status: 0
  language:
  - Python
  - Java
  lastUpdate: '2024-02-23T09:13:36.252622Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/SPKlab/Operon-Finder
  maturity: null
  name: Operon Finder
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1016/J.JMB.2022.167921
    metadata:
      abstract: Operons are groups of consecutive genes that transcribe together under
        the regulation of a common promoter. They influence protein regulation and
        various physiological pathways, making their accurate detection desirable.
        The detection of operons through experimental means is a laborious and financially
        intensive process. Therefore, human experts predict potential operons utilizing
        their prior knowledge of the genetic organization and functional correlation
        of the genes. However, with the rise in the number of completely sequenced
        genomes, the development of automated algorithms, tools, and web servers is
        highly preferred over manual detection for operon prediction. Currently available
        state-of-the-art algorithms use a deep learning-based model to predict if
        the adjacent genes belong to the same operons in the given genome. However,
        these require an understanding of programming knowledge and computational
        skills, making them not-very user friendly. In this study, we developed a
        user-friendly web service, Operon Finder, for on-the-fly prediction of operons
        using the deep learning method. The interface provides a facility for genome
        search, operon live-filtering, viewing operonic DNA sequences, downloading
        predicted results, and links for data retrieval from the NCBI (National Center
        for Biotechnology Information) database. The web server is available at https://www.iitg.ac.in/spkanaujia/operonfinder.html.
        The experimental methods and the implementation details are publicly available
        at https://github.com/SPKlab/Operon-Finder.
      authors:
      - name: Tomar T.S.
      - name: Dasgupta P.
      - name: Kanaujia S.P.
      citationCount: 2
      date: '2023-07-15T00:00:00Z'
      journal: Journal of Molecular Biology
      title: 'Operon Finder: A Deep Learning-based Web Server for Accurate Prediction
        of Prokaryotic Operons'
    note: null
    pmcid: null
    pmid: '37356898'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Gene structure
    uri: http://edamontology.org/topic_0114
  - term: Physiology
    uri: http://edamontology.org/topic_3300
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Biotechnology
    uri: http://edamontology.org/topic_3297
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  validated: 0
  version: []
- accessibility: null
  additionDate: '2024-02-22T12:20:05.220524Z'
  biotoolsCURIE: biotools:lapis
  biotoolsID: lapis
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: chaoran.chen@bsse.ethz.ch
    fundrefid: null
    gridid: null
    name: Chaoran Chen
    note: null
    orcidid: https://orcid.org/0000-0002-8763-2937
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: tanja.stadler@bsse.ethz.ch
    fundrefid: null
    gridid: null
    name: Tanja Stadler
    note: null
    orcidid: https://orcid.org/0000-0001-6431-535X
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: LAPIS is a fast web API for massive open virus sequencing data.
  documentation:
  - note: null
    type:
    - User manual
    url: https://lapis-docs.readthedocs.io/
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Aggregation
      uri: http://edamontology.org/operation_3436
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output: []
  homepage: https://github.com/GenSpectrum/LAPIS
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-02-22T12:20:05.223196Z'
  license: AGPL-3.0
  link: []
  maturity: null
  name: LAPIS
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1186/S12859-023-05364-3
    metadata:
      abstract: 'Background: Recent epidemic outbreaks such as the SARS-CoV-2 pandemic
        and the mpox outbreak in 2022 have demonstrated the value of genomic sequencing
        data for tracking the origin and spread of pathogens. Laboratories around
        the globe generated new sequences at unprecedented speed and volume and bioinformaticians
        developed new tools and dashboards to analyze this wealth of data. However,
        a major challenge that remains is the lack of simple and efficient approaches
        for accessing and processing sequencing data. Results: The Lightweight API
        for Sequences (LAPIS) facilitates rapid retrieval and analysis of genomic
        sequencing data through a REST API. It supports complex mutation- and metadata-based
        queries and can perform aggregation operations on massive datasets. LAPIS
        is optimized for typical questions relevant to genomic epidemiology. Using
        a newly-developed in-memory database engine, it has a high speed and throughput:
        between 25 January and 4 February 2023, the SARS-CoV-2 instance of LAPIS,
        which contains 14.5 million sequences, processed over 20 million requests
        with a mean response time of 411 ms and a median response time of 1 ms. LAPIS
        is the core engine behind our dashboards on genspectrum.org and we currently
        maintain public LAPIS instances for SARS-CoV-2 and mpox. Conclusions: Powered
        by an optimized database engine and available through a web API, LAPIS enhances
        the accessibility of genomic sequencing data. It is designed to serve as a
        common backend for dashboards and analyses with the potential to be integrated
        into common database platforms such as GenBank.'
      authors:
      - name: Chen C.
      - name: Taepper A.
      - name: Engelniederhammer F.
      - name: Kellerer J.
      - name: Roemer C.
      - name: Stadler T.
      citationCount: 0
      date: '2023-12-01T00:00:00Z'
      journal: BMC Bioinformatics
      title: LAPIS is a fast web API for massive open virus sequencing data
    note: null
    pmcid: PMC10240112
    pmid: '37277732'
    type: []
    version: null
  relation: []
  toolType:
  - Web API
  topic:
  - term: Public health and epidemiology
    uri: http://edamontology.org/topic_3305
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  validated: 0
  version: []
next: ?page=2
previous: null
