count: 3915 list: - accessibility: Open access additionDate: '2024-03-27T21:31:18.764496Z' biotoolsCURIE: biotools:aghmatrix biotoolsID: aghmatrix collectionID: [] community: null confidence_flag: tool cost: Free of charge credit: - email: lferrao@ufl.edu fundrefid: null gridid: null name: Luís Felipe V Ferrão note: null orcidid: https://orcid.org/0000-0002-9655-4838 rorid: null typeEntity: Person typeRole: [] url: null - email: null fundrefid: null gridid: null name: Rodrigo R Amadeu note: null orcidid: null rorid: null typeEntity: Person typeRole: [] url: null description: AGHmatrix software is an R-package to build relationship matrices using pedigree (A matrix) and/or molecular markers (G matrix) with the possibility to build a combined matrix of Pedigree corrected by Molecular (H matrix). The package works with diploid and autopolyploid data. documentation: [] download: [] editPermission: authors: [] type: public elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: null operation: - term: Genotyping uri: http://edamontology.org/operation_3196 - term: Essential dynamics uri: http://edamontology.org/operation_3891 output: [] homepage: https://cran.r-project.org/web/packages/AGHmatrix/index.html homepage_status: 0 language: - R lastUpdate: '2024-03-27T21:31:18.767038Z' license: GPL-3.0 link: - note: null type: - Repository url: https://github.com/rramadeu/AGHmatrix maturity: null name: AGHmatrix operatingSystem: [] otherID: [] owner: Pub2Tools publication: - doi: 10.1093/BIOINFORMATICS/BTAD445 metadata: abstract: 'Motivation: The resemble between relatives computed from pedigree and genomic data is an important resource for geneticists and ecologists, who are interested in understanding how genes influence phenotypic variation, fitness adaptation, and population dynamics. Results: The AGHmatrix software is an R package focused on the construction of pedigree (A matrix) and/or molecular markers (G matrix), with the possibility of building a combined matrix of pedigree corrected by molecular markers (H matrix). Designed to estimate the relationships for any ploidy level, the software also includes auxiliary functions related to filtering molecular markers, and checks pedigree errors in large data sets. After computing the relationship matrices, results from the AGHmatrix can be used in different contexts, including on prediction of (genomic) estimated breeding values and genome-wide association studies.' authors: - name: Amadeu R.R. - name: Garcia A.A.F. - name: Munoz P.R. - name: Ferrao L.F.V. citationCount: 2 date: '2023-07-01T00:00:00Z' journal: Bioinformatics title: 'AGHmatrix: Genetic relationship matrices in R' note: null pmcid: PMC10371492 pmid: '37471595' type: [] version: null relation: [] toolType: - Library topic: - term: Epistasis uri: http://edamontology.org/topic_3974 - term: Genotype and phenotype uri: http://edamontology.org/topic_0625 - term: DNA polymorphism uri: http://edamontology.org/topic_2885 - term: GWAS study uri: http://edamontology.org/topic_3517 validated: 0 version: [] - accessibility: Open access additionDate: '2024-03-27T19:47:51.594633Z' biotoolsCURIE: biotools:pygellermann biotoolsID: pygellermann collectionID: [] community: null confidence_flag: tool cost: Free of charge credit: - email: Yannick.Jadoul@mpi.nl fundrefid: null gridid: null name: Yannick Jadoul note: null orcidid: null rorid: null typeEntity: Person typeRole: [] url: null - email: andrea.ravignani@uniroma1.it fundrefid: null gridid: null name: Andrea Ravignani note: null orcidid: null rorid: null typeEntity: Person typeRole: [] url: null description: Python tool to generate pseudorandom series for human and non-human animal behavioural experiments. It includes both a graphical user interface (GUI) as well as a simple Python API. documentation: [] download: [] editPermission: authors: [] type: public elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: null operation: - term: Sequence generation uri: http://edamontology.org/operation_0230 output: [] homepage: https://github.com/YannickJadoul/PyGellermann homepage_status: 0 language: - Python lastUpdate: '2024-03-27T19:47:51.597501Z' license: GPL-3.0 link: [] maturity: null name: PyGellermann operatingSystem: - Mac - Linux - Windows otherID: [] owner: Pub2Tools publication: - doi: 10.1186/S13104-023-06396-X metadata: abstract: 'Objective: Researchers in animal cognition, psychophysics, and experimental psychology need to randomise the presentation order of trials in experimental sessions. In many paradigms, for each trial, one of two responses can be correct, and the trials need to be ordered such that the participant’s responses are a fair assessment of their performance. Specifically, in some cases, especially for low numbers of trials, randomised trial orders need to be excluded if they contain simple patterns which a participant could accidentally match and so succeed at the task without learning. Results: We present and distribute a simple Python software package and tool to produce pseudorandom sequences following the Gellermann series. This series has been proposed to pre-empt simple heuristics and avoid inflated performance rates via false positive responses. Our tool allows users to choose the sequence length and outputs a.csv file with newly and randomly generated sequences. This allows behavioural researchers to produce, in a few seconds, a pseudorandom sequence for their specific experiment. PyGellermann is available at https://github.com/YannickJadoul/PyGellermann .' authors: - name: Jadoul Y. - name: Duengen D. - name: Ravignani A. citationCount: 0 date: '2023-12-01T00:00:00Z' journal: BMC Research Notes title: 'PyGellermann: a Python tool to generate pseudorandom series for human and non-human animal behavioural experiments' note: null pmcid: PMC10320995 pmid: '37403146' type: [] version: null relation: [] toolType: - Library - Desktop application - Command-line tool topic: - term: Zoology uri: http://edamontology.org/topic_3500 - term: Animal study uri: http://edamontology.org/topic_3679 - term: Laboratory techniques uri: http://edamontology.org/topic_3361 validated: 0 version: [] - accessibility: Open access additionDate: '2024-03-27T14:45:55.984492Z' biotoolsCURIE: biotools:megaltr biotoolsID: megaltr collectionID: [] community: null confidence_flag: tool cost: Free of charge credit: - email: morad.mokhtar@ageri.sci.eg fundrefid: null gridid: null name: Morad M. Mokhtar note: null orcidid: null rorid: null typeEntity: Person typeRole: [] url: null - email: achraf.elallali@um6p.ma fundrefid: null gridid: null name: Achraf El Allali note: null orcidid: null rorid: null typeEntity: Person typeRole: [] url: null description: Web server and standalone pipeline for detecting and annotating LTR-retrotransposons in plant genomes. documentation: [] download: [] editPermission: authors: [] type: private elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: null operation: - term: Scaffolding uri: http://edamontology.org/operation_3216 - term: Genome assembly uri: http://edamontology.org/operation_0525 output: [] homepage: https://bioinformatics.um6p.ma/MegaLTR homepage_status: 0 language: - Perl - Shell lastUpdate: '2024-03-27T14:45:55.987821Z' license: GPL-3.0 link: - note: null type: - Repository url: https://github.com/MoradMMokhtar/MegaLTR maturity: null name: MegaLTR operatingSystem: - Mac - Linux - Windows otherID: [] owner: Pub2Tools publication: - doi: 10.3389/FPLS.2023.1237426 metadata: abstract: LTR-retrotransposons (LTR-RTs) are a class of RNA-replicating transposon elements (TEs) that can alter genome structure and function by moving positions, repositioning genes, shifting exons, and causing chromosomal rearrangements. LTR-RTs are widespread in many plant genomes and constitute a significant portion of the genome. Their movement and activity in eukaryotic genomes can provide insight into genome evolution and gene function, especially when LTR-RTs are located near or within genes. Building the redundant and non-redundant LTR-RTs libraries and their annotations for species lacking this resource requires extensive bioinformatics pipelines and expensive computing power to analyze large amounts of genomic data. This increases the need for online services that provide computational resources with minimal overhead and maximum efficiency. Here, we present MegaLTR as a web server and standalone pipeline that detects intact LTR-RTs at the whole-genome level and integrates multiple tools for structure-based, homologybased, and de novo identification, classification, annotation, insertion time determination, and LTR-RT gene chimera analysis. MegaLTR also provides statistical analysis and visualization with multiple tools and can be used to accelerate plant species discovery and assist breeding programs in their efforts to improve genomic resources. We hope that the development of online services such as MegaLTR, which can analyze large amounts of genomic data, will become increasingly important for the automated detection and annotation of LTR-RT elements. authors: - name: Mokhtar M.M. - name: El Allali A. citationCount: 0 date: '2023-01-01T00:00:00Z' journal: Frontiers in Plant Science title: 'MegaLTR: a web server and standalone pipeline for detecting and annotating LTR-retrotransposons in plant genomes' note: null pmcid: PMC10552921 pmid: '37810401' type: [] version: null relation: [] toolType: - Web application topic: - term: Plant biology uri: http://edamontology.org/topic_0780 - term: Mobile genetic elements uri: http://edamontology.org/topic_0798 - term: Gene transcripts uri: http://edamontology.org/topic_3512 - term: Model organisms uri: http://edamontology.org/topic_0621 - term: Workflows uri: http://edamontology.org/topic_0769 validated: 0 version: [] - accessibility: Open access additionDate: '2024-03-27T12:31:52.492448Z' biotoolsCURIE: biotools:pangolin_cov-lineages biotoolsID: pangolin_cov-lineages collectionID: - COVID-19 community: null confidence_flag: null cost: Free of charge credit: - email: null fundrefid: null gridid: null name: Áine O'Toole note: null orcidid: null rorid: null typeEntity: Person typeRole: - Developer url: null description: Phylogenetic Assignment of Named Global Outbreak LINeages - software package for assigning SARS-CoV-2 genome sequences to global lineages documentation: [] download: [] editPermission: authors: [] type: public elixirCommunity: [] elixirNode: [] elixirPlatform: - Tools elixir_badge: 0 function: - cmd: null input: - data: term: DNA sequence uri: http://edamontology.org/data_3494 format: - term: FASTA uri: http://edamontology.org/format_1929 note: null operation: - term: Tree-based sequence alignment uri: http://edamontology.org/operation_0499 - term: Variant classification uri: http://edamontology.org/operation_3225 output: - data: term: Taxonomic classification uri: http://edamontology.org/data_1872 format: - term: DSV uri: http://edamontology.org/format_3751 homepage: https://cov-lineages.org/resources/pangolin.html homepage_status: 0 language: [] lastUpdate: '2024-03-27T12:45:41.622372Z' license: GPL-3.0 link: - note: null type: - Repository url: https://github.com/cov-lineages/pangolin maturity: Mature name: pangolin operatingSystem: - Linux - Mac otherID: [] owner: wm75 publication: - doi: 10.1093/ve/veab064 metadata: abstract: The response of the global virus genomics community to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been unprecedented, with significant advances made towards the ‘real-time’ generation and sharing of SARS-CoV-2 genomic data. The rapid growth in virus genome data production has necessitated the development of new analytical methods that can deal with orders of magnitude of more genomes than previously available. Here, we present and describe Phylogenetic Assignment of Named Global Outbreak Lineages (pangolin), a computational tool that has been developed to assign the most likely lineage to a given SARSCoV-2 genome sequence according to the Pango dynamic lineage nomenclature scheme. To date, nearly two million virus genomes have been submitted to the web-application implementation of pangolin, which has facilitated the SARS-CoV-2 genomic epidemiology and provided researchers with access to actionable information about the pandemic’s transmission lineages. authors: - name: O'Toole A. - name: Scher E. - name: Underwood A. - name: Jackson B. - name: Hill V. - name: McCrone J.T. - name: Colquhoun R. - name: Ruis C. - name: Abu-Dahab K. - name: Taylor B. - name: Yeats C. - name: du Plessis L. - name: Maloney D. - name: Medd N. - name: Attwood S.W. - name: Aanensen D.M. - name: Holmes E.C. - name: Pybus O.G. - name: Rambaut A. citationCount: 528 date: '2021-01-01T00:00:00Z' journal: Virus Evolution title: Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool note: null pmcid: null pmid: null type: [] version: null relation: [] toolType: - Command-line tool topic: - term: Virology uri: http://edamontology.org/topic_0781 validated: 0 version: - v4.0 - v4.3.1 - accessibility: Open access additionDate: '2024-03-23T21:36:23.370696Z' biotoolsCURIE: biotools:singlem biotoolsID: singlem collectionID: [] community: null confidence_flag: null cost: Free of charge credit: [] description: Novelty-inclusive microbial community profiling of shotgun metagenomes documentation: - note: null type: - General - Command-line options - Installation instructions url: https://wwood.github.io/singlem/ download: [] editPermission: authors: [] type: private elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: - data: term: DNA sequence uri: http://edamontology.org/data_3494 format: - term: FASTQ uri: http://edamontology.org/format_1930 - term: FASTA uri: http://edamontology.org/format_1929 note: null operation: - term: Taxonomic classification uri: http://edamontology.org/operation_3460 output: - data: term: Taxonomy uri: http://edamontology.org/data_3028 format: - term: CSV uri: http://edamontology.org/format_3752 homepage: https://wwood.github.io/singlem/ homepage_status: 0 language: - Python lastUpdate: '2024-03-23T21:46:51.247440Z' license: GPL-3.0 link: [] maturity: null name: SingleM operatingSystem: - Linux otherID: [] owner: benjwoodcroft publication: - doi: 10.1101/2024.01.30.578060 metadata: null note: null pmcid: null pmid: null type: [] version: null relation: [] toolType: - Command-line tool topic: - term: Metagenomics uri: http://edamontology.org/topic_3174 validated: 0 version: [] - accessibility: Open access additionDate: '2021-09-22T06:53:17.910163Z' biotoolsCURIE: biotools:kingfisher biotoolsID: kingfisher collectionID: [] community: null confidence_flag: null cost: Free of charge credit: [] description: Easier download/extract of FASTA/Q read data and metadata from the ENA, NCBI, AWS or GCP. documentation: - note: null type: - Command-line options - General - Installation instructions url: https://wwood.github.io/kingfisher-download/ download: [] editPermission: authors: [] type: private elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: kingfisher get -r ERR1739691 -m ena-ascp aws-http prefetch input: - data: term: Accession uri: http://edamontology.org/data_2091 format: [] note: null operation: - term: Data retrieval uri: http://edamontology.org/operation_2422 - term: Sequence database search (by property) uri: http://edamontology.org/operation_0349 output: - data: term: Nucleic acid sequence uri: http://edamontology.org/data_2977 format: - term: SRA format uri: http://edamontology.org/format_3698 - term: FASTQ uri: http://edamontology.org/format_1930 - term: FASTA uri: http://edamontology.org/format_1929 homepage: https://github.com/wwood/kingfisher-download homepage_status: 0 language: - Python lastUpdate: '2024-03-23T21:28:46.812337Z' license: GPL-3.0 link: [] maturity: Emerging name: Kingfisher operatingSystem: - Linux - Mac otherID: [] owner: benjwoodcroft publication: [] relation: [] toolType: [] topic: - term: Nucleic acids uri: http://edamontology.org/topic_0077 validated: 0 version: [] - accessibility: Open access additionDate: '2019-05-27T16:59:15Z' biotoolsCURIE: biotools:SLiM_software biotoolsID: SLiM_software collectionID: [] community: null confidence_flag: null cost: Free of charge credit: - email: messer@cornell.edu fundrefid: null gridid: null name: Philipp Messer note: null orcidid: https://orcid.org/0000-0001-8453-9377 rorid: null typeEntity: Person typeRole: - Primary contact url: https://messerlab.org - email: bhaller@benhaller.com fundrefid: null gridid: null name: Benjamin C. Haller note: null orcidid: https://orcid.org/0000-0003-1874-8327 rorid: null typeEntity: Person typeRole: - Primary contact url: http://benhaller.com description: Evolutionary simulation framework that combines a powerful engine for population genetic simulations with the capability of modeling arbitrarily complex evolutionary scenarios. Includes a graphical modeling environment. documentation: - note: The manual for SLiM itself type: - User manual url: http://benhaller.com/slim/SLiM_Manual.pdf - note: The manual for Eidos, the scripting language used by SLiM type: - User manual url: http://benhaller.com/slim/Eidos_Manual.pdf - note: Quick reference sheets for SLiM and Eidos type: - Quick start guide url: http://benhaller.com/slim/SLiMEidosRefSheets.zip download: - note: A source archive for the command-line `slim` tool only. Complete source code is on GitHub, but most platforms have an installer anyway; see the manual, chapter 2, for installation instructions. type: Source code url: http://benhaller.com/slim/SLiM.zip version: null - note: The GitHub page for the current release version, to obtain full source code. type: Downloads page url: https://github.com/MesserLab/SLiM/releases/latest version: null editPermission: authors: [] type: private elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: Run individual-based eco-evolutionary simulations with explicit genetics operation: - term: DNA substitution modelling uri: http://edamontology.org/operation_0550 - term: Sequence generation uri: http://edamontology.org/operation_0230 - term: Ecological modelling uri: http://edamontology.org/operation_3946 output: [] homepage: https://messerlab.org/slim/ homepage_status: 0 language: - C++ lastUpdate: '2024-03-22T16:10:48.260397Z' license: GPL-3.0 link: - note: SLiM home page in the Messer Lab website type: - Software catalogue url: https://messerlab.org/slim/ - note: GitHub repository for SLiM type: - Repository url: https://github.com/MesserLab/SLiM - note: Discussion forum for SLiM questions type: - Discussion forum url: https://groups.google.com/g/slim-discuss - note: Announcements mailing list type: - Mailing list url: https://groups.google.com/g/slim-announce maturity: Mature name: SLiM operatingSystem: - Linux - Mac - Windows otherID: [] owner: bchaller publication: - doi: 10.1093/molbev/msy228 metadata: abstract: With the desire to model population genetic processes under increasingly realistic scenarios, forward genetic simulations have become a critical part of the toolbox of modern evolutionary biology. The SLiM forward genetic simulation framework is one of the most powerful and widely used tools in this area. However, its foundation in the Wright-Fisher model has been found to pose an obstacle to implementing many types of models; it is difficult to adapt the Wright-Fisher model, with its many assumptions, to modeling ecologically realistic scenarios such as explicit space, overlapping generations, individual variation in reproduction, density-dependent population regulation, individual variation in dispersal or migration, local extinction and recolonization, mating between subpopulations, age structure, fitness-based survival and hard selection, emergent sex ratios, and so forth. In response to this need, we here introduce SLiM 3, which contains two key advancements aimed at abolishing these limitations. First, the new non-Wright-Fisher or "nonWF" model type provides a much more flexible foundation that allows the easy implementation of all of the above scenarios and many more. Second, SLiM 3 adds support for continuous space, including spatial interactions and spatial maps of environmental variables. We provide a conceptual overview of these new features, and present several example models to illustrate their use. authors: - name: Haller B.C. - name: Messer P.W. citationCount: 410 date: '2019-03-01T00:00:00Z' journal: Molecular Biology and Evolution title: 'SLiM 3: Forward Genetic Simulations Beyond the Wright-Fisher Model' note: 'B.C. Haller, P.W. Messer. (2019). SLiM 3: Forward genetic simulations beyond the Wright–Fisher Model. Molecular Biology and Evolution 36(3), 632–637.' pmcid: null pmid: null type: - Other version: null - doi: 10.1093/molbev/msy237 metadata: abstract: The SLiM forward genetic simulation framework has proved to be a powerful and flexible tool for population genetic modeling. However, as a complex piece of software with many features that allow simulating a diverse assortment of evolutionary models, its initial learning curve can be difficult. Here we provide a step-by-step demonstration of how to build a simple evolutionary model in SLiM 3, to help new users get started. We will begin with a panmictic neutral model, and build up to a model of the evolution of a polygenic quantitative trait under selection for an environmental phenotypic optimum. authors: - name: Haller B.C. - name: Messer P.W. citationCount: 8 date: '2019-05-01T00:00:00Z' journal: Molecular Biology and Evolution title: Evolutionary Modeling in SLiM 3 for Beginners note: B.C. Haller, P.W. Messer. (2019). Evolutionary modeling in SLiM 3 for beginners. Molecular Biology and Evolution 36(5), 1101–1109. pmcid: null pmid: null type: - Usage version: null - doi: 10.1111/1755-0998.12968 metadata: abstract: 'There is an increasing demand for evolutionary models to incorporate relatively realistic dynamics, ranging from selection at many genomic sites to complex demography, population structure, and ecological interactions. Such models can generally be implemented as individual-based forward simulations, but the large computational overhead of these models often makes simulation of whole chromosome sequences in large populations infeasible. This situation presents an important obstacle to the field that requires conceptual advances to overcome. The recently developed tree-sequence recording method (Kelleher, Thornton, Ashander, & Ralph, 2018), which stores the genealogical history of all genomes in the simulated population, could provide such an advance. This method has several benefits: (1) it allows neutral mutations to be omitted entirely from forward-time simulations and added later, thereby dramatically improving computational efficiency; (2) it allows neutral burn-in to be constructed extremely efficiently after the fact, using “recapitation”; (3) it allows direct examination and analysis of the genealogical trees along the genome; and (4) it provides a compact representation of a population''s genealogy that can be analysed in Python using the msprime package. We have implemented the tree-sequence recording method in SLiM 3 (a free, open-source evolutionary simulation software package) and extended it to allow the recording of non-neutral mutations, greatly broadening the utility of this method. To demonstrate the versatility and performance of this approach, we showcase several practical applications that would have been beyond the reach of previously existing methods, opening up new horizons for the modelling and exploration of evolutionary processes.' authors: - name: Haller B.C. - name: Galloway J. - name: Kelleher J. - name: Messer P.W. - name: Ralph P.L. citationCount: 79 date: '2019-03-01T00:00:00Z' journal: Molecular Ecology Resources title: Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes note: B.C. Haller, J. Galloway, J. Kelleher, P.W. Messer, P.L. Ralph. (2019). Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes. Molecular Ecology Resources 19(2), 552–566. pmcid: null pmid: null type: - Method version: null - doi: 10.1086/723601 metadata: abstract: The SLiM software framework for genetically explicit forward simulation has been widely used in population genetics. However, it has been largely restricted to modeling only a single species, which has limited its broader utility in evolutionary biology. Indeed, to our knowledge no general-purpose, flexible modeling framework exists that provides support for simulating multiple species while also providing other key features, such as explicit genetics and continuous space. The lack of such software has limited our ability to model higher biological levels such as communities, eco-systems, coevolutionary and eco-evolutionary processes, and bio-diversity, which is crucial for many purposes, from extending our basic understanding of evolutionary ecology to informing conservation and management decisions. We here announce the release of SLiM 4, which fills this important gap by adding support for multiple species, including ecological interactions between species such as predation, parasitism, and mutualism, and illustrate its new features with examples. authors: - name: Haller B.C. - name: Messer P.W. citationCount: 20 date: '2023-05-01T00:00:00Z' journal: American Naturalist title: 'SLiM 4: Multispecies Eco-Evolutionary Modeling' note: 'B.C. Haller, P.W. Messer. (2023). SLiM 4: Multispecies eco-evolutionary modeling. The American Naturalist 201(5), E127–E139.' pmcid: null pmid: null type: - Primary version: null relation: [] toolType: - Command-line tool - Desktop application topic: - term: Ecology uri: http://edamontology.org/topic_0610 - term: Molecular interactions, pathways and networks uri: http://edamontology.org/topic_0602 - term: Genetic variation uri: http://edamontology.org/topic_0199 - term: Evolutionary biology uri: http://edamontology.org/topic_3299 validated: 0 version: - '4.2' - accessibility: Open access additionDate: '2024-03-21T13:52:24.051270Z' biotoolsCURIE: biotools:opus-dsd biotoolsID: opus-dsd collectionID: [] community: null confidence_flag: tool cost: Free of charge credit: - email: jpma@fudan.edu.cn fundrefid: null gridid: null name: Jianpeng Ma note: null orcidid: https://orcid.org/0009-0001-2124-6080 rorid: null typeEntity: Person typeRole: [] url: null - email: null fundrefid: null gridid: null name: Zhenwei Luo note: null orcidid: null rorid: null typeEntity: Person typeRole: [] url: null description: Deep structural disentanglement for cryo-EM single-particle analysis. documentation: [] download: [] editPermission: authors: [] type: public elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: null operation: - term: Single particle analysis uri: http://edamontology.org/operation_3457 - term: Essential dynamics uri: http://edamontology.org/operation_3891 - term: Clustering uri: http://edamontology.org/operation_3432 output: [] homepage: https://github.com/alncat/opusDSD homepage_status: 0 language: - Python lastUpdate: '2024-03-21T13:52:24.055039Z' license: GPL-3.0 link: [] maturity: null name: OPUS-DSD operatingSystem: - Mac - Linux - Windows otherID: [] owner: Pub2Tools publication: - doi: 10.1038/S41592-023-02031-6 metadata: abstract: Cryo-electron microscopy (cryo-EM) captures snapshots of dynamic macromolecules, collectively illustrating the involved structural landscapes. This provides an exciting opportunity to explore the structural variations of macromolecules under study. However, traditional cryo-EM single-particle analysis often yields static structures. Here we describe OPUS-DSD, an algorithm capable of efficiently reconstructing the structural landscape embedded in cryo-EM data. OPUS-DSD uses a three-dimensional convolutional encoder–decoder architecture trained with cryo-EM images, thereby encoding structural variations into a smooth and easily analyzable low-dimension space. This space can be traversed to reconstruct continuous dynamics or clustered to identify distinct conformations. OPUS-DSD can offer meaningful insights into the structural variations of macromolecules, filling in the gaps left by traditional cryo-EM structural determination, and potentially improves the reconstruction resolution by reliably clustering similar particles within the dataset. These functionalities are especially relevant to the study of highly dynamic biological systems. OPUS-DSD is available at https://github.com/alncat/opusDSD . authors: - name: Luo Z. - name: Ni F. - name: Wang Q. - name: Ma J. citationCount: 1 date: '2023-11-01T00:00:00Z' journal: Nature Methods title: 'OPUS-DSD: deep structural disentanglement for cryo-EM single-particle analysis' note: null pmcid: PMC10630141 pmid: '37813988' type: [] version: null relation: [] toolType: - Command-line tool topic: - term: Imaging uri: http://edamontology.org/topic_3382 - term: Biophysics uri: http://edamontology.org/topic_3306 - term: Structural variation uri: http://edamontology.org/topic_3175 - term: Molecular modelling uri: http://edamontology.org/topic_2275 - term: Mathematics uri: http://edamontology.org/topic_3315 validated: 0 version: [] - accessibility: null additionDate: '2024-03-20T14:31:33.597559Z' biotoolsCURIE: biotools:phfinder biotoolsID: phfinder collectionID: [] community: null confidence_flag: tool cost: Free of charge credit: - email: m.suarez.menendez@rug.nl fundrefid: null gridid: null name: Marcos Suárez Menéndez note: null orcidid: null rorid: null typeEntity: Person typeRole: [] url: null description: Assisted detection of point heteroplasmy in sanger sequencing chromatograms. documentation: [] download: [] editPermission: authors: [] type: private elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: null operation: - term: Chromatogram visualisation uri: http://edamontology.org/operation_3203 - term: Peak detection uri: http://edamontology.org/operation_3215 - term: Variant calling uri: http://edamontology.org/operation_3227 output: [] homepage: https://github.com/MSuarezMenendez/PHFinder homepage_status: 0 language: - Python - Shell lastUpdate: '2024-03-20T14:31:33.600446Z' license: GPL-3.0 link: [] maturity: null name: PHFinder operatingSystem: - Mac - Linux - Windows otherID: [] owner: Pub2Tools publication: - doi: 10.7717/PEERJ.16028 metadata: abstract: Heteroplasmy is the presence of two or more organellar genomes (mitochondrial or plastid DNA) in an organism, tissue, cell or organelle. Heteroplasmy can be detected by visual inspection of Sanger sequencing chromatograms, where it appears as multiple peaks of fluorescence at a single nucleotide position. Visual inspection of chromatograms is both consuming and highly subjective, as heteroplasmy is difficult to differentiate from background noise. Few software solutions are available to automate the detection of point heteroplasmies, and those that are available are typically proprietary, lack customization or are unsuitable for automated heteroplasmy assessment in large datasets. Here, we present PHFinder, a Python-based, open-source tool to assist in the detection of point heteroplasmies in large numbers of Sanger chromatograms. PHFinder automatically identifies point heteroplasmies directly from the chromatogram trace data. The program was tested with Sanger sequencing data from 100 humpback whales (Megaptera novaeangliae) tissue samples with known heteroplasmies. PHFinder detected most (90%) of the known heteroplasmies thereby greatly reducing the amount of visual inspection required. PHFinder is flexible and enables explicit specification of key parameters to infer double peaks (i.e., heteroplasmies). authors: - name: Menendez M.S. - name: Rivera-Leon V.E. - name: Robbins J. - name: Berube M. - name: Palsboll P.J. citationCount: 0 date: '2023-01-01T00:00:00Z' journal: PeerJ title: 'PHFinder: assisted detection of point heteroplasmy in Sanger sequencing chromatograms' note: null pmcid: PMC10516101 pmid: '37744223' type: [] version: null relation: [] toolType: - Command-line tool topic: - term: Cell biology uri: http://edamontology.org/topic_2229 - term: Sequencing uri: http://edamontology.org/topic_3168 - term: DNA polymorphism uri: http://edamontology.org/topic_2885 - term: Zoology uri: http://edamontology.org/topic_3500 validated: 0 version: [] - accessibility: Open access additionDate: '2017-03-03T15:36:30Z' biotoolsCURIE: biotools:schloro biotoolsID: schloro collectionID: - Bologna Biocomputing Group community: null confidence_flag: tool cost: Free of charge credit: - email: null fundrefid: null gridid: null name: ELIXIR-ITA-BOLOGNA note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Maintainer url: http://www.biocomp.unibo.it - email: castrense.savojardo2@unibo.it fundrefid: null gridid: null name: Castrense Savojardo note: null orcidid: https://orcid.org/0000-0002-7359-0633 rorid: null typeEntity: Person typeRole: - Developer - Primary contact - Maintainer url: null description: Prediction of protein sub-chloroplastinc localization. documentation: - note: null type: - General url: https://schloro.biocomp.unibo.it/sclpred/default/index - note: null type: - Command-line options url: https://github.com/BolognaBiocomp/schloro download: - note: null type: Source code url: https://github.com/BolognaBiocomp/schloro version: null - note: null type: Container file url: https://hub.docker.com/r/bolognabiocomp/schloro version: null editPermission: authors: - ELIXIR-ITA-BOLOGNA - savo type: group elixirCommunity: [] 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 note: null operation: - term: Protein subcellular localisation prediction uri: http://edamontology.org/operation_2489 output: - data: term: Sequence report uri: http://edamontology.org/data_2955 format: - term: HTML uri: http://edamontology.org/format_2331 homepage: https://busca.biocomp.unibo.it/schloro homepage_status: 0 language: [] lastUpdate: '2024-03-20T09:50:20.056264Z' license: GPL-3.0 link: [] maturity: Mature name: SChloro operatingSystem: - Linux - Windows - Mac otherID: [] owner: ELIXIR-ITA-BOLOGNA publication: - doi: 10.1093/bioinformatics/btw656 metadata: abstract: 'Motivation: Chloroplasts are organelles found in plants and involved in several important cell processes. Similarly to other compartments in the cell, chloroplasts have an internal structure comprising several sub-compartments, where different proteins are targeted to perform their functions. Given the relation between protein function and localization, the availability of effective computational tools to predict protein sub-organelle localizations is crucial for large-scale functional studies. Results: In this paper we present SChloro, a novel machine-learning approach to predict protein sub-chloroplastic localization, based on targeting signal detection and membrane protein information. The proposed approach performs multi-label predictions discriminating six chloroplastic sub-compartments that include inner membrane, outer membrane, stroma, thylakoid lumen, plastoglobule and thylakoid membrane. In comparative benchmarks, the proposed method outperforms current state-of-the-art methods in both single- and multi-compartment predictions, with an overall multi-label accuracy of 74%. The results demonstrate the relevance of the approach that is eligible as a good candidate for integration into more general large-scale annotation pipelines of protein subcellular localization.' authors: - name: Savojardo C. - name: Martelli P.L. - name: Fariselli P. - name: Casadio R. citationCount: 18 date: '2017-01-01T00:00:00Z' journal: Bioinformatics title: 'SChloro: Directing Viridiplantae proteins to six chloroplastic sub-compartments' note: null pmcid: PMC5408801 pmid: '28172591' type: - Primary version: null relation: [] toolType: - Web application - Command-line tool topic: - term: Protein targeting and localisation uri: http://edamontology.org/topic_0140 - term: Plant biology uri: http://edamontology.org/topic_0780 validated: 1 version: - '1' next: ?page=2 previous: null