count: 8421
list:
- accessibility: Open access
  additionDate: '2024-04-19T11:31:13.116284Z'
  biotoolsCURIE: biotools:lion_localizer
  biotoolsID: lion_localizer
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: roca@illinois.edu
    fundrefid: null
    gridid: null
    name: Alfred L Roca
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Wesley C Au
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Software tool for inferring the provenance of lions (Panthera leo)
    using mitochondrial DNA.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence trimming
      uri: http://edamontology.org/operation_3192
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    - term: Haplotype mapping
      uri: http://edamontology.org/operation_0487
    output: []
  homepage: https://lionlocalizer.org
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-19T11:31:13.118404Z'
  license: null
  link: []
  maturity: null
  name: Lion Localizer
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/JHERED/ESAD072
    metadata:
      abstract: The illegal poaching of lions for their body parts poses a severe
        threat to lion populations across Africa. Poaching accounts for 35% of all
        human-caused lion deaths, with 51% attributed to retaliatory killings following
        livestock predation. In nearly half of the retaliatory killings, lion body
        parts are removed, suggesting that high demand for lion body parts may fuel
        killings attributed to human-lion conflict. Trafficked items are often confiscated
        in transit or destination countries far from their country of origin. DNA
        from lion parts may in some cases be the only available means for examining
        their geographic origins. In this paper, we present the Lion Localizer, a
        full-stack software tool that houses a comprehensive database of lion mitochondrial
        DNA (mtDNA) sequences sourced from previously published studies. The database
        covers 146 localities from across the African continent and India, providing
        information on the potential provenance of seized lion body parts. Lion mtDNA
        sequences of 350 or 1,140 bp corresponding to the cytochrome b region can
        be generated from lion products and queried against the Lion Localizer database.
        Using the query sequence, the Lion Localizer generates a listing of exact
        or partial matches, which are displayed on an interactive map of Africa. This
        allows for the rapid identification of potential regions and localities where
        lions have been or are presently being targeted by poachers. By examining
        the potential provenance of lion samples, the Lion Localizer serves as a valuable
        resource in the fight against lion poaching. The software is available at
        https://lionlocalizer.org.
      authors:
      - name: Au W.C.
      - name: Dures S.G.
      - name: Ishida Y.
      - name: Green C.E.
      - name: Zhao K.
      - name: Ogden R.
      - name: Roca A.L.
      citationCount: 0
      date: '2024-03-01T00:00:00Z'
      journal: Journal of Heredity
      title: 'Lion Localizer: A software tool for inferring the provenance of lions
        (Panthera leo) using mitochondrial DNA'
    note: null
    pmcid: null
    pmid: '37952226'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: DNA
    uri: http://edamontology.org/topic_0654
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T11:28:09.722051Z'
  biotoolsCURIE: biotools:metgene
  biotoolsID: metgene
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: shsubramaniam@ucsd.edu
    fundrefid: null
    gridid: null
    name: Shankar Subramaniam
    note: null
    orcidid: https://orcid.org/0000-0002-8059-4659
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Sumana Srinivasan
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Gene-centric metabolomics information retrieval tool.
  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: Aggregation
      uri: http://edamontology.org/operation_3436
    - term: Filtering
      uri: http://edamontology.org/operation_3695
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    output: []
  homepage: https://bdcw.org/MetGENE/index.php
  homepage_status: 0
  language:
  - PHP
  - R
  lastUpdate: '2024-04-19T11:28:09.723894Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/metabolomicsworkbench/MetGENE
  maturity: null
  name: MetGENE
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/GIGASCIENCE/GIAD089
    metadata:
      abstract: 'Background: Biomedical research often involves contextual integration
        of multimodal and multiomic data in search of mechanisms for improved diagnosis,
        treatment, and monitoring. Researchers need to access information from diverse
        sources, comprising data in various and sometimes incongruent formats. The
        downstream processing of the data to decipher mechanisms by reconstructing
        networks and developing quantitative models warrants considerable effort.
        Results: MetGENE is a knowledge-based, gene-centric data aggregator that hierarchically
        retrieves information about the gene(s), their related pathway(s), reaction(s),
        metabolite(s), and metabolomic studies from standard data repositories under
        one dashboard to enable ease of access through centralization of relevant
        information. We note that MetGENE focuses only on those genes that encode
        for proteins directly associated with metabolites. All other gene–metabolite
        associations are beyond the current scope of MetGENE. Further, the information
        can be contextualized by filtering by species, anatomy (tissue), and condition
        (disease or phenotype). Conclusions: MetGENE is an open-source tool that aggregates
        metabolite information for a given gene(s) and presents them in different
        computable formats (e.g., JSON) for further integration with other omics studies.
        MetGENE is available at https://bdcw.org/MetGENE/index.php.'
      authors:
      - name: Srinivasan S.
      - name: Maurya M.R.
      - name: Ramachandran S.
      - name: Fahy E.
      - name: Subramaniam S.
      citationCount: 0
      date: '2023-01-01T00:00:00Z'
      journal: GigaScience
      title: 'MetGENE: gene-centric metabolomics information retrieval tool'
    note: null
    pmcid: PMC10659118
    pmid: '37983749'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  - term: Anatomy
    uri: http://edamontology.org/topic_3067
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T10:09:48.151582Z'
  biotoolsCURIE: biotools:mespeus
  biotoolsID: mespeus
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: kunyi.hsin@nchu.edu.tw
    fundrefid: null
    gridid: null
    name: Kun-Yi Hsin
    note: null
    orcidid: https://orcid.org/0000-0001-7220-3454
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Geng-Yu Lin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Database of metal coordination groups in proteins.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Metal-binding site prediction
      uri: http://edamontology.org/operation_3898
    - term: Protein-metal contact calculation
      uri: http://edamontology.org/operation_1834
    - term: Metal-bound cysteine detection
      uri: http://edamontology.org/operation_1831
    - term: Deposition
      uri: http://edamontology.org/operation_3431
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output: []
  homepage: http://mespeus.nchu.edu.tw/
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-19T10:09:48.154041Z'
  license: null
  link: []
  maturity: null
  name: MESPEUS
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/NAR/GKAD1009
    metadata:
      abstract: MESPEUS isã freelyãccessible database which uses carefully selected
        metal coordination groups found in metalloprotein str uct ures taken from
        the Protein Data Bãnk. T he datãbase contãins geometrical information of metal
        sites within proteins, including 40 metãl t ypes. In order to completely determine
        the metal coordination, the symmetry-related units ofã given protein str uct
        ureãre taken intoãccountãndãre generated using theãppropriate space group
        symmetry operations. This permitsã more complete description of the metal
        coordination geometry by includingãll coordinatingãtoms. The user-friendly
        web interfaceãllows users to directly search forã metal site of interest using
        se v eral useful options, including searching for metal elements, metal-donor
        distances, coordination number, donor residue group,ãnd str uct ural resolution.
        These searches can be carried out singly or in combination. The details ofã
        metal siteãnd the metal site(s) in the whole str uct ure can be graphically
        displa y ed using the interactiv e w eb interfãce. MESPEUS isãutomatically
        updated monthly b y synchronizing with the PDB database. An in v estigation
        f or the Mg-ATP interaction is giv en to demonstrate how MESPEUS can be used
        to e xtract inf ormationãbout metal sites by selecting str uct ureãnd coordination
        feat ures. MESPEUS isã vãilableãt ht tp://mespeus.nc hu.edu.tw/.
      authors:
      - name: Lin G.-Y.
      - name: Su Y.-C.
      - name: Huang Y.L.
      - name: Hsin K.-Y.
      citationCount: 1
      date: '2024-01-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: MESPEUS:ã database of metal coordination groups in proteins
    note: null
    pmcid: PMC10767821
    pmid: '37941148'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Biological databases
    uri: http://edamontology.org/topic_3071
  - term: NMR
    uri: http://edamontology.org/topic_0593
  - term: X-ray diffraction
    uri: http://edamontology.org/topic_2828
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T10:04:52.539998Z'
  biotoolsCURIE: biotools:deephlapred
  biotoolsID: deephlapred
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: guohuahhn@163.com
    fundrefid: null
    gridid: null
    name: Guohua Huang
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Xingyu Tang
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Peijie Zheng
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Deep learning-based method for non-classical HLA binder prediction.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Peptide immunogenicity prediction
      uri: http://edamontology.org/operation_0252
    - term: Promoter prediction
      uri: http://edamontology.org/operation_0440
    - term: Standardisation and normalisation
      uri: http://edamontology.org/operation_3435
    output: []
  homepage: http://www.biolscience.cn/DeepHLApred/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-04-19T10:04:52.542062Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/tangxingyu0/DeepHLApred
  maturity: null
  name: DeepHLAPred
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1186/S12864-023-09796-2
    metadata:
      abstract: Human leukocyte antigen (HLA) is closely involved in regulating the
        human immune system. Despite great advance in detecting classical HLA Class
        I binders, there are few methods or toolkits for recognizing non-classical
        HLA Class I binders. To fill in this gap, we have developed a deep learning-based
        tool called DeepHLAPred. The DeepHLAPred used electron-ion interaction pseudo
        potential, integer numerical mapping and accumulated amino acid frequency
        as initial representation of non-classical HLA binder sequence. The deep learning
        module was used to further refine high-level representations. The deep learning
        module comprised two parallel convolutional neural networks, each followed
        by maximum pooling layer, dropout layer, and bi-directional long short-term
        memory network. The experimental results showed that the DeepHLAPred reached
        the state-of-the-art performanceson the cross-validation test and the independent
        test. The extensive test demonstrated the rationality of the DeepHLAPred.
        We further analyzed sequence pattern of non-classical HLA class I binders
        by information entropy. The information entropy of non-classical HLA binder
        sequence implied sequence pattern to a certain extent. In addition, we have
        developed a user-friendly webserver for convenient use, which is available
        at http://www.biolscience.cn/DeepHLApred/ . The tool and the analysis is helpful
        to detect non-classical HLA Class I binder. The source code and data is available
        at https://github.com/tangxingyu0/DeepHLApred .
      authors:
      - name: Huang G.
      - name: Tang X.
      - name: Zheng P.
      citationCount: 0
      date: '2023-12-01T00:00:00Z'
      journal: BMC Genomics
      title: 'DeepHLAPred: a deep learning-based method for non-classical HLA binder
        prediction'
    note: null
    pmcid: PMC10666343
    pmid: '37993812'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Immunoproteins and antigens
    uri: http://edamontology.org/topic_2830
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T09:48:49.564191Z'
  biotoolsCURIE: biotools:refmetaplant
  biotoolsID: refmetaplant
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: pchen@cemps.ac.cn
    fundrefid: null
    gridid: null
    name: Ping Chen
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: lixuan@sippe.ac.cn
    fundrefid: null
    gridid: null
    name: Xuan Li
    note: null
    orcidid: https://orcid.org/0000-0002-7435-9652
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Reference metabolome database for plants across five major phyla.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    - term: Spectral library search
      uri: http://edamontology.org/operation_3801
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output: []
  homepage: https://www.biosino.org/RefMetaDB/
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-19T09:48:49.566259Z'
  license: null
  link: []
  maturity: null
  name: RefMetaPlant
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/NAR/GKAD980
    metadata:
      abstract: Plants are unique with tremendous chemical diversity and metabolic
        complexity, which is highlighted by estimates that green plants collectively
        produce metabolites numbering in the millions. Plant metabolites play crucial
        roles in all aspects of plant biology, like growth, development, stress responses,
        etc. However, the lack of a reference metabolome for plants, and paucity of
        high-quality standard compound spectral libraries and related analytical tools,
        have hindered the discovery and functional study of phytochemicals in plants.
        Here, by leveraging an advanced LC–MS platform, we generated untargeted mass
        spectral data from >150 plant species collected across the five major phyla.
        Using a self-developed computation protocol, we constructed reference metabolome
        for 153 plant species. A ‘Reference Metabolome Database for Plants’ (RefMetaPlant)
        was built to encompass the reference metabolome, integrated standard compound
        mass spectral libraries for annotation, and related query and analytical tools
        like ‘LC–MS/MS Query’, ‘RefMetaBlast’ and ‘CompoundLibBlast’ for searches
        and profiling of plant metabolome and metabolite identification. Analogous
        to a reference genome in genomic research, RefMetaPlant provides a powerful
        platform to support plant genome-scale metabolite analysis to promote knowledge/data
        sharing and collaboration in the field of metabolomics. RefMetaPlant is freely
        available at https://www.biosino.org/RefMetaDB/.
      authors:
      - name: Shi H.
      - name: Wu X.
      - name: Zhu Y.
      - name: Jiang T.
      - name: Wang Z.
      - name: Li X.
      - name: Liu J.
      - name: Zhang Y.
      - name: Chen F.
      - name: Gao J.
      - name: Xu X.
      - name: Zhang G.
      - name: Xiao N.
      - name: Feng X.
      - name: Zhang P.
      - name: Wu Y.
      - name: Li A.
      - name: Chen P.
      - name: Li X.
      citationCount: 1
      date: '2024-01-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'RefMetaPlant: a reference metabolome database for plants across five
        major phyla'
    note: null
    pmcid: PMC10767953
    pmid: '37953341'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Agricultural science
    uri: http://edamontology.org/topic_3810
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T09:34:52.013720Z'
  biotoolsCURIE: biotools:ppgr
  biotoolsID: ppgr
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: baoym@big.ac.cn
    fundrefid: null
    gridid: null
    name: Yiming Bao
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: lirj@big.ac.cn
    fundrefid: null
    gridid: null
    name: Rujiao Li
    note: null
    orcidid: https://orcid.org/0000-0002-3276-8335
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: jbxie@bjfu.edu.cn
    fundrefid: null
    gridid: null
    name: Jianbo Xie
    note: null
    orcidid: https://orcid.org/0000-0002-8650-7675
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Comprehensive perennial plant genomes and regulation database.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Gene regulatory network prediction
      uri: http://edamontology.org/operation_2437
    - term: Database search
      uri: http://edamontology.org/operation_2421
    - term: Text mining
      uri: http://edamontology.org/operation_0306
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: PCR primer design
      uri: http://edamontology.org/operation_0308
    output: []
  homepage: https://ngdc.cncb.ac.cn/ppgr/
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-19T09:34:52.015995Z'
  license: null
  link: []
  maturity: null
  name: PPGR
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/NAR/GKAD963
    metadata:
      abstract: 'Perennial woody plants hold vital ecological significance, distinguished
        by their unique traits. While significant progress has been made in their
        genomic and functional studies, a major challenge persists: the absence of
        a comprehensive reference platform for collection, integration and in-depth
        analysis of the vast amount of data. Here, we present PPGR (Resource for Perennial
        Plant Genomes and Regulation; https://ngdc.cncb.ac.cn/ppgr/) to address this
        critical gap, by collecting, integrating, analyzing and visualizing genomic,
        gene regulation and functional data of perennial plants. PPGR currently includes
        60 species, 847 million protein–protein/TF (transcription factor)-target interactions,
        9016 transcriptome samples under various environmental conditions and genetic
        backgrounds. Noteworthy is the focus on genes that regulate wood production,
        seasonal dormancy, terpene biosynthesis and leaf senescence representing a
        wealth of information derived from experimental data, literature mining, public
        databases and genomic predictions. Furthermore, PPGR incorporates a range
        of multi-omics search and analysis tools to facilitate browsing and application
        of these extensive datasets. PPGR represents a comprehensive and high-quality
        resource for perennial plants, substantiated by an illustrative case study
        that demonstrates its capacity in unraveling gene functions and shedding light
        on potential regulatory processes.'
      authors:
      - name: Yang S.
      - name: Zong W.
      - name: Shi L.
      - name: Li R.
      - name: Ma Z.
      - name: Ma S.
      - name: Si J.
      - name: Wu Z.
      - name: Zhai J.
      - name: Ma Y.
      - name: Fan Z.
      - name: Chen S.
      - name: Huang H.
      - name: Zhang D.
      - name: Bao Y.
      - name: Li R.
      - name: Xie J.
      citationCount: 2
      date: '2024-01-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'PPGR: a comprehensive perennial plant genomes and regulation database'
    note: null
    pmcid: PMC10767873
    pmid: '37933857'
    type: []
    version: null
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  toolType:
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  topic:
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Gene regulation
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  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T09:32:39.965113Z'
  biotoolsCURIE: biotools:uniprotextractr
  biotoolsID: uniprotextractr
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  confidence_flag: tool
  cost: Free of charge
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    fundrefid: null
    gridid: null
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    note: null
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  description: Shiny App and R package for easily extracting protein-specific UniProtKB
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  lastUpdate: '2024-04-19T09:33:09.634027Z'
  license: null
  link:
  - note: null
    type:
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    url: https://github.com/alex-bio/UniProtExtractR
  maturity: null
  name: UniProtExtractR
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  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIOADV/VBAD157
    metadata:
      abstract: 'UniProtKB is a publicly accessible database of annotated protein
        features for numerous organisms; however, globally extracting protein entry
        information for data visualization and categorization can be challenging.
        While the UniProtKB entry syntax maintains database consistency, it simultaneously
        obscures key terms within long character strings. To increase accessibility,
        UniProtExtractR is both an app and R package that extracts desired information
        across nine UniProtKB categories: DNA binding, Pathway, Transmembrane, Signal
        peptide, Protein families, Domain [FT], Motif, Involvement in disease, and
        Subcellular location [CC]. The app features interactive frequency tables that
        globally summarize both the original UniProtKB input query as well as the
        extracted/changed entry values. Moreover, UniProtExtractR includes a tractable
        mapping algorithm to define custom organelle-level resolution. UniProtExtractR
        exists as a freely accessible Shiny app that requires no coding experience
        as well as R package, the code of which is entirely open source.'
      authors:
      - name: Panov A.
      - name: Harper J.W.
      citationCount: 0
      date: '2023-01-01T00:00:00Z'
      journal: Bioinformatics Advances
      title: 'UniProtExtractR: an app and R package for easily extracting protein-specific
        UniProtKB information and fine-tuning organelle resolution'
    note: null
    pmcid: PMC10636703
    pmid: '37953912'
    type: []
    version: null
  relation: []
  toolType:
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  - Web API
  topic:
  - term: Cell biology
    uri: http://edamontology.org/topic_2229
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Gene and protein families
    uri: http://edamontology.org/topic_0623
  - term: Protein modifications
    uri: http://edamontology.org/topic_0601
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T09:14:48.657400Z'
  biotoolsCURIE: biotools:como
  biotoolsID: como
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: thelikar2@unl.edu
    fundrefid: null
    gridid: null
    name: Tomáš Helikar
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: bpuniya2@unl.edu
    fundrefid: null
    gridid: null
    name: Bhanwar Lal Puniya
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Pipeline for multi-omics data integration in metabolic modelling and
    drug discovery.
  documentation: []
  download: []
  editPermission:
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    type: public
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  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Metabolic network modelling
      uri: http://edamontology.org/operation_3660
    - term: Metabolic pathway prediction
      uri: http://edamontology.org/operation_3929
    - term: Differential gene expression profiling
      uri: http://edamontology.org/operation_3223
    output: []
  homepage: https://github.com/HelikarLab/COMO
  homepage_status: 0
  language:
  - Python
  - R
  lastUpdate: '2024-04-19T09:14:48.659485Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: COMO
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  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIB/BBAD387
    metadata:
      abstract: Identifying potential drug targets using metabolic modeling requires
        integrating multiple modeling methods and heterogeneous biological datasets,
        which can be challenging without efficient tools. We developed Constraint-based
        Optimization of Metabolic Objectives (COMO), a user-friendly pipeline that
        integrates multi-omics data processing, context-specific metabolic model development,
        simulations, drug databases and disease data to aid drug discovery. COMO can
        be installed as a Docker Image or with Conda and includes intuitive instructions
        within a Jupyter Lab environment. It provides a comprehensive solution for
        the integration of bulk and single-cell RNA-seq, microarrays and proteomics
        outputs to develop context-specific metabolic models. Using public databases,
        open-source solutions for model construction and a streamlined approach for
        predicting repurposable drugs, COMO enables researchers to investigate low-cost
        alternatives and novel disease treatments. As a case study, we used the pipeline
        to construct metabolic models of B cells, which simulate and analyze them
        to predict metabolic drug targets for rheumatoid arthritis and systemic lupus
        erythematosus, respectively. COMO can be used to construct models for any
        cell or tissue type and identify drugs for any human disease where metabolic
        inhibition is relevant. The pipeline has the potential to improve the health
        of the global community cost-effectively by providing high-confidence targets
        to pursue in preclinical and clinical studies. The source code of the COMO
        pipeline is available at https://github.com/HelikarLab/COMO. The Docker image
        can be pulled at https://github.com/HelikarLab/COMO/pkgs/container/como.
      authors:
      - name: Bessell B.
      - name: Loecker J.
      - name: Zhao Z.
      - name: Aghamiri S.S.
      - name: Mohanty S.
      - name: Amin R.
      - name: Helikar T.
      - name: Puniya B.L.
      citationCount: 0
      date: '2023-11-01T00:00:00Z'
      journal: Briefings in Bioinformatics
      title: 'COMO: a pipeline for multi-omics data integration in metabolic modeling
        and drug discovery'
    note: null
    pmcid: PMC10627799
    pmid: '37930022'
    type: []
    version: null
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Drug discovery
    uri: http://edamontology.org/topic_3336
  - term: Endocrinology and metabolism
    uri: http://edamontology.org/topic_3407
  - term: Drug metabolism
    uri: http://edamontology.org/topic_3375
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Preclinical and clinical studies
    uri: http://edamontology.org/topic_3379
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-19T09:11:21.895049Z'
  biotoolsCURIE: biotools:varcards2
  biotoolsID: varcards2
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: ghzhao@csu.edu.cn
    fundrefid: null
    gridid: null
    name: Guihu Zhao
    note: null
    orcidid: https://orcid.org/0000-0003-4033-1843
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: lijinchen@csu.edu.cn
    fundrefid: null
    gridid: null
    name: Bin Li
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jinchen Li
    note: null
    orcidid: https://orcid.org/0000-0003-3335-9303
    rorid: null
    typeEntity: Person
    typeRole: []
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  description: Integrated genetic and clinical database for ACMG-AMP variant-interpretation
    guidelines in the human whole genome.
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  download: []
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  function:
  - cmd: null
    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_3461
    - term: Variant classification
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    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    - term: Variant prioritisation
      uri: http://edamontology.org/operation_3226
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output: []
  homepage: http://www.genemed.tech/varcards2/
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  license: null
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  name: VarCards2
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  publication:
  - doi: 10.1093/NAR/GKAD1061
    metadata:
      abstract: VarCards, an online database, combines comprehensive variant- and
        gene-level annotation data to streamline genetic counselling for coding variants.
        Recognising the increasing clinical relevance of non-coding variations, there
        has been an accelerated development of bioinformatics tools dedicated to interpreting
        non-coding variations, including single-nucleotide variants and copy number
        variations. Regrettably, most tools remain as either locally installed databases
        or command-line tools dispersed across diverse online platforms. Such a landscape
        poses inconveniences and challenges for genetic counsellors seeking to utilise
        these resources without advanced bioinformatics expertise. Consequently, we
        developed VarCards2, which incorporates nearly nine billion artificially generated
        single-nucleotide variants (including those from mitochondrial DNA) and compiles
        vital annotation information for genetic counselling based on ACMG-AMP variant-interpretation
        guidelines. These annotations include (I) functional effects; (II) minor allele
        frequencies; (III) comprehensive function and pathogenicity predictions covering
        all potential variants, such as non-synonymous substitutions, non-canonical
        splicing variants, and non-coding variations and (IV) gene-level information.
        Furthermore, VarCards2 incorporates 368 820 266 documented short insertions
        and deletions and 2 773 555 documented copy number variations, complemented
        by their corresponding annotation and prediction tools. In conclusion, VarCards2,
        by integrating over 150 variant- and gene-level annotation sources, significantly
        enhances the efficiency of genetic counselling and can be freely accessed
        at http://www.genemed.tech/varcards2/.
      authors:
      - name: Wang Z.
      - name: Zhao G.
      - name: Zhu Z.
      - name: Wang Y.
      - name: Xiang X.
      - name: Zhang S.
      - name: Luo T.
      - name: Zhou Q.
      - name: Qiu J.
      - name: Tang B.
      - name: Xia K.
      - name: Li B.
      - name: Li J.
      citationCount: 2
      date: '2024-01-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'VarCards2: an integrated genetic and clinical database for ACMG-AMP
        variant-interpretation guidelines in the human whole genome'
    note: null
    pmcid: PMC10767961
    pmid: '37956311'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
  - term: RNA splicing
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  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Epigenetics
    uri: http://edamontology.org/topic_3295
  validated: 0
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- accessibility: Open access
  additionDate: '2024-04-19T08:45:10.333820Z'
  biotoolsCURIE: biotools:pgs-depot
  biotoolsID: pgs-depot
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  confidence_flag: tool
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Dandan Huang
    note: null
    orcidid: null
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  - email: yangsheng@njmu.edu.cn
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    gridid: null
    name: Sheng Yang
    note: null
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    typeEntity: Person
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    url: null
  description: Comprehensive resource for polygenic scores constructed by summary
    statistics based methods.
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  language:
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  lastUpdate: '2024-04-19T08:45:10.336582Z'
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  link:
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  publication:
  - doi: 10.1093/NAR/GKAD1029
    metadata:
      abstract: Polygenic score (PGS) isãn important tool for the genetic prediction
        of comple x traits. Ho w e v er, thereãre currently no resources pro viding
        comprehensive PGSs computed from published summary statistics,ãnd it is difficult
        to implementãnd run different PGS methods due to the complexity of their pipelinesãnd
        parameter settings. Toãddress these issues, we introduceã new resource called
        PGS-Depot containing the most comprehensive set of publiclyã vãilable disease-related
        GWAS summary statistics. PGS-Depot includes 5585 high quality summary stãtistics
        (1933 quantitãtiveãnd 3652 binary trait statistics) curated from 1564 traits
        in Europeanãnd East Asian populations. A standardized best-practice pipeline
        is used to implement 11 summary statistics-based PGS methods, each with different
        modelãssumptionsãnd estimation procedures. T he prediction perf ormance of
        each method can be compared for both in-ãnd cross-ancestry populations,ãnd
        users canãlso submit their own summary statistics to obtain custom PGS with
        theã vãilable methods. Other features include searching for PGSs by trait
        name, publication, cohort information, population, or the MeSH ontology treeãnd
        searching for trait descriptions with the e xperimental fãctor ontology (EFO).
        All scores, SNP effect sizesãnd summary statistics can be downloaded via FTP.
        PGS-Depot is freelyã vãilableãt http://www.pgsdepot.net .
      authors:
      - name: Cao C.
      - name: Zhang S.
      - name: Wang J.
      - name: Tian M.
      - name: Ji X.
      - name: Huang D.
      - name: Yang S.
      - name: Gu N.
      citationCount: 0
      date: '2024-01-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: PGS-Depot:ã comprehensive resource for polygenic scores constructed by
        summary statistics based methods
    note: null
    pmcid: PMC10767792
    pmid: '37953384'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
  - term: DNA polymorphism
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  - term: GWAS study
    uri: http://edamontology.org/topic_3517
  - term: Biobank
    uri: http://edamontology.org/topic_3337
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  validated: 0
  version: []
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