count: 29612
list:
- accessibility: Open access
  additionDate: '2024-04-30T13:12:13.495572Z'
  biotoolsCURIE: biotools:virushound-i
  biotoolsID: virushound-i
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: beltran.lissabet.jf@gmail.com
    fundrefid: null
    gridid: null
    name: Jorge F Beltrán
    note: null
    orcidid: https://orcid.org/0000-0003-2703-9629
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Fernanda Parraguez-Contreras
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Prediction of viral proteins involved in the evasion of host adaptive
    immune response using the random forest algorithm and generative adversarial network
    for data augmentation.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Virulence prediction
      uri: http://edamontology.org/operation_3461
    - term: Peptide immunogenicity prediction
      uri: http://edamontology.org/operation_0252
    - term: Epitope mapping
      uri: http://edamontology.org/operation_0416
    - term: Deposition
      uri: http://edamontology.org/operation_3431
    output: []
  homepage: https://www.biochemintelli.com/VirusHound-I
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-30T13:12:13.499807Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/jfbldevs/virushound-I
  maturity: null
  name: VirusHound-I
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIB/BBAD434
    metadata:
      abstract: Throughout evolution, pathogenic viruses have developed different
        strategies to evade the response of the adaptive immune system. To carry out
        successful replication, some pathogenic viruses encode different proteins
        that manipulate the molecular mechanisms of host cells. Currently, there are
        different bioinformatics tools for virus research; however, none of them focus
        on predicting viral proteins that evade the adaptive system. In this work,
        we have developed a novel tool based on machine and deep learning for predicting
        this type of viral protein named VirusHound-I. This tool is based on a model
        developed with the multilayer perceptron algorithm using the dipeptide composition
        molecular descriptor. In this study, we have also demonstrated the robustness
        of our strategy for data augmentation of the positive dataset based on generative
        antagonistic networks. During the 10-fold cross-validation step in the training
        dataset, the predictive model showed 0.947 accuracy, 0.994 precision, 0.943
        F1 score, 0.995 specificity, 0.896 sensitivity, 0.894 kappa, 0.898 Matthew’s
        correlation coefficient and 0.989 AUC. On the other hand, during the testing
        step, the model showed 0.964 accuracy, 1.0 precision, 0.967 F1 score, 1.0
        specificity, 0.936 sensitivity, 0.929 kappa, 0.931 Matthew’s correlation coefficient
        and 1.0 AUC. Taking this model into account, we have developed a tool called
        VirusHound-I that makes it possible to predict viral proteins that evade the
        host’s adaptive immune system. We believe that VirusHound-I can be very useful
        in accelerating studies on the molecular mechanisms of evasion of pathogenic
        viruses, as well as in the discovery of therapeutic targets.
      authors:
      - name: Beltran J.F.
      - name: Belen L.H.
      - name: Farias J.G.
      - name: Zamorano M.
      - name: Lefin N.
      - name: Miranda J.
      - name: Parraguez-Contreras F.
      citationCount: 1
      date: '2024-01-01T00:00:00Z'
      journal: Briefings in Bioinformatics
      title: 'VirusHound-I: prediction of viral proteins involved in the evasion of
        host adaptive immune response using the random forest algorithm and generative
        adversarial network for data augmentation'
    note: null
    pmcid: PMC10753651
    pmid: '38033292'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Immunoinformatics
    uri: http://edamontology.org/topic_3948
  - term: Immunogenetics
    uri: http://edamontology.org/topic_3930
  - term: Immunoproteins and antigens
    uri: http://edamontology.org/topic_2830
  - term: Pharmacology
    uri: http://edamontology.org/topic_0202
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-30T13:03:54.037389Z'
  biotoolsCURIE: biotools:jsonwp
  biotoolsID: jsonwp
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: jernigan@iastate.edu
    fundrefid: null
    gridid: null
    name: Robert L Jernigan
    note: null
    orcidid: https://orcid.org/0000-0003-0996-8360
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Mesih Kilinc
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'Static website generator for protein bioinformatics research.


    It is a JS application that creates a website based on the JSON data.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Parsing
      uri: http://edamontology.org/operation_1812
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output: []
  homepage: http://jsonwp.onrender.com
  homepage_status: 0
  language:
  - JavaScript
  lastUpdate: '2024-04-30T13:03:54.039616Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/MesihK/react-json-wpbuilder
  maturity: null
  name: JSONWP
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIOADV/VBAD154
    metadata:
      abstract: 'Motivation: Presenting the integrated results of bioinformatics research
        can be challenging and requires sophisticated visualization components, which
        can be time-consuming to develop. This article presents a new way to effectively
        communicate research findings. Results: We have developed a static web page
        generator, JSONWP, which is specifically designed for protein bioinformatics
        research. Utilizing React (a JavaScript library used to build interactive
        and dynamic user interfaces for web applications), we have integrated publicly
        available bioinformatics visualization components to provide standardized
        access to these components. JSON (or JavaScript Object Notation, is a lightweight
        textual data format often used to structure and exchange information between
        different software tools.) is used as the input source due to its ability
        to represent nearly all types of data using key and value pairs. This allows
        researchers to use their preferred programming language to create a JSON representation,
        which can then be converted into a website by JSONWP. No server or domain
        is required to host the website, as only the publicly accessible JSON file
        is required. Conclusions: Overall, JSONWP provides a useful new tool for bioinformatics
        researchers to effectively communicate their findings. The open-source implementation
        is located at https://github.com/MesihK/react-json-wpbuilder, and the tool
        can be used at jsonwp.onrender.com.'
      authors:
      - name: Kilinc M.
      - name: Jia K.
      - name: Jernigan R.L.
      citationCount: 0
      date: '2023-01-01T00:00:00Z'
      journal: Bioinformatics Advances
      title: 'JSONWP: a static website generator for protein bioinformatics research'
    note: null
    pmcid: PMC10613403
    pmid: '37904893'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Software engineering
    uri: http://edamontology.org/topic_3372
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-30T12:45:47.267049Z'
  biotoolsCURIE: biotools:cell4d
  biotoolsID: cell4d
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: jparkin@sickkids.ca
    fundrefid: null
    gridid: null
    name: John Parkinson
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Donny Chan
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Cell4D is a Linux C++-based graphical spatial stochatic cell simulator
    capable of simulating a wide variety of cellular pathways. Molecules are simulated
    as particles within a user-defined simulation space under a Smoluchowski-based
    reaction-diffusion system on a static time-step basis.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Pathway analysis
      uri: http://edamontology.org/operation_3928
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output: []
  homepage: https://github.com/ParkinsonLab/cell4d
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2024-04-30T12:45:47.269277Z'
  license: null
  link: []
  maturity: null
  name: Cell4D
  operatingSystem: []
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1186/s12859-024-05739-0
    metadata:
      abstract: 'Background: With the generation of vast compendia of biological datasets,
        the challenge is how best to interpret ‘omics data alongside biochemical and
        other small-scale experiments to gain meaningful biological insights. Key
        to this challenge are computational methods that enable domain-users to generate
        novel hypotheses that can be used to guide future experiments. Of particular
        interest are flexible modeling platforms, capable of simulating a diverse
        range of biological systems with low barriers of adoption to those with limited
        computational expertise. Results: We introduce Cell4D, a spatial-temporal
        modeling platform combining a robust simulation engine with integrated graphics
        visualization, a model design editor, and an underlying XML data model capable
        of capturing a variety of cellular functions. Cell4D provides an interactive
        visualization mode, allowing intuitive feedback on model behavior and exploration
        of novel hypotheses, together with a non-graphics mode, compatible with high
        performance cloud compute solutions, to facilitate generation of statistical
        data. To demonstrate the flexibility and effectiveness of Cell4D, we investigate
        the dynamics of CEACAM1 localization in T-cell activation. We confirm the
        importance of Ca2+ microdomains in activating calmodulin and highlight a key
        role of activated calmodulin on the surface expression of CEACAM1. We further
        show how lymphocyte-specific protein tyrosine kinase can help regulate this
        cell surface expression and exploit spatial modeling features of Cell4D to
        test the hypothesis that lipid rafts regulate clustering of CEACAM1 to promote
        trans-binding to neighbouring cells. Conclusions: Through demonstrating its
        ability to test and generate hypotheses, Cell4D represents an effective tool
        to help integrate knowledge across diverse, large and small-scale datasets.'
      authors:
      - name: Chan D.
      - name: Cromar G.L.
      - name: Taj B.
      - name: Parkinson J.
      citationCount: 0
      date: '2024-12-01T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'Cell4D: a general purpose spatial stochastic simulator for cellular
        pathways'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Lipids
    uri: http://edamontology.org/topic_0153
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-30T12:35:46.193814Z'
  biotoolsCURIE: biotools:jeasytfm
  biotoolsID: jeasytfm
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: philippe.carl@unistra.fr
    fundrefid: null
    gridid: null
    name: Philippe Carl
    note: null
    orcidid: https://orcid.org/0000-0001-8063-3294
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Philippe Rondé
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Open-source software package for the analysis of large 2D TFM data
    within ImageJ.
  documentation:
  - note: null
    type:
    - User manual
    url: http://questpharma.u-strasbg.fr/JEasyTFM_manual.html
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Splitting
      uri: http://edamontology.org/operation_3359
    - term: Editing
      uri: http://edamontology.org/operation_3096
    - term: Image analysis
      uri: http://edamontology.org/operation_3443
    output: []
  homepage: http://questpharma.u-strasbg.fr/JEasyTFM.html
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-30T12:35:46.196223Z'
  license: null
  link: []
  maturity: null
  name: JeasyTFM
  operatingSystem: []
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIOADV/VBAD156
    metadata:
      abstract: 'Motivation: Cells adhering to the extracellular matrix can sense
        and respond to a wide variety of chemical and physical features of the adhesive
        surface. Traction force microscopy (TFM) allows determining the tensile forces
        exerted by the cells on their substrate with high resolution. Results: To
        allow broad access of this techniques to cell biology laboratories we developed
        JeasyTFM, an open-source ImageJ package able to process multi-color and multi-position
        time-lapse pictures thus suitable for the automatic analysis of large TFM
        data.'
      authors:
      - name: Carl P.
      - name: Ronde P.
      citationCount: 0
      date: '2023-01-01T00:00:00Z'
      journal: Bioinformatics Advances
      title: 'JEasyTFM: an open-source software package for the analysis of large
        2D TFM data within ImageJ'
    note: null
    pmcid: PMC10625472
    pmid: '37928344'
    type: []
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Imaging
    uri: http://edamontology.org/topic_3382
  - term: Cytometry
    uri: http://edamontology.org/topic_3934
  - term: Physics
    uri: http://edamontology.org/topic_3318
  - term: Protein expression
    uri: http://edamontology.org/topic_0108
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-30T12:33:30.345341Z'
  biotoolsCURIE: biotools:syntenyplotter
  biotoolsID: syntenyplotter
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: m.farre-belmonte@kent.ac.uk
    fundrefid: null
    gridid: null
    name: Marta Farré
    note: null
    orcidid: https://orcid.org/0000-0001-9170-5767
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Sarah Quigley
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: User-friendly R package to visualize genome synteny, ideal for both
    experienced and novice bioinformaticians.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Formatting
      uri: http://edamontology.org/operation_0335
    - term: Scaffolding
      uri: http://edamontology.org/operation_3216
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output: []
  homepage: https://farre-lab.github.io/syntenyPlotteR/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2024-04-30T12:33:30.347736Z'
  license: null
  link: []
  maturity: null
  name: syntenyPlotteR
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIOADV/VBAD161
    metadata:
      abstract: 'Motivation: The rapid increase in the number of chromosome-scale
        genome assemblies has renewed interest in chromosome evolution studies. The
        visualization of syntenic relationships between genomes is a crucial initial
        step in the study of chromosome rearrangements and evolution. There are few
        tools available that serve this purpose, and they can be difficult to learn.
        Moreover, these tools are limited in the number of species comparisons that
        can be visualized and the size of chromosome rearrangements identified. Thus,
        the development of novel visualization tools is in strong need. Results: Here,
        we present syntenyPlotteR, an R package developed to visualize homologous
        synteny blocks in a pairwise or multispecies manner. This package contains
        three functions that allow users to generate publication-quality representations
        of syntenic relationships easily and quickly between genomes of interest.'
      authors:
      - name: Quigley S.
      - name: Damas J.
      - name: Larkin D.M.
      - name: Farre M.
      citationCount: 2
      date: '2023-01-01T00:00:00Z'
      journal: Bioinformatics Advances
      title: 'syntenyPlotteR: a user-friendly R package to visualize genome synteny,
        ideal for both experienced and novice bioinformaticians'
    note: null
    pmcid: PMC10660287
    pmid: '38023328'
    type: []
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Structural variation
    uri: http://edamontology.org/topic_3175
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Evolutionary biology
    uri: http://edamontology.org/topic_3299
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-30T12:31:41.312350Z'
  biotoolsCURIE: biotools:degronmd
  biotoolsID: degronmd
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: zhongming.zhao@uth.tmc.edu
    fundrefid: null
    gridid: null
    name: Zhongming Zhao
    note: null
    orcidid: https://orcid.org/0000-0002-3477-0914
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Haodong Xu
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Ruifeng Hu
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'DegronMD: protein-targeted degradation, mutation and drug response
    to degrons.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Small molecule design
      uri: http://edamontology.org/operation_4009
    - term: PTM site prediction
      uri: http://edamontology.org/operation_0417
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output: []
  homepage: https://bioinfo.uth.edu/degronmd
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-30T12:31:41.315403Z'
  license: null
  link: []
  maturity: null
  name: DegronMD
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/MOLBEV/MSAD253
    metadata:
      abstract: Protein-Targeted degradation is an emerging and promising therapeutic
        approach. The specificity of degradation and the maintenance of cellular homeostasis
        are determined by the interactions between E3 ubiquitin ligase and degradation
        signals, known as degrons. The human genome encodes over 600 E3 ligases; however,
        only a small number of targeted degron instances have been identified so far.
        In this study, we introduced DegronMD, an open knowledgebase designed for
        the investigation of degrons, their associated dysfunctional events, and drug
        responses. We revealed that degrons are evolutionarily conserved and tend
        to occur near the sites of protein translational modifications, particularly
        in the regions of disordered structure and higher solvent accessibility. Through
        pattern recognition and machine learning techniques, we constructed the degrome
        landscape across the human proteome, yielding over 18,000 new degrons for
        targeted protein degradation. Furthermore, dysfunction of degrons disrupts
        the degradation process and leads to the abnormal accumulation of proteins;
        this process is associated with various types of human cancers. Based on the
        estimated phenotypic changes induced by somatic mutations, we systematically
        quantified and assessed the impact of mutations on degron function in pan-cancers;
        these results helped to build a global mutational map on human degrome, including
        89,318 actionable mutations that may induce the dysfunction of degrons and
        disrupt protein degradation pathways. Multiomics integrative analysis unveiled
        over 400 drug resistance events associated with the mutations in functional
        degrons. DegronMD, accessible at https://bioinfo.uth.edu/degronmd, is a useful
        resource to explore the biological mechanisms, infer protein degradation,
        and assist with drug discovery and design on degrons.
      authors:
      - name: Xu H.
      - name: Hu R.
      - name: Zhao Z.
      citationCount: 0
      date: '2023-12-01T00:00:00Z'
      journal: Molecular Biology and Evolution
      title: 'DegronMD: Leveraging Evolutionary and Structural Features for Deciphering
        Protein-Targeted Degradation, Mutations, and Drug Response to Degrons'
    note: null
    pmcid: PMC10701100
    pmid: '37992195'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Protein targeting and localisation
    uri: http://edamontology.org/topic_0140
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Oncology
    uri: http://edamontology.org/topic_2640
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-30T12:28:42.617345Z'
  biotoolsCURIE: biotools:probiominserver
  biotoolsID: probiominserver
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: chieh@imst.nsysu.edu.tw
    fundrefid: null
    gridid: null
    name: Chih-Chieh Chen
    note: null
    orcidid: https://orcid.org/0000-0002-5844-8428
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Yen-Yi Liu
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Integrated platform for assessing the safety and functional properties
    of potential probiotic strains.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Genome report
        uri: http://edamontology.org/data_2711
      format:
      - term: FASTA-like (text)
        uri: http://edamontology.org/format_2200
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Multilocus sequence typing
      uri: http://edamontology.org/operation_3840
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output: []
  homepage: https://probiomindb.imst.nsysu.edu.tw
  homepage_status: 0
  language:
  - JavaScript
  - PHP
  - Perl
  lastUpdate: '2024-04-30T12:28:42.620166Z'
  license: null
  link: []
  maturity: null
  name: ProbioMinServer
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIOADV/VBAD153
    metadata:
      abstract: 'Motivation: ProbioMinServer is a platform designed to help researchers
        access information on probiotics regarding a wide variety of characteristics,
        such as safety (e.g. antimicrobial resistance, virulence, pathogenic, plasmid,
        and prophage genes) and functionality (e.g. functional classes, carbohydrate-active
        enzyme, and metabolite gene cluster profile). Because probiotics are functional
        foods, their safety and functionality are a crucial part of health care. Genomics
        has become a crucial methodology for investigating the safety and functionality
        of probiotics in food and feed. This shift is primarily attributed to the
        growing affordability of next-generation sequencing technologies. However,
        no integrated platform is available for simultaneously evaluating probiotic
        strain safety, investigating probiotic functionality, and identifying known
        phylogenetically related strains. Results: Thus, we constructed a new platform,
        ProbioMinServer, which incorporates these functions. ProbioMinServer accepts
        whole-genome sequence files in the FASTA format. If the query genome belongs
        to the 25 common probiotic species collected in our database, the server performs
        a database search and analyzes the core-genome multilocus sequence typing.
        Front-end applications were implemented in JavaScript with a bootstrap framework,
        and back-end programs were implemented using PHP, Perl, and Python. ProbioMinServer
        can help researchers quickly and easily retrieve information on the safety
        and functionality of various probiotics.'
      authors:
      - name: Liu Y.-Y.
      - name: Hsu C.-Y.
      - name: Yang Y.-C.
      - name: Huang C.-H.
      - name: Chen C.-C.
      citationCount: 0
      date: '2023-01-01T00:00:00Z'
      journal: Bioinformatics Advances
      title: 'ProbioMinServer: an integrated platform for assessing the safety and
        functional properties of potential probiotic strains'
    note: null
    pmcid: PMC10625473
    pmid: '37928343'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  - term: Agricultural science
    uri: http://edamontology.org/topic_3810
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-30T12:08:01.090084Z'
  biotoolsCURIE: biotools:scan_db
  biotoolsID: scan_db
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: zhanglm36@mail.sysu.edu.cn
    fundrefid: null
    gridid: null
    name: Liangming Zhang
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: ronglm@mail.sysu.edu.cn
    fundrefid: null
    gridid: null
    name: Limin Rong
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: xdwang@fuccb.com
    fundrefid: null
    gridid: null
    name: Xiangdong Wang
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Dongsheng Chen
    note: null
    orcidid: https://orcid.org/0000-0002-7196-4136
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: SCAN is a neural database that combines single cell transcriptome and
    spatial transcriptome data.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence motif recognition
      uri: http://edamontology.org/operation_0239
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Neurite measurement
      uri: http://edamontology.org/operation_3450
    output: []
  homepage: http://scanatlas.net
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-30T12:08:01.092348Z'
  license: null
  link: []
  maturity: null
  name: SCAN
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/NAR/GKAD895
    metadata:
      abstract: The nervous system is one of the most complicated and enigmatic systems
        within the animal kingdom. Recently, the emergence and development of spatial
        transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) technologies
        have provided an unprecedented ability to systematically decipher the cellular
        heterogeneity and spatial locations of the nervous system from multiple unbiased
        aspects. However, efficiently integrating, presenting and analyzing massive
        multiomic data remains a huge challenge. Here, we manually collected and comprehensively
        analyzed high-quality scRNA-seq and ST data from the nervous system, covering
        10 679 684 cells. In addition, multi-omic datasets from more than 900 species
        were included for extensive data mining from an evolutionary perspective.
        Furthermore, over 100 neurological diseases (e.g. Alzheimer’s disease, Parkinson’s
        disease, Down syndrome) were systematically analyzed for high-throughput screening
        of putative biomarkers. Differential expression patterns across developmental
        time points, cell types and ST spots were discerned and subsequently subjected
        to extensive interpretation. To provide researchers with efficient data exploration,
        we created a new database with interactive interfaces and integrated functions
        called the Spatiotemporal Cloud Atlas for Neural cells (SCAN), freely accessible
        at http://47.98.139.124:8799 or http://scanatlas.net. SCAN will benefit the
        neuroscience research community to better exploit the spatiotemporal atlas
        of the neural system and promote the development of diagnostic strategies
        for various neurological disorders.
      authors:
      - name: Deng Y.
      - name: Lu Y.
      - name: Li M.
      - name: Shen J.
      - name: Qin S.
      - name: Zhang W.
      - name: Zhang Q.
      - name: Shen Z.
      - name: Li C.
      - name: Jia T.
      - name: Chen P.
      - name: Peng L.
      - name: Chen Y.
      - name: Zhang W.
      - name: Liu H.
      - name: Zhang L.
      - name: Rong L.
      - name: Wang X.
      - name: Chen D.
      citationCount: 0
      date: '2024-01-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'SCAN: Spatiotemporal Cloud Atlas for Neural cells'
    note: null
    pmcid: PMC10767991
    pmid: '37930842'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Neurobiology
    uri: http://edamontology.org/topic_3304
  - term: Neurology
    uri: http://edamontology.org/topic_3334
  - term: Pathology
    uri: http://edamontology.org/topic_0634
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-30T08:41:07.253380Z'
  biotoolsCURIE: biotools:lncpcd
  biotoolsID: lncpcd
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: ningsw@ems.hrbmu.edu.cn
    fundrefid: null
    gridid: null
    name: Shangwei Ning
    note: null
    orcidid: https://orcid.org/0000-0003-4079-8945
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: wangjian_427@163.com
    fundrefid: null
    gridid: null
    name: Lihua Wang
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: wanglh211@163.com
    fundrefid: null
    gridid: null
    name: Jianjian Wang
    note: null
    orcidid: https://orcid.org/0000-0001-5568-4612
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Manually curated database of experimentally supported associations
    between lncRNA-mediated programmed cell death and diseases.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Quantification
      uri: http://edamontology.org/operation_3799
    output: []
  homepage: http://spare4.hospital.studio:9000/lncPCD/Home.jsp
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-30T08:41:07.255470Z'
  license: null
  link: []
  maturity: null
  name: LncPCD
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/DATABASE/BAAD087
    metadata:
      abstract: 'Programmed cell death (PCD) refers to controlled cell death that
        is conducted to keep the internal environment stable. Long noncoding RNAs
        (lncRNAs) participate in the progression of PCD in a variety of diseases.
        However, no specialized online repository is available to collect and store
        the associations between lncRNA-mediated PCD and diseases. Here, we developed
        LncPCD, a comprehensive database that provides information on experimentally
        supported associations of lncRNA-mediated PCD with diseases. The current version
        of LncPCD documents 6666 associations between five common types of PCD (apoptosis,
        autophagy, ferroptosis, necroptosis and pyroptosis) and 1222 lncRNAs in 331
        diseases.We also manually curated a wealth of information: (1) 7 important
        lncRNA regulatory mechanisms, (2) 310 PCD-associated cell types in three species,
        (3) detailed information on lncRNA subcellular locations and (4) clinical
        applications for lncRNA-mediated PCD in diseases. Additionally, 10 single-cell
        sequencing datasets were integrated into LncPCD to characterize the dynamics
        of lncRNAs in diseases. Overall, LncPCD is an extremely useful resource for
        understanding the functions and mechanisms of lncRNA-mediated PCD in diseases.'
      authors:
      - name: He N.
      - name: Li D.
      - name: Xu F.
      - name: Jin J.
      - name: Li L.
      - name: Tian L.
      - name: Chen B.
      - name: Li X.
      - name: Ning S.
      - name: Wang L.
      - name: Wang J.
      citationCount: 0
      date: '2023-01-01T00:00:00Z'
      journal: Database
      title: 'LncPCD: a manually curated database of experimentally supported associations
        between lncRNA-mediated programmed cell death and diseases'
    note: null
    pmcid: PMC10681436
    pmid: '38011720'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Functional, regulatory and non-coding RNA
    uri: http://edamontology.org/topic_0659
  - term: Pathology
    uri: http://edamontology.org/topic_0634
  - term: Cell biology
    uri: http://edamontology.org/topic_2229
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  - term: Cardiology
    uri: http://edamontology.org/topic_3335
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-04-30T08:15:41.767832Z'
  biotoolsCURIE: biotools:atlas_db
  biotoolsID: atlas_db
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: jean-christophe.gelly@u-paris.fr
    fundrefid: null
    gridid: null
    name: Jean-Christophe Gelly
    note: null
    orcidid: https://orcid.org/0000-0001-5138-361X
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: tatiana.galochkina@u-paris.fr
    fundrefid: null
    gridid: null
    name: Tatiana Galochkina
    note: null
    orcidid: https://orcid.org/0000-0002-3608-5208
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: ATLAS gathers standardized molecular dynamics simulations of protein
    structures accompanied by their analysis in the form of interactive diagrams and
    trajectory visualisation.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Molecular dynamics
      uri: http://edamontology.org/operation_2476
    - term: Simulation analysis
      uri: http://edamontology.org/operation_0244
    - term: Trajectory visualization
      uri: http://edamontology.org/operation_3890
    - term: Protein-protein docking
      uri: http://edamontology.org/operation_3899
    - term: Protein geometry calculation
      uri: http://edamontology.org/operation_0249
    output: []
  homepage: https://www.dsimb.inserm.fr/ATLAS
  homepage_status: 0
  language: []
  lastUpdate: '2024-04-30T08:15:41.770796Z'
  license: null
  link: []
  maturity: null
  name: ATLAS
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/NAR/GKAD1084
    metadata:
      abstract: Dynamical behaviour is one of the most crucial protein characteristics.
        Despite theãdvances in the field of protein str uct ure resolutionãnd predic-
        tion,ãnalysisãnd prediction of protein dynamic properties remainsã major challenge,
        mostly due to the lowãccessibility of dataãnd its diversityãnd heterogeneity.
        Toãddress this issue, we present ATLA S ,ã database of standardisedãll-atom
        molecular dynamics simulations,ãccompanied by theirãnalysis in the form of
        interactive diagramsãnd trajectory visualisation. ATLAS offersã large-scale
        viewãnd valuable insights on protein dynamics forã largeãnd representative
        set of proteins, by combining data obtained through molecular dynamics simulations
        with information e xtracted from e xperimental str uct ures. Users can easilyãnalyse
        dynamic properties of functional protein regions, suchãs domain limits (hinge
        positions)ãnd residues in v olv ed in interaction with other biological molecules.
        Additionally, the database enables exploration of proteins with uncommon dynamic
        properties conditioned by their environment suchãs chameleon subsequencesãnd
        Dual Personality Fragments. The ATLAS database is freelyã vãilableãt https://
        www.dsimb.inserm.fr/ ATLAS .
      authors:
      - name: Meersche Y.V.
      - name: Cretin G.
      - name: Gheeraert A.
      - name: Gelly J.-C.
      - name: Galochkina T.
      citationCount: 3
      date: '2024-01-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'ATLA S: prot ein flexibility description fromãtomistic molecular dynamics
        simulations'
    note: null
    pmcid: PMC10767941
    pmid: '37986215'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Molecular dynamics
    uri: http://edamontology.org/topic_0176
  - term: Protein folds and structural domains
    uri: http://edamontology.org/topic_0736
  - term: Protein interactions
    uri: http://edamontology.org/topic_0128
  - term: Protein folding, stability and design
    uri: http://edamontology.org/topic_0130
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  validated: 0
  version: []
next: ?page=2
previous: null
