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http://www.genetools.us

Web-service providing access to database that brings together information from broad range of resources. Web application for functional annotation and statistical hypothesis testing. Provides tools for analysis of genomic and microarray data. Collection of tools include Bibliographic Information,Databases,Gene Annotation,Gene Regulation, Microarray,Proteins,Sequence Manipulation - Nucleic Acids,Sequence Manipulation - Protein, Systems Biology.

Proper citation: GeneTools (RRID:SCR_005663) Copy   

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http://g2im.u-clermont1.fr/serimour/goarrays.html

GOArray is a Perl program which inputs a lists of genes annotated as of interest (GOI) or not, and determines if any associated GO terms have an overrepresentation of GOI. A permutation test is optionally used to assess confidence in the results. Output includes multiple visualizations and supplementary information and, for future reference, a summary of the statistical methods used. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOArray (RRID:SCR_005785) Copy   

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http://www.webarraydb.org/webarray/index.html

An open source integrated microarray database and analysis suite that features convenient uploading of data for storage in a MIAME (Minimal Information about a Microarray Experiment) compliant fashion. It allows data to be mined with a large variety of R-based tools, including data analysis across multiple platforms. Different methods for probe alignment, normalization and statistical analysis are included to account for systematic bias. Student's t-test, moderated t-tests, non-parametric tests and analysis of variance or covariance (ANOVA/ANCOVA) are among the choices of algorithms for differential analysis of data. Users also have the flexibility to define new factors and create new analysis models to fit complex experimental designs. All data can be queried or browsed through a web browser. The computations can be performed in parallel on symmetric multiprocessing (SMP) systems or Linux clusters.

Proper citation: WebArrayDB (RRID:SCR_005577) Copy   

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http://biostat.mc.vanderbilt.edu/wiki/Main/ASAP

Software developed to provide a framework for building and executing a pipeline to preprocess next generation sequence data and variant calls.

Proper citation: Advanced Sequence Automated Pipeline (RRID:SCR_005578) Copy   

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http://fields.scripps.edu/

Scientists at the Yates Lab at The Scripps Research Institute (TSRI) rely on information yielded by tandem mass spectrometry to identify proteins from complex mixtures. Using this powerful technique, researchers draw upon a cross section of fields to increase the scope, sensitivity, and throughput of technologies for practical proteomics. Biologists provide the questions that drive our research. By identifying complexes that are poorly understood or organism-wide issues requiring further exploration, we gain a theoretical understanding of issues that are tractable only through proteomic strategies. Analytical chemists and biochemists improve our tools for revealing the proteins present in biological samples. Targets for optimization include the isolations used to obtain proteins, the steps to generate peptides from these proteins, and the separation of peptides en route to the mass spectrometer. Chemistry is vital to increasing power of proteomic technology. Computer science yields tools on two scales. First, the sequence corresponding to each peptide''s tandem mass spectrum must be identified. Once those identifications have been completed, additional tools are needed to summarize and organize these identifications.

Proper citation: TSRI-Yates Lab (RRID:SCR_005699) Copy   

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http://compbio.clemson.edu/index.html

The research in the lab focuses on computational modeling of biological macromolecules and their assemblages and predicting biophysical quantities associated with them. The main focus of the lab is the development and maintenance of the popular software package DelPhi, which calculates electrostatic potential and energies of systems comprised of biological macromolecules. In addition, we are interested in modeling disease-causing missense mutations, pKa''s of amino acids and nucleic groups and pH-dependence of stability and binding. In parallel with in silico modeling, the lab actively collaborates with experimetalists to better understand molecular mechanisms of biological reactions and interactions. The combination of the methods of Computational Biophysics and Bioinformatics with experimental results is an essential approach utilized in our research.

Proper citation: Clemson Computational Biophysics and Bioinformatics (RRID:SCR_005696) Copy   

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http://cs.nyu.edu/~bingsun/

NYU Bioinformatics group applies algorithmic, statistical, and mathematical techniques to solve problems of interest to biology, biotechnology and biomedicine. The group focuses on bioinformatics, computational biology and systems biology with many active projects in areas ranging from single molecules to entire populations: Analysis of Single-Molecule/Single-Cell Data, SPM-based Transcriptomic Profiling, Whole-Genome Haplotype Sequencing using SMASH (Single Molecule Approaches to Haplotype Sequencing), SUTTA (Scoring and Unfolding Trimmed Tree Assembler) assembly algorithm, Analysis of Spatio-Temporal Data, Model Checking and Model Building for Systems Biology, GOALIE-based Phenomenological Models and their Verification, Causality Analysis, Causal Models and their Verification, Analysis of EHR (Electronic Health Record Data) and Disease Models (e.g., Chronic Fatigue Syndrome, Congestive Heart Failure, Deep Vein Thrombosis, etc.), Models of Cancer, Applications to Pancreatic Cancer, Polymorphisms and Biomarkers, Strategies for Group Testing, Epidemiological and Bio-Warfare Models, Planning with Large Agent Networks against Catastrophes (PLAN C), Population Genomics, and Genome Wide Association Studies (GWAS). The group has received its funding from Air Force, Army, CCPR, DARPA, NIH, NIST, NSF, NYSTAR, etc. and various other governmental and commercial entities. Currently, the group is part of an NSF funded Expedition in Computing project (CMACS: Center for Modeling and Analysis of Complex Systems at CMU) and collaborates widely, both nationally and internationally. The group is highly multi-disciplinary, attracting researchers and students from mathematics, statistics, computer science, and biology who team up with physicians, physicists, and chemists as well as professionals in their own disciplines. This group is led by Prof. Bud Mishra, a professor of computer science and mathematics at NYU''s Courant Institute of Mathematical Sciences.

Proper citation: NYU Bioinformatics Group (RRID:SCR_005697) Copy   

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http://rafalab.jhsph.edu/bsmooth/

A pipeline for analyzing whole genome bisulfite sequencing (WGBS) data.

Proper citation: BSmooth (RRID:SCR_005693) Copy   

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http://manatee.sourceforge.net/

Manatee is a web-based gene evaluation and genome annotation tool; Manatee can store and view annotation for prokaryotic and eukaryotic genomes. The Manatee interface allows biologists to quickly identify genes and make high quality functional assignments, such as GO classifications, using search data, paralogous families, and annotation suggestions generated from automated analysis. Manatee can be downloaded and installed to run under the CGI area of a web server, such as Apache. Platform: Online tool, Linux compatible, Solaris

Proper citation: Manatee (RRID:SCR_005685) Copy   

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http://genenet2.uthsc.edu/geneinfoviz/search.php

GeneInfoViz is a web based tool for batch retrieval of gene function information, visualization of GO structure and construction of gene relation networks. It takes a input list of genes in the form of LocusLink ID, UniGeneID, gene symbol, or accession number and returns their functional genomic information. Based on the GO annotations of the given genes, GeneInfoViz allows users to visualize these genes in the DAG structure of GO, and construct a gene relation network at a selected level of the DAG. Platform: Online tool

Proper citation: GeneInfoViz (RRID:SCR_005680) Copy   

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https://datadryad.org

International, curated, digital repository that makes the data underlying scientific publications discoverable, freely reusable, and citable. Particularly data for which no specialized repository exists. Provides the infrastructure for, and promotes the re-use of, data underlying the scholarly literature. Governed by a nonprofit membership organization. Membership is open to any stakeholder organization, including but not limited to journals, scientific societies, publishers, research institutions, libraries, and funding organizations. Most data are associated with peer-reviewed articles, although data associated with non-peer reviewed publications from reputable academic sources, such as dissertations, are also accepted. Used to validate published findings, explore new analysis methodologies, repurpose data for research questions unanticipated by the original authors, and perform synthetic studies.UC system is member organization of Dryad general subject data repository.

Proper citation: Dryad Digital Repository (RRID:SCR_005910) Copy   

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http://sourceforge.net/projects/cancergrid-tma/

A web-based application for the management and storage of tissue microarray (TMA) images and the associated metadata. The application enables the user to navigate a grid of TMA core images within a slide, zoom and pan around an image, and enter a score constrained to a specific scoring system. The submitted scores are scored in the eXist open source database, in an XML format, which is compatible with existing TMA standards, and thus allow the data to be archived and re-used in future analysis.

Proper citation: cancergrid-tma (RRID:SCR_005595) Copy   

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http://www.learnaboutsma.org/

Learn About SMA is a resource for spinal muscular atrophy (SMA) patients, families and researchers. The site includes stories of living with SMA and recent advances in the understanding and potential treatment of SMA. Learn About SMA is divided into five sections with video interviews, animations, and narrative. What is SMA? includes interviews with doctors and patients, plus an animation explaining the cause, inheritance and diagnosis of SMA. SMA Science provides an introduction to the genes and mechanisms involved with SMA, including 2-D and 3-D animations and interviews with Nobel Laureates. * In SMA Therapies doctors discuss current and potential treatments for SMA and a father describes the daily routine of physical therapies for his daughter, who has SMA. Antisense Therapy for SMA includes videos and animations to explain antisense therapy for SMA. In Living with SMA four SMA families describe daily routines, disease progression, children''s understanding of SMA, and grieving.

Proper citation: Learn about SMA website (RRID:SCR_005592) Copy   

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http://sybil.sourceforge.net/

A web-based software package for comparative genomics.

Proper citation: Sybil (RRID:SCR_005593) Copy   

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http://apps.cytoscape.org/apps/jepetto

A Cytoscape plugin that performs integrated gene set analysis using information from interaction, pathways and processes databases. The plugin integrates information from three separate web servers specializing in enrichment analysis, pathways expansion and topological matching. It uses the TopoGSA server to identify topological analogies between the user selected gene set and the known pathways and processes. TopoGSA finds the most similar biological mechanism using the topological features of the interaction network of a user selected gene set. It is also able to suggest genes related to the query gene set using two pathway analysis servers EnrichNet and PathExpand. Both these servers are using a different topological matching algorithms that extends the query gene set with genes from the pathway databases. This integration substantially simplifies the analysis of user gene sets and the interpretation of the results.

Proper citation: JEPETTO (RRID:SCR_005909) Copy   

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http://www.opencalais.com/

Service and open API to tag the people, places, facts and events in your content. You hand the Web Service unstructured text (like news articles, blog postings, your term paper, etc.) and it returns semantic metadata in RDF format. Using natural language processing and machine learning techniques, the Calais Web Service examines your text and locates the entities, facts, and events. Calais then processes the entities, facts and events extracted from the text and returns them to the caller in RDF format. * Calais Tagaroo: If you are on WordPress, this plug-in automatically tags content as you type. It can also fetch images from Flickr and videos from Google Video. * Calais Marmoset: To manipulate your search results appearance in Google and Yahoo!, which is simple javacode you embed in your site pages. It will collect the metadata from your page (in the form of RDFa) and hand it over to Google Rich Snippets> and Yahoo! Search Monkey so that you can customize the way your search results appear. * Semantic Proxy: If you want to extract metadata from Web pages using URLs * Calais Collection: For the open source platform Drupal, you can find a complete Calais Collection of modules for easy integration. * OpenPublish: for building a new site from the ground up, this free Content Management System is based on Drupal. OpenPublish bakes-in OpenCalais from the ground up to semantify your site and automate the creation of ''related reading'' widgets, ''topic hubs'' and more.

Proper citation: OpenCalais (RRID:SCR_005906) Copy   

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http://europepmc.org/

Free access to biomedical literature resources including all of PubMed and PubMed Central, agricultural abstracts (from AGRICOLA), over 4 million international life science patents abstracts, National Health Service (NHS) clinical guidelines, and is supplemented with Chinese Biological Abstracts and the Citeseer database. As well as powerful search of abstracts and full text articles, it also includes: * article citations and sort order based on citation count * data citations mined from full text articles * links to and from related databases and institutional repositories * a tool to create bibliographies linked to your ORCID * named entity recognition of keywords and text-mining-based applications showcased in Europe PMC Labs * Tools for recipients of grants from one of the Europe PMC funders to deposit full-text manuscripts and link them to those specific grants. * Web services for programmatic access to all the above bibliographic information and 50,000 grants. * Search by publication date, relevance, or the number of times an article has been cited. * Links to public databases such as UniProt, Protein Data Bank (PDBe), and the European Nucleotide Archive (ENA) are provided. * Through textmining technologies, you can highlight and browse keywords such as gene names, organisms and diseases. * Search 40,000 biomedical research grants awarded to the 18,000 PIs supported by the Europe PMC funders. * Roadtest new tools based on Europe PMC content in Europe PMC labs. * In Europe PMC plus, PIs supported by the Europe PMC funders can link grants to publication information, view article citation and download statistics, and submit manuscripts.

Proper citation: Europe PubMed Central (RRID:SCR_005901) Copy   

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http://www.pensoft.net/index.php

Publisher that specializes in academic and professional book and journal publishing, mostly in the field of biodiversity science and natural history. They are academic publishers based in Eastern Europe with more than 600 books and e-books published so far. They largely perform their activities in English, with only a minor fraction of publications being in French, German, Russian and Bulgarian. Pensoft is also involved as a publisher in several European Union Fp5, FP6 and FP7 projects where they have specialized in dissemination, communication and publishing; as well as in creating and maintaining websites and Internal Communication Platforms (ICP), designing of logos, flyers, leaflets and posters. Open-access journals include ZooKeys, BioRisk, and PhytoKeys. ZooKeys is a journal in biodiversity science and has implemented several innovations in digital publishing and dissemination including developing and implementing an XML-based submission, editorial, publication and dissemination workflow. The TRIADA platform, for publishing, disseminating and marketing of printed books, e-books and open access journals, provides a linked environment for content, authors, reviewers, editors and customers through four independent classifications (taxonomic, subject, geographical, and geological time scale) as well through tagging and semantic mark-up. TRIADA uses a one-time registration process which allows users to submit, review or edit manuscripts, to subscribe for E-mail and RSS alerts, and to purchase Pensoft''s products. Web services: Metadata and journal content can be harvested.

Proper citation: Pensoft (RRID:SCR_005903) Copy   

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http://infocenter.nimh.nih.gov/il/public_il/

Database of photographs and illustrations of general biomedical research and research tools, mental health specific research, and treatment related images that are available, copyright free, to the public at no cost. Many images are available in low, medium, and high resolutions. Formats include jpg, gif, and png. NIMH images may not be used to state or imply the endorsement by NIMH or by an NIMH employee of a commercial product, service, or activity, or use in any other manner that might mislead. No fee is charged for using the images. However, credit must be given to the National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services unless otherwise instructed to give credit to the photographer or other source., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NIMH Image Library (RRID:SCR_005588) Copy   

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https://github.com/transmart

tranSMART is a knowledge management platform that enables scientists to develop and refine research hypotheses by investigating correlations between genetic and phenotypic data, and assessing their analytical results in the context of published literature and other work. tranSMART is licensed through GPL 3. The integration, normalization, and alignment of data in tranSMART permits users to explore data very efficiently to formulate new research strategies. Some of tranSMART''s specific applications include: * Revalidating previous hypotheses * Testing and refining novel hypotheses * Conducting cross-study meta-analysis * Searching across multiple data sources to find associations of concepts, such as a gene''s involvement in biological processes or experimental results * Comparing biological processes and pathways among multiple data sets from related diseases or even across multiple therapeutic areas Data Repository The tranSMART Data Repository combines a data warehouse with access to federated sources of open and commercial databases. tranSMART accommodates: * Phenotypic data, such as demographics, clinical observations, clinical trial outcomes, and adverse events * High content biomarker data, such as gene expression, genotyping, pharmacokinetic and pharmaco-dynamics markers, metabolomics data, and proteomics data * Unstructured text-data, such as published journal articles, conference abstracts and proceedings, and internal studies and white papers * Reference data from sources such as MeSH, UMLS, Entrez, GeneGo, Ingenuity, etc. * Metadata providing context about datasets, allowing users to assess the relevance of results delivered by tranSMART Data in tranSMART is aligned to allow identification and analysis of associations between phenotypic and biomarker data, and it is normalized to conform with CDISC and other standards to facilitate search and analysis across different data sources. tranSMART also enables investigators to search published literature and other text sources to evaluate their analysis in the context of the broader universe of reported research. External data can also be integrated into the tranSMART data repository, either from open data projects like GEO, EBI Array Express, GCOD, or GO, or from commercially available data sources. Making data accessible in tranSMART enables organizations to leverage investments in manual curation, development costs of automated ETL tools, or commercial subscription fees across multiple research groups. Dataset Explorer tranSMART''s Dataset Explorer provides flexible, powerful search and analysis capabilities. The core of the Dataset Explorer integrates and extends the open source i2b2 application, Lucene text indexing, and GenePattern analytical tools. Connections to other open source and commercial analytical tools such as Galaxy, Integrative Genomics Viewer, Plink, Pathway Studio, GeneGo, Spotfire, R, and SAS can be established to expand tranSMART''s capabilities. tranSMART''s design allows organizations flexibility in selecting analytical tools accessible through the Dataset Explorer, and provides file export capabilities to enable researchers to use tools not accessible in the tranSMART portal.

Proper citation: tranSMART (RRID:SCR_005586) Copy   

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