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http://skatebase.org/

Portal supporting the North East Bioinformatics Collaborative''s project to sequence the genome of the Little Skate. Provided is a clearinghouse for Little Skate Genome Project and other publicly available Skate and Ray (Batoidea) genome data, and tools for data visualization and analysis. Little Skate Genome Project The little skate (Leucoraja erinacea) is a chondrichthyan (cartilaginous) fish native to the east coast of North America. Elasmobranchs (Skates, Rays, and Sharks) exhibit many fundamental vertebrate characteristics, including a neural crest, jaws and teeth, an adaptive immune system, and a pressurized circulatory system. These characteristics have been exploited to promote understanding about human physiology, immunology, stem cell biology, toxicology, neurobiology and regeneration. The development of standardized experimental protocols in elasmobranchs such as L. erinacea and the spiny dogfish shark (Squalus acanthias) has further positioned these organisms as important biomedical and developmental models. Despite this distinction, the only reported chondrichthyan genome is the low coverage (1.4x) draft genome of the elephant shark (Callorhinchus milii). To close the evolutionary gaps in available elasmobranch genome sequence data, and generate critical genomic resources for future biomedical study, the genome of L. erinacea is being sequenced by the North East Bioinformatics Collaborative (NEBC). As close evolutionary relatives, the little skate sequence will facilitate studies that employ dogfish shark and other elasmobranchs as model organisms. Skate tools include the SkateBLAST and the Skate Genome Browsers: Little Skate Mitochondrion, Thorny Skate Mitochondrion, and Ocellate Spot Skate Mitochondrion.

Proper citation: SkateBase (RRID:SCR_005302) Copy   

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http://www.topsan.org/

Collect, share, and distribute information about protein three-dimensional structures. It serves as a portal for the scientific community to learn about protein structures solved by SG centers, and also to contribute their expertise in annotating protein function. The premise of the TOPSAN project is that, no matter how much any individual knows about a particular protein, there are other members of the scientific community who know more about certain aspects of the same protein, and that the collective analyses from experts will be far more informative than any local group, let alone individual, could contribute. They believe that, if the members of the biological community are given the opportunity, authorship incentives, and an easy way to contribute their knowledge to the structure annotation, they would do so. Therefore, borrowing elements from successful, distributed, collaborative projects, such as Wikipedia (the free encyclopedia anyone can edit) and from other open source software development projects, TOPSAN will be a broad, collaborative effort to annotate protein structures, initially, those determined at the JCSG. They believe that the annotation of proteins solved by structural genomics consortia offers a unique opportunity to challenge the extant paradigm of how biological data is collected and distributed, and to connect structural genomics and structural biology to the entire biological research community. TOPSAN is designed to be scalable, modular and extensible. Furthermore, it is intended to be immediately useful in a simplistic way and will accommodate incremental improvements to functionality as usage becomes more sophisticated. Their annotation pages will offer the end user a combination of automatically generated as well as expert-curated annotations of protein structures. They will use available technology to increase the speed and granularity of the exchange of scientific ideas, and use incentive mechanisms that will encourage collaborative participation.

Proper citation: TOPSAN (RRID:SCR_005758) Copy   

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http://publications.nigms.nih.gov/multimedia/searchresults.asp?search=All

As part of its multimedia outreach, the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health -- the United States'' medical research agency -- offers audio and video podcasts and other multimedia resources that explore the exciting world of basic biomedical research.

Proper citation: NIGMS Multimedia (RRID:SCR_005712) Copy   

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http://publications.nigms.nih.gov/chemhealth/

Visit ChemHealthWeb for research highlights, chemist profiles, games and videos and other Web extras. The NIGMS Chemistry of Health booklet describes basic chemistry and biochemistry research that spurs a better understanding of human health.

Proper citation: ChemHealthWeb (RRID:SCR_005851) Copy   

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http://polbase.neb.com/

Repository of biochemical, genetic, and structural information about DNA Polymerases. Polbase is designed to compile detailed results of polymerase experimentation, presenting them in a dynamic view to inform further research. After validation, results from references are displayed in context with relevant experimental details and are always traceable to their source publication. Polbase is connected to other resources, including PubMed, UniProt and the RCSB Protein Data Bank, to provide multi-faceted views of polymerase knowledge. In addition to a simple web interface, Polbase data is exposed for custom analysis by external software.

Proper citation: Polbase (RRID:SCR_006107) Copy   

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https://simtk.org

A National NIH Center for Biomedical Computing that focuses on physics-based simulation of biological structures and provides open access to high quality simulation tools, accurate models and the people behind them. It serves as a repository for models that are published (as well as the associated code) to create a living archive of simulation scholarship. Simtk.org is organized into projects. A project represents a research endeavor, a software package or a collection of documents and publications. Includes sharing of image files, media, references to publications and manuscripts, as well as executables and applications for download and source code. Simulation tools are free to download and space is available for developers to manage, share and disseminate code.

Proper citation: Simtk.org (RRID:SCR_002680) Copy   

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http://bioportal.bioontology.org/

Open repository of biomedical ontologies that provides access via Web browsers and Web services to ontologies. It supports ontologies in OBO format, OWL, RDF, Rich Release Format (RRF), Protege frames, and LexGrid XML. Functionality includes the ability to browse, search and visualize ontologies as well as to comment on, and create mappings for ontologies. Any registered user can submit an ontology. The NCBO Annotator and NCBO Resource Index can also be accessed via BioPortal. Additional features: * Add Reviews: rate the ontology according to several criteria and describe your experience using the ontology. * Add Mappings: submit point-to-point mappings or upload bulk mappings created with external tools. Notification of new Mappings is RSS-enabled and Mappings can be browsed via BioPortal and accessed via Web services. * NCBO Annotator: Tool that tags free text with ontology terms. NCBO uses the Annotator to generate ontology annotations, creating an ontology index of these resources accessible via the NCBO Resource Index. The Annotator can be accessed through BioPortal or directly as a Web service. The annotation workflow is based on syntactic concept recognition (using the preferred name and synonyms for terms) and on a set of semantic expansion algorithms that leverage the ontology structure (e.g., is_a relations). * NCBO Resource Index: The NCBO Resource Index is a system for ontology based annotation and indexing of biomedical data; the key functionality of this system is to enable users to locate biomedical data linked via ontology terms. A set of annotations is generated automatically, using the NCBO Annotator, and presented in BioPortal. This service uses a concept recognizer (developed by the National Center for Integrative Biomedical Informatics, University of Michigan) to produce a set of annotations and expand them using ontology is_a relations. * Web services: Documentation on all Web services and example code is available at: BioPortal Web services.

Proper citation: BioPortal (RRID:SCR_002713) Copy   

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https://simtk.org/home/foldvillin

An archive of hundreds of all-atom, explicit solvent molecular dynamics simulations that were performed on a set of nine unfolded conformations of a variant of the villin headpiece subdomain (HP-35 NleNle). It includes scripts for accessing the archive of villin trajectories as well as a VMD plug-in for viewing the trajectories. In addition, all starting structures used in the trajectories are also provided. The simulations were generated using a distributed computing method utilizing the symmetric multiprocessing paradigm for individual nodes of the Folding_at_home distributed computing network. The villin trajectories in the archive are divided into two projects: PROJ3036 and PROJ3037. PROJ3036 contains trajectories starting from nine non-folded configurations. PROJ3037 contains trajectories starting from the native (folded) state. Runs 0 through 8 (in PROJ3036) correspond to starting configurations 0 through 8 discussed in the paper in J. Mol. Biol. (2007) 374(3):806-816 (see the publications tab for a full reference), whereas RUN9 uses the same starting configuration as RUN8. Each run contains 100 trajectories (named clone 0-99), each with the same starting configuration but different random velocities. Trajectories vary in their length of time and are subdivided into frames, also known as a generation. Each frame contains around 400 configurational snapshots, or timepoints, of the trajectory, with the last configurational snapshot of frame i corresponding to the first configurational snapshot of generation i+1. The goal is to allow researchers to analyze and benefit from the many trajectories produced through the simulations.

Proper citation: Molecular Simulation Trajectories Archive of a Villin Variant (RRID:SCR_002704) Copy   

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http://pir.georgetown.edu/pro/

An ontological representation of protein-related entities, explicitly defining them and showing the relationships between them. Each PRO term represents a distinct class of entities (including specific modified forms, orthologous isoforms, and protein complexes) ranging from the taxon-neutral to the taxon-specific. PRO encompasses three sub-ontologies: proteins based on evolutionary relatedness (ProEvo); protein forms produced from a given gene locus (ProForm); and protein-containing complexes (ProComp).

Proper citation: PRO (RRID:SCR_002902) Copy   

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http://cytoscape.org

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

Proper citation: Cytoscape (RRID:SCR_003032) Copy   

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http://www.bioperl.org

BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: BioPerl (RRID:SCR_002989) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry

http://bio3d.colorado.edu/imod

A free, cross-platform set of image processing, modeling and display programs used for tomographic reconstruction and for 3D reconstruction of EM serial sections and optical sections. The package contains tools for assembling and aligning data within multiple types and sizes of image stacks, viewing 3-D data from any orientation, and modeling and display of the image files. IMOD 4.1.8 Is Now Available for Linux, Windows, and Mac OS X

Proper citation: IMOD (RRID:SCR_003297) Copy   

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http://mods.rna.albany.edu

The RNA modification database provides a comprehensive listing of posttranscriptionally modified nucleosides from RNA. Information provided for each nucleoside includes: the type of RNA in which it occurs and phylogenetic distribution; common chemical name and symbol; Chemical Abstracts registry number and index name; chemical structure; initial literature citations for structural characterization or occurrence, and for chemical synthesis. Both the structural diversity and extent of posttranscriptional modification in RNA is remarkable, with 107 different nucleosides presently known in all types of RNA. The discovery of new modified nucleosides as well as increasing knowledge of the array of functional roles of modification, based largely on extensive studies of tRNA, mandates a need for a comprehensive database of RNA nucleosides. The RNA Modification Database is maintained as an extension of the initial version published in mid-1994. The database consists of all RNA-derived ribonucleosides of known structure, including those from established sequence positions, as well as those detected or characterized from hydrolysates of RNA. The information provided permits access to the modified nucleoside literature through provision of both computer-searchable Chemical Abstracts registry numbers and key literature citations. This database also provides an historical record of the initial reports of occurrence, characterization and chemical synthesis of modified nucleosides from RNA. It is our judgement that the total number of RNA nucleosides listed, and the chemical structures reported, are very accurate. However, the distributions listed are in some cases a matter of concern, due primarily to the possibility of inhomogeneity of the RNA isolate and the use of methods of nucleoside identification that are not sufficiently rigorous. Reinvestigation of some of the unusual or single-report source distributions is warranted, and will likely lead to future refinements in the listings. The authors invite comments concerning new entries, errors or omissions and on the format presently used for electronic access to the database.

Proper citation: RNA Modification Database (RRID:SCR_003535) Copy   

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http://megasoftware.net/

Software integrated tool for conducting automatic and manual sequence alignment, inferring phylogenetic trees, mining web based databases, estimating rates of molecular evolution, and testing evolutionary hypotheses. Used for comparative analysis of DNA and protein sequences to infer molecular evolutionary patterns of genes, genomes, and species over time. MEGA version 4 expands on existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. MEGA version 6 enables inference of timetrees, as it implements RelTime method for estimating divergence times for all branching points in phylogeny.

Proper citation: MEGA (RRID:SCR_000667) Copy   

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http://sfld.rbvi.ucsf.edu/

A database of hierarchical classification of enzymes that relates specific sequence-structure features to specific chemical capabilities. The SFLD classifies evolutionarily related enzymes according to shared chemical functions and maps these shared functions to conserved active site features. The classification is hierarchical, where broader levels encompass more distantly related proteins with fewer shared features. It thus serves as the analysis and archive site for superfamilies targeted by the Enzyme Function Initiative, and is developed by the Babbitt Laboratory in collaboration with the UCSF Resource for Biocomputing, Visualization, and Informatics. The resource also provides a collection of tools and data for investigating sequence-structure-function relationships and hypothesizing function.

Proper citation: Structure-function linkage database (RRID:SCR_001375) Copy   

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https://github.com/mwang87/MassQueryLanguage

Software application for universal searching of Mass Spectrometry data. Open source MS query language for flexible and mass spectrometer manufacturer-independent mining of MS data. Implements common MS terminology to build consensus vocabulary to search for MS patterns in single mass spectrometry run. Enables set of mass spectrometry patterns to be queried directly from raw data.

Proper citation: MassQL (RRID:SCR_025106) Copy   

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https://github.com/bmvdgeijn/WASP/

Software allele-specific pipeline for unbiased read mapping and molecular QTL discovery. Allele-specific software for robust molecular quantitative trait locus discovery.

Proper citation: WASP (RRID:SCR_025497) Copy   

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http://alfred.med.yale.edu

A public curated compilation of allele frequency data on anthropologically defined human population samples linked to the molecular genetics-human genome databases. Only data on well defined population samples that are large enough to yield reasonably accurate frequencies and for polymorphisms sufficiently defined to be replicable can be included in ALFRED. Researchers wishing to have their data entered into ALFRED should contact them. Initially, ALFRED contained primarily data generated in the laboratories of K.K. and J.R. Kidd in the Department of Genetics at Yale, including extensive unpublished data. Data from the published literature are being entered into ALFRED in a systematic way, with a focus on polymorphisms studied in many different populations. ALFRED is distinct from such databases as dbSNP, which catalogs sequence variation. ALFRED's focus is on allele frequencies in diverse anthropologically defined populations. It is not a compendium of human DNA polymorphisms but of frequencies of selected polymorphisms with an emphasis on those that have been studied in multiple populations. All of the data in ALFRED are considered to be in the public domain and available for use in research and teaching. ALFRED provides easy searching options including versatile "Keyword search" and also has numerous summary tables providing quick overviews of contents by chromosome, population, average heterozygosity, Fst and others, all available under various tabs from the ALFRED homepage.

Proper citation: ALFRED (RRID:SCR_001730) Copy   

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https://www.genome.wisc.edu/tools/asap.htm

Database and web interface developed to store, update and distribute genome sequence data and gene expression data. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments. Use of some of this preliminary data is conditional, and it is the users responsibility to read the data release policy and to verify that any use of specific data obtained through ASAP is consistent with this policy. There are four main routes to viewing the information in ASAP: # a summary page, # a form to query the genome annotations, # a form to query strain collections, and # a form to query the experimental data. Navigational buttons appear on every page allowing users to jump to any of these four points., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ASAP (RRID:SCR_001849) Copy   

•   Source: SciCrunch Registry