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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
System that classifies genes by their functions, using published scientific experimental evidence and evolutionary relationships to predict function even in absence of direct experimental evidence. Orthologs view is curated orthology relationships between genes for human, mouse, rat, fish, worm, and fly., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: PANTHER (RRID:SCR_004869) Copy
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
http://ccb.jhu.edu/software/FLASH/
Open source software tool to merge paired-end reads from next-generation sequencing experiments. Designed to merge pairs of reads when original DNA fragments are shorter than twice length of reads. Can improve genome assemblies and transcriptome assembly by merging RNA-seq data.
Proper citation: FLASH (RRID:SCR_005531) Copy
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
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
Web server for flexible protein structure comparison. Structure alignment is formulated as the aligned fragment pairs chaining process allowing at most t twists, and the flexible structure alignment is transformed into a rigid structure alignment when t is forced to be 0., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: FATCAT (RRID:SCR_014631) Copy
http://bowtie-bio.sourceforge.net/bowtie2/index.shtml
Ultrafast and memory efficient tool for aligning sequencing reads to long reference sequences. Supports gapped, local, and paired end alignment modes. More suited to finding longer, gapped alignments in comparison with original Bowtie method.
Proper citation: Bowtie 2 (RRID:SCR_016368) Copy
Image analysis software that learns modular models of things such as cell shape, nuclear shape, vesicular organelle distribution and microtubule distribution directly from 2D or 3D images and can produce specific instances of cell geometries without the need to create them by hand or to segment microscope images. These geometries can be combined with biochemical models to perform spatially realistic cell simulations if used in conjunction with MCell.
Proper citation: CellOrganizer (RRID:SCR_014828) Copy
http://www.ccg.unam.mx/tfmodeller
Web application that scans a library of protein-DNA complexes and builds comparative models of proteins bound to DNA. Its results include complex coordinates, schematic interface diagrams, interface alignments and DNA motifs.
Proper citation: TFmodeller (RRID:SCR_015715) Copy
http://amp.pharm.mssm.edu/gen3va/
Software tool for aggregation and analysis of gene expression signatures from related studies.Used to aggregate and analyze gene expression signatures extracted from GEO by crowd using GEO2Enrichr. Used to view aggregated report that provides global, interactive views, including enrichment analyses, for collections of signatures from multiple studies sharing biological theme.
Proper citation: GEN3VA (RRID:SCR_015682) Copy
http://amp.pharm.mssm.edu/CREEDS/
Software resource that allows students or the general public find variants that may be significantly associated with some disease. CREEDS also visualizes and analyzes gene expression signatures.
Proper citation: CRowd Extracted Expression of Differential Signatures (RRID:SCR_015680) Copy
Database of mouse brain cell type-specific gene expression datasets. NeuroExpresso is able to demonstrate the use of marker genes for acquiring cell type specific information from whole tissue expression.
Proper citation: NeuroExpresso (RRID:SCR_015724) Copy
https://www.rosettacommons.org/home
Molecular modeling software package for 3D structure prediction and high resolution design of proteins, nucleic acids, and non natural polymers. Used in computational biology, including de novo protein design, enzyme design, ligand docking, and structure prediction of biological macromolecules and macromolecular complexes.
Proper citation: Rosetta (RRID:SCR_015701) Copy
http://trans.nih.gov/bmap/index.htm
The Brain Molecular Anatomy Project is a trans-NIH project aimed at understanding gene expression and function in the nervous system. BMAP has two major scientific goals: # Gene discovery: to catalog of all the genes expressed in the nervous system, under both normal and abnormal conditions. # Gene expression analysis: to monitor gene expression patterns in the nervous system as a function of cell type, anatomical location, developmental stage, and physiological state, and thus gain insight into gene function. In pursuit of these goals, BMAP has launched several initiatives to provide resources and funding opportunities for the scientific community. These include several Requests for Applications and Requests for Proposals, descriptions of which can be found in this Web site. BMAP is also in the process of establishing physical and electronic resources for the community, including repositories of cDNA clones for nervous system genes, and databases of gene expression information for the nervous system. Most of the BMAP initiatives so far have focused on the mouse as a model species because of the ease of experimental and genetic manipulation of this organism, and because many models of human disease are available in the mouse. However, research in humans, other mammalian species, non-mammalian vertebrates, and invertebrates is also being funded through BMAP. For the convenience of interested investigators, we have established this Web site as a central information resource, focusing on major NIH-sponsored funding opportunities, initiatives, genomic resources available to the research community, courses and scientific meetings related to BMAP initiatives, and selected reports and publications. When appropriate, we will also post initiatives not directly sponsored by BMAP, but which are deemed relevant to its goals. Posting decisions are made by the Trans-NIH BMAP Committee
Proper citation: BMAP - Brain Molecular Anatomy Project (RRID:SCR_008852) Copy
http://www.sci.utah.edu/cibc/software/map3d.html
A scientific visualization application written to display and edit complex, three-dimensional geometric models and scalar, time-based data associated with those models such as high resolution EEG, MEG, and ECG.
Proper citation: map3d (RRID:SCR_009628) Copy
Web-based suite of phylogenetic analysis tools for use in evolutionary biology. Web application for comparative analysis of sequence alignments using statistical models. Used for analyzing evolutionary signatures in sequence data. Datamonkey 2.0 provides curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application.
Proper citation: Datamonkey (RRID:SCR_010278) Copy
Web tool to predict biological targets of miRNAs by searching for presence of conserved 8mer, 7mer and 6mer sites that match seed region of each miRNA. Nonconserved sites are also predicted and sites with mismatches in seed region that are compensated by conserved 3' pairing. Used to search for predicted microRNA targets in mammals.
Proper citation: TargetScan (RRID:SCR_010845) Copy
https://crispresso.pinellolab.partners.org/submission
Software suite of tools to qualitatively and quantitatively evaluate outcomes of genome editing experiments in which target loci are subject to deep sequencing and provides integrated, user friendly interface. Used for analysis of CRISPR-Cas9 genome editing outcomes from sequencing data. CRISPResso2 provides accurate and rapid genome editing sequence analysis.Used for analysis of deep sequencing data for rapid and intuitive interpretation of genome editing experiments.
Proper citation: CRISPResso (RRID:SCR_021538) Copy
https://github.com/nskvir/RepEnrich
Software tool to profile enrichment of next generation sequencing reads at transposable elements. Method to estimate repetitive element enrichment using high throughput sequencing data. Used to study genome wide transcriptional regulation of repetitive elements.RepEnrich2 is updated method to estimate repetitive element enrichment using high-throughput sequencing data.
Proper citation: RepEnrich (RRID:SCR_021733) Copy
https://vanvalen.github.io/about/
Software for segmenting individual cells in microscopy images using deep learning. Cell segmentation software.
Proper citation: DeepCell (RRID:SCR_022197) Copy
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