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http://compbio.mit.edu/ChromHMM/

Software tool for chromatin state discovery and characterization. Used for chromatin state discovery and genome annotation of non coding genome using epigenomic information across one or multiple cell types. Combines multiple genome wide epigenomic maps, and uses combinatorial and spatial mark patterns to infer complete annotation for each cell type. Provides automated enrichment analysis of resulting annotations.

Proper citation: ChromHMM (RRID:SCR_018141) Copy   

•   Source: SciCrunch Registry

http://ultrascan.aucsolutions.com/

Software package for hydrodynamic data from analytical ultracentrifugation experiments. Features integrated data editing and analysis environment with portable graphical user interface. Provides resolution for sedimentation velocity experiments using high-performance computing modules for 2-dimensional spectrum analysis, genetic algorithm, and for Monte Carlo analysis.

Proper citation: UltraScan (RRID:SCR_018126) Copy   

•   Source: SciCrunch Registry

https://github.com/brain-life/encode

Software that implements a framework to encode structural brain connectomes into multidimensional arrays (tensors). Encoding Connectomes provides an agile framework for computing over connectome edges and nodes.

Proper citation: Linear Fascicle Evaluation (RRID:SCR_016153) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/psc/

Data analysis software that can simultaneously characterize a large number of white matter bundles within and across different subjects for group analysis. It has three major components: construction of the structural connectome for the whole brain, low-dimensional representation of streamlines in each connection, and multi-level connectome analysis.

Proper citation: Mapping Population-based Structural Connectomes (RRID:SCR_016232) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/gscca_2013/

Group Sparse Canonical Correlation Analysis is a method designed to study the mutual relationship between two different types of data.

Proper citation: Group Sparse Canonical Correlation Analysis (RRID:SCR_014977) Copy   

•   Source: SciCrunch Registry

https://pynwb.readthedocs.io/en/latest/

Software Python package for working with Neurodata stored in Neurodata Without Borders files. Software providing API allowing users to read and create NWB formatted HDF5 files. Developed in support to NWB project with aim of spreading standardized data format for cellular based neurophysiology information.

Proper citation: PyNWB (RRID:SCR_017452) Copy   

•   Source: SciCrunch Registry

https://github.com/compbiolabucf/omicsGAN

Software generative adversarial network to integrate two omics data and their interaction network to generate one synthetic data corresponding to each omics profile that can result in better phenotype prediction. Used to capture information from interaction network as well as two omics datasets and fuse them to generate synthetic data with better predictive signals.

Proper citation: OmicsGAN (RRID:SCR_022976) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/fmridatacenter/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 25, 2013 Public curated repository of peer reviewed fMRI studies and their underlying data. This Web-accessible database has data mining capabilities and the means to deliver requested data to the user (via Web, CD, or digital tape). Datasets available: 107 NOTE: The fMRIDC is down temporarily while it moves to a new home at UCLA. Check back again in late Jan 2013! The goal of the Center is to help speed the progress and the understanding of cognitive processes and the neural substrates that underlie them by: * Providing a publicly accessible repository of peer-reviewed fMRI studies. * Providing all data necessary to interpret, analyze, and replicate these fMRI studies. * Provide training for both the academic and professional communities. The Center will accept data from those researchers who are publishing fMRI imaging articles in peer-reviewed journals. The goal is to serve the entire fMRI community.

Proper citation: fMRI Data Center (RRID:SCR_007278) Copy   

•   Source: SciCrunch Registry

http://nsr.bioeng.washington.edu/

Database of physiological, pharmacological, and pathological information on humans and other organisms and integration through computational modeling. Models include everything from diagrammatic schema, suggesting relationships among elements composing a system, to fully quantitative, computational models describing the behavior of physiological systems and an organism''s response to environmental change. Each mathematical model is an internally self-consistent summary of available information, and thereby defines a working hypothesis about how a system operates. Predictions from such models are subject to test, with new results leading to new models.BR /> A Tool developed for the NSR Physiome project is JSim, an open source, free software. JSim is a Java-based simulation system for building quantitative numeric models and analyzing them with respect to experimental reference data. JSim''s primary focus is in physiology and biomedicine, however its computational engine is quite general and applicable to a wide range of scientific domains. JSim models may intermix ODEs, PDEs, implicit equations, integrals, summations, discrete events and procedural code as appropriate. JSim''s model compiler can automatically insert conversion factors for compatible physical units as well as detect and reject unit unbalanced equations. JSim also imports the SBML and CellML model archival formats. All JSim models are open source. Goals of the Physiome Project: - To develop and database observations of physiological phenomenon and interpret these in terms of mechanism (a fundamentally reductionist goal). - To integrate experimental information into quantitative descriptions of the functioning of humans and other organisms (modern integrative biology glued together via modeling). - To disseminate experimental data and integrative models for teaching and research. - To foster collaboration amongst investigators worldwide, to speed up the discovery of how biological systems work. - To determine the most effective targets (molecules or systems) for therapy, either pharmaceutic or genomic. - To provide information for the design of tissue-engineered, biocompatible implants.

Proper citation: NSR Physiome Project (RRID:SCR_007379) Copy   

•   Source: SciCrunch Registry

http://cagt.bu.edu/page/PRECISE_about

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Database of interactions between amino acid residues of enzyme and its ligands. Provides summary of interactions between amino acid residues of enzyme and its various ligands including substrate and transition state analogues, cofactors, inhibitors, and products., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRECISE (RRID:SCR_007874) Copy   

•   Source: SciCrunch Registry

https://plantcyc.org/databases/aracyc/15.0

Curated species-specific database present at the Plant Metabolic Network. It has a large number of experimentally supported enzymes and metabolic pathways, but it also houses a substantial number of computationally predicted enzymes and pathways.

Proper citation: AraCyc (RRID:SCR_008109) Copy   

•   Source: SciCrunch Registry

http://openwetware.org/wiki/Main_Page

OpenWetWare is an effort to promote the sharing of information, know-how, and wisdom among researchers and groups who are working in biology & biological engineering. OWW provides a place for labs, individuals, and groups to organize their own information and collaborate with others easily and efficiently. In the process, the hope is that OWW will not only lead to greater collaboration between member groups, but also provide a useful information portal to our colleagues, and ultimately the rest of the world. OWW''s approaches to achieve their goals: # Lower the technical barriers to sharing and dissemination of knowledge in biological research # Build a community of researchers in biology and biological engineering that values, practices, and innovates the open sharing of information # Integrate OpenWetWare into existing and future reward structures in research

Proper citation: OpenWetWare (RRID:SCR_008053) Copy   

•   Source: SciCrunch Registry

https://bioinformatics.sdstate.edu/idep/

Integrated web application for differential expression and pathway analysis of RNA-Seq data.

Proper citation: iDEP: Integrated Differential Expression and Pathway analysis (RRID:SCR_027373) Copy   

•   Source: SciCrunch Registry

http://great.stanford.edu/public/html/splash.php

Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool

Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy   

•   Source: SciCrunch Registry

http://umbbd.msi.umn.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms).

Proper citation: UM-BBD (RRID:SCR_005787) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.

Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy   

•   Source: SciCrunch Registry

http://pmgn.vbi.vt.edu

The Oomycete Molecular Genetics Research Collaboration Network (OMGN) is a network for research collaboration for investigators interested in oomycete molecular genetics and genomics. The goals of the OMGN is to facilitate the integration of these investigators into the community and to further strengthen the cooperative culture of this community. A particular emphasis is placed on training and integrating junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. Because of their economic impact as plant pathogens, molecular, genetic and genomics studies are well advanced in many oomycete species. These organisms have served as lead species for the entire Stramenopiles lineage, a major radiation of crown eukaryotes, distinct from plants, animals and fungi. The oomycete molecular genetics community has a strong culture of collaboration and communication, and sharing of techniques and resources. With the recent blossoming of genetic and genomic tools for oomycetes, many new investigators, from a variety of backgrounds, have become interested in oomycete molecular genetics and genomics. The proposed network is open to all researchers with an interest in oomycete molecular genetics and genomics, either at an experimental or a computational level. Investigators new to the field are always welcome, especially those interested in saprophytes and animal pathogens. Goals of OMGN # Provide training to o��mycete molecular genetics researchers, especially those from smaller institutions, in the use of bioinformatics and genomics resources. # Promote the entry, participation and training of new investigators into the field of o��mycete genomics, particularly junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. # Promote communication and collaboration, and minimize duplication of effort, within the worldwide o��mycete genomics community. # Support an O��mycete Genomics Resources Center to maintain and distribute training and research materials produced by community genomics projects. The network''s activities have been supported by two grants from the NSF Research Collaboration Networks in Biology program.

Proper citation: OMGN (RRID:SCR_005781) Copy   

•   Source: SciCrunch Registry

http://mcbc.usm.edu/gofetcher/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: Quick Search, Advanced Search, and Upload Files for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format. Platform: Online tool

Proper citation: GOfetcher (RRID:SCR_005681) Copy   

•   Source: SciCrunch Registry

http://connectomes.utah.edu/

A web-compliant application that allows connectomics visualization by converting datasets to web-optimized tiles, delivering volume transforms to client devices, and providing groups of users with connectome annotation tools and data simultaneously via conventional internet connections. Viking is an extensible tool for connectomics analysis and is generalizable to histomics applications.

Proper citation: Viking Viewer for Connectomics (RRID:SCR_005986) Copy   

•   Source: SciCrunch Registry

http://www.crowdlabs.org/

A social visualization repository for the scientific workflow management system VisTrails providing a platform for sharing and executing computational tasks. It adopts the model used by social Web sites and that integrates a set of usable tools and a scalable infrastructure to provide an environment for scientists to collaboratively analyze and visualize data. crowdLabs aims to foster collaboration but was specifically designed to support the needs of computational scientists, including the ability to access high-performance computers and manipulate large volumes of data. By providing mechanisms that simplify the publishing and use of analysis pipelines, it allows IT personnel and end users to collaboratively construct and refine portals. This lowers the barriers for the use of scientific analyses and enables broader audiences to contribute insights to the scientific exploration process, without the high costs incurred by traditional portals. In addition, it supports a more dynamic environment where new exploratory analyses can be added on-the-fly.

Proper citation: crowdLabs (RRID:SCR_006294) Copy   

•   Source: SciCrunch Registry