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http://genome.ucsc.edu/ENCODE

Encyclopedia of DNA elements consisting of list of functional elements in human genome, including elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Enables scientific and medical communities to interpret role of human genome in biology and disease. Provides identification of common cell types to facilitate integrative analysis and new experimental technologies based on high-throughput sequencing. Genome Browser containing ENCODE and Epigenomics Roadmap data. Data are available for entire human genome.

Proper citation: ENCODE (RRID:SCR_006793) Copy   

•   Source: SciCrunch Registry

http://bio.math.berkeley.edu/eXpress/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented January 29, 2018.
From website: "Note that the eXpress software is also no longer being developed. We recommend you use kallisto instead." Kallisto can be found at http://pachterlab.github.io/kallisto/.

Software for streaming quantification for high-throughput DNA/RNA sequencing.
Can be used in any application where abundances of target sequences need to be estimated from short reads sequenced from them.

Proper citation: eXpress (RRID:SCR_006873) Copy   

•   Source: SciCrunch Registry

http://intramural.nimh.nih.gov/sscc/index.html

Scientific and Statistical Computing Core of the NIMH Intramural Research Program supporting functional neuroimaging research at the NIH. This includes development of new data analysis techniques, their implementation in the AFNI software, advising researchers on the analysis methods, and instructing them in the use of software tools. Support methods: A. Provision of software for analysis for FMRI data (AFNI package: http://afni.nimh.nih.gov) * AFNI has been developed for the last 10 years by Dr Cox, et al. (6 years in Milwaukee, 4 years at NIMH) * Formal and informal instruction in the use of AFNI, including outlines of the statistical methods used in the programs * Installation of AFNI on NIH computers (Mac OS X, Unix, Linux) approximately 120 NIH systems have used AFNI in the last month (80 NIMH, 20 NINDS, 20 other) * Realtime monitoring of FMRI data at scanners * Continuing development of new modules for AFNI to meet needs of NIH researchers B. Consulting with NIH researchers about FMRI data analysis issues, concerns, and methods

Proper citation: NIMH DIRP Scientific and Statistical Computing Core (RRID:SCR_006958) Copy   

•   Source: SciCrunch Registry

http://www.icpsr.umich.edu/SAMHDA/

Database of the nation''s substance abuse and mental health research data providing public use data files, file documentation, and access to restricted-use data files to support a better understanding of this critical area of public health. The goal is to increase the use of the data to most accurately understand and assess substance abuse and mental health problems and the impact of related treatment systems. The data include the U.S. general and special populations, annual series, and designs that produce nationally representative estimates. Some of the data acquired and archived have never before been publicly distributed. Each collection includes survey instruments (when provided), a bibliography of related literature, and related Web site links. All data may be downloaded free of charge in SPSS, SAS, STATA, and ASCII formats and most studies are available for use with the online data analysis system. This system allows users to conduct analyses ranging from cross-tabulation to regression without downloading data or relying on other software. Another feature, Quick Tables, provides the ability to select variables from drop down menus to produce cross-tabulations and graphs that may be customized and cut and pasted into documents. Documentation files, such as codebooks and questionnaires, can be downloaded and viewed online.

Proper citation: Substance Abuse and Mental Health Data Archive (RRID:SCR_007002) Copy   

•   Source: SciCrunch Registry

http://mga.bionet.nsc.ru/soft/maia-1.0/

Software package of programs for complex segregation analysis in animal pedigrees.

Proper citation: MAIA (RRID:SCR_007153) Copy   

•   Source: SciCrunch Registry

http://www.biomanta.org/

This project encompasses development of novel biological network analysis methods and infrastructure for querying biological data in a semantically-enabled format, and aims to create a semantic interactome model. Research within the BioMANTA project will focus on computational modelling and analysis, primarily using Semantic Web technologies and Machine Learning methods, of large-scale protein-protein interaction and compound activity networks across a wide variety of species. A range of information such as kinetic activity, tissue expression, and subcellular localization and disease state attributes will be included in the resulting data model. Protein interactions are a fundamental component of biological processes. Many proteins are functional only in multimeric complexes, or require interaction partners to achieve their correct localisation or function. For this reason, the study of protein-protein interaction (PPI) networks has become an area of growing interest in computational biology. Through the use of Semantic Web technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL), interaction data is modelled to create a knowledge representation in which meaning is vested in the ontology rather than instances of data. Stochastic and computational intelligence methods are applied to this data to infer high coverage networks. Semantic inferencing is used to infer previously unknown and meaningful pathways. Major project components: - The BioMANTA Ontology:- An OWL DL ontology incorporating the PSI-MI Ontology, the NCBI Taxonomy, and elements of BioPax ontology and Gene Ontology (describing subcellular localisation). This allows us to re-use existing ontologies, thereby reducing overheads associated with knowledge acquisition in the ontology development process. We are able to integrate existing public data that contain annotation in these formats. - Data conversion & semantic protein integration:- A set of software components that convert protein-protein databases (DIP, MPact, IntAct, etc.) from PSI-MI XML to RDF compliant with the BioMANTA ontology. These software allow us to make these protein-protein interaction datasets (and more generally, any PSI-MI XML data) semantically available for querying and inference within BioMANTA. - A RDF triple store based on RDF Molecules and the MapReduce architecture:- A proof-of-concept RDF triple store using RDF molecules and Hadoop scale-out architectures. Regular RDF graphs are deconstructed into RDF molecules, which are distributed over distributed compute nodes in the MapReduce architecture, and are subsequently combined to form equivalent RDF graphs. Such an approach makes the distributed SPARQL querying and reasoning on RDF triple stores possible. - A quantitative framework to integrate networks extracted from independent data sources (gene expression, subcellular localization, and ortholog mapping):- The model is multi-layer, with a first layer based on Decision Trees where each Decision tree is built on each dataset independently. The tree nodes are cut using Shannon''s entropy (mutual information); the decision of these independent trees is integrated using logistic regression, and the parameters are optimised using maximum likelihood. Sponsors: This resource is supported by the Pfizer Global Research and Development, the Institute for Molecular Bioscience (IMB), and the University of Queensland, Australia.

Proper citation: BioMANTA (RRID:SCR_007177) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/high-throughput-sequencing-and-microarray-facility-princeton

Core facility provides researchers with access to high-throughput sequencing technologies. The staff provide consultation on experimental design, library preparation, and data analysis. The Sequencing Core Facility works closely with Bioinformatics staff in the Center for Quantitative Biology to provide researchers with computing power and consulting services to analyze sequencing data.

Proper citation: Princeton High Throughput Sequencing and Microarray Facility (RRID:SCR_012619) Copy   

•   Source: SciCrunch Registry

https://www.immport.org/home

Data sharing repository of clinical trials, associated mechanistic studies, and other basic and applied immunology research programs. Platform to store, analyze, and exchange datasets for immune mediated diseases. Data supplied by NIAID/DAIT funded investigators and genomic, proteomic, and other data relevant to research of these programs extracted from public databases. Provides data analysis tools and immunology focused ontology to advance research in basic and clinical immunology.

Proper citation: The Immunology Database and Analysis Portal (ImmPort) (RRID:SCR_012804) Copy   

•   Source: SciCrunch Registry

https://github.com/macs3-project/MACS

Software Python package for identifying transcript factor binding sites. Used to evaluate significance of enriched ChIP regions. Improves spatial resolution of binding sites through combining information of both sequencing tag position and orientation. Can be used for ChIP-Seq data alone, or with control sample with increase of specificity.

Proper citation: MACS (RRID:SCR_013291) Copy   

•   Source: SciCrunch Registry

http://www.mrc-lmb.cam.ac.uk/genomes/dolop/

DOLOP is an exclusive knowledge base for bacterial lipoproteins by processing information from 510 entries to provide a list of 199 distinct lipoproteins with relevant links to molecular details. Features include functional classification, predictive algorithm for query sequences, primary sequence analysis and lists of predicted lipoproteins from 43 completed bacterial genomes along with interactive information exchange facility. This website along will have additional information on the biosynthetic pathway, supplementary material and other related figures. DOLOP also contains information and links to molecular details for about 278 distinct lipoproteins and predicted lipoproteins from 234 completely sequenced bacterial genomes. Additionally, the website features a tool that applies a predictive algorithm to identify the presence or absence of the lipoprotein signal sequence in a user-given sequence. The experimentally verified lipoproteins have been classified into different functional classes and more importantly functional domain assignments using hidden Markov models from the SUPERFAMILY database that have been provided for the predicted lipoproteins. Other features include: primary sequence analysis, signal sequence analysis, and search facility and information exchange facility to allow researchers to exchange results on newly characterized lipoproteins.

Proper citation: DOLOP: A Database of Bacterial Lipoproteins (RRID:SCR_013487) Copy   

•   Source: SciCrunch Registry

http://www.cma.mgh.harvard.edu/iatr/display.php?spec=id&ids=107

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 6,2023. EMMA (Extensible MATLAB Medical image Analysis) is a toolkit designed to ease the use of MATLAB in the analysis of medical imaging data. It provides functions for reading and writing MINC files, viewing images, performing ROI operations, and performing several popular analyses. Also, there are toolkits for performing kinetic analysis of dynamic PET rCBF (regional cerebral blood flow) and FDG data. The goal for this site is to provide a centrally available listing of all image analysis tools that are available to the neuroscience community in order to facilitate the development, identification, and sharing of tools that are of use to the general community.

Proper citation: Extensible MATLAB Medical image Analysis (RRID:SCR_013499) Copy   

•   Source: SciCrunch Registry

http://www.licor.com/bio/products/software/image_studio_lite/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 28,2023. Software application which can analyze basic Western blot data and export them for use in spreadsheet programs. Users can create standardized or custom lab reports and can share them with colleagues. Image Studio Lite has been discontinued and replaced with Empiria Studio Software.

Proper citation: Image Studio Lite (RRID:SCR_013715) Copy   

•   Source: SciCrunch Registry

http://www.hedtags.org/

Strategy guide for HED Annotation. Framework for systematically describing laboratory and real world events.HED tags are comma separated path strings. Organized in forest of groups with roots Event, Item, Sensory presentation, Attribute, Action, Participant, Experiment context, and Paradigm. Used for preparing brain imaging data for automated analysis and meta analysis. Applied to brain imaging EEG, MEG, fNIRS, multimodal mobile brain or body imaging, ECG, EMG, GSR, or behavioral data. Part of Brain Imaging Data Structure standard for brain imaging.

Proper citation: HED Tags (RRID:SCR_014074) Copy   

•   Source: SciCrunch Registry

https://skyline.gs.washington.edu/labkey/project/home/software/Skyline/begin.view

Software tool as Windows client application for targeted proteomics method creation and quantitative data analysis. Open source document editor for creating and analyzing targeted proteomics experiments. Used for large scale quantitative mass spectrometry studies in life sciences.

Proper citation: Skyline (RRID:SCR_014080) Copy   

•   Source: SciCrunch Registry

http://www.originlab.com/index.aspx?go=PRODUCTS/Origin

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 4, 2025.Software application for data analysis and graphing. Origin contains a variety of different graph types, including statistical plots, 2D and 3D vector graphs, and counter graphs. More advance version is OriginPro which offers advanced analysis tools and Apps for Peak Fitting, Surface Fitting, Statistics and Signal Processing.

Proper citation: Origin (RRID:SCR_014212) Copy   

•   Source: SciCrunch Registry

http://www.maplesoft.com/products/Maple/

Mathematical software that can compute both numeric and symbolic solutions. It can be used to analyze, explore, visualize, and solve mathematical problems.

Proper citation: Maple (RRID:SCR_014449) Copy   

•   Source: SciCrunch Registry

https://www.wolfram.com/mathematica/

A technical computing software and computing environment that provides users with algorithms and mathematical functions for various projects and purposes. The resource incorporates other Wolfram products such as Wolfram Algorithmbase, Wolfram Language, and Wolfram Knowledgebase.

Proper citation: Wolfram Mathematica (RRID:SCR_014448) Copy   

•   Source: SciCrunch Registry

http://marrvel.org/

Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.

Proper citation: MARRVEL (RRID:SCR_016871) Copy   

•   Source: SciCrunch Registry

http://cab.spbu.ru/software/rnaspades/

Software tool for assembling transcripts from RNA-Seq data. Explores surprising computational parallels between assembly of transcriptomes and single cell genomes. Suitable for all kind of organisms. Part of SPAdes package since version 3.9.

Proper citation: rnaSPAdes (RRID:SCR_016992) Copy   

•   Source: SciCrunch Registry

https://www.sciencescott.com/pyminer

Software tool to automate cell type identification, cell type-specific pathway analyses, graph theory-based analysis of gene regulation, and detection of autocrine-paracrine signaling networks. Finds Gene and Autocrine-Paracrine Networks from Human Islet scRNA-Seq.

Proper citation: PyMINEr (RRID:SCR_016990) Copy   

•   Source: SciCrunch Registry