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http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

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http://humancyc.org/

The HumanCyc database describes human metabolic pathways and the human genome. By presenting metabolic pathways as an organizing framework for the human genome, HumanCyc provides the user with an extended dimension for functional analysis of Homo sapiens at the genomic level. A computational pathway analysis of the human genome assigned human enzymes to predicted metabolic pathways. Pathway assignments place genes in their larger biological context, and are a necessary step toward quantitative modeling of metabolism. HumanCyc contains the complete genome sequence of Homo sapiens, as presented in Build 31. Data on the human genome from Ensembl, LocusLink and GenBank were carefully merged to create a minimally redundant human gene set to serve as an input to SRI''s PathoLogic software, which generated the database and predicted Homo sapiens metabolic pathways from functional information contained in the genome''s annotation. SRI did not re-annotate the genome, but worked with the gene function assignments in Ensembl, LocusLink, and GenBank. The resulting pathway/genome database (PGDB) includes information on 28,783 genes, their products and the metabolic reactions and pathways they catalyze. Also included are many links to other databases and publications. The Pathway Tools software/database bundle includes HumanCyc and the Pathway Tools software suite and is available under license. This form of HumanCyc is faster and more powerful than the Web version.

Proper citation: HumanCyc: Encyclopedia of Homo sapiens Genes and Metabolism (RRID:SCR_007050) Copy   

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http://tritrypdb.org/tritrypdb/

An integrated genomic and functional genomic database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. ''''User Comments'''' may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate. TriTrypDB provides programmatic access to its searches, via REST Web Services. The result of a web service request is a list of records (genes, ESTs, etc) in either XML or JSON format. REST services can be executed in a browser by typing a specific URL. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).

Proper citation: TriTrypDB (RRID:SCR_007043) Copy   

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http://deconseq.sourceforge.net/

Software tool to automatically detect and efficiently remove sequence contaminations from genomic and metagenomic datasets. It is easily configurable and provides a user-friendly interface. The user can upload FASTA or FASTQ files and select the databases used for contamination screening, including seven human genomes, bacterial genomes, and viral genomes. The user can set the thresholds interactivly and see the results directly using the functionality of the graphical interface. The results can be downloaded in joined or separated files in different formats. The coverage-identity plots provide additional information that can guide the selections of the thresholds using color coded points and connecting lines.

Proper citation: DeconSeq (RRID:SCR_007006) Copy   

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http://www.obofoundry.org/

A collaboration involving developers of science-based ontologies who are establishing a set of principles for ontology development with the goal of creating a suite of orthogonal interoperable reference ontologies in the biomedical domain. In addition to a listing of OBO ontologies, this site provides a statement of the OBO Foundry principles, discussion fora, technical infrastructure, and other services to facilitate ontology development. Feedback is welcome and participation encouraged.

Proper citation: OBO (RRID:SCR_007083) Copy   

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http://www.vbase2.org/

Integrative database of germ-line V genes from the immunoglobulin loci of human and mouse. It presents V gene sequences extracted from the EMBL nucleotide sequence database and Ensembl together with links to the respective source sequences. Based on the properties of the source sequences, V genes are classified into 3 different classes: * Class 1: genomic and rearranged evidence * Class 2: genomic evidence only * Class 3: rearranged evidence only This allows careful sequence quality validation by the user. References to other immunological databases ( KABAT, IMGT/LIGM and VBASE ) are given to provide all public annotation data for each V gene. The VBASE2 database can be accessed either by the Direct Query interface or by the DNAPLOT Query interface. The Sequences given by the user are aligned with DNAPLOT against the VBASE2 database. Direct Query allows to enter sequence IDs and names (Field 1), choose species, locus, V gene family and class (Field 2) or search for 100% sequences (Field 3). At the DNAPLOT Query, the sequences given by the user are aligned with DNAPLOT against the VBASE2 database. The DNAPLOT program offers V gene nucleotide sequence alignment referring to the IMGT V gene unique numbering. The Quick Search can be used either for Direct Query to search for sequence IDs and V gene names or for DNAPLOT Query for up to 5 sequences. The new Fab Analysis allows you to align Fab, scFab, scAb or scFv sequences with DNAPLOT against the VBASE2 database, where both heavy and light chain are analyzed.

Proper citation: VBASE2 (RRID:SCR_007082) Copy   

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http://physionet.org/physiobank/

Archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community. PhysioBank currently includes databases of multi-parameter cardiopulmonary, neural, and other biomedical signals from healthy subjects and patients with a variety of conditions with major public health implications, including sudden cardiac death, congestive heart failure, epilepsy, gait disorders, sleep apnea, and aging. The PhysioBank Archives now contain over 700 gigabytes of data that may be freely downloaded. PhysioNet is seeking contributions of data sets that can be made freely available in PhysioBank. Contributions of digitized and anonymized (deidentified) physiologic signals and time series of all types are welcome. If you have a data set that may be suitable, please review PhysioNet''s guidelines for contributors and contact them.

Proper citation: Physiobank (RRID:SCR_006949) Copy   

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http://vcell.org/

V-Cell is a remote user modeling and simulation environment utilizing Java''s Remote Method Invocation (RMI). The biologically oriented user interface allows experimentalists to create models, define cellular geometry, specify simulations and analyze the simulation results. The results are run and stored on a remote server and can be reviewed in the software and/or exported in a variety of popular formats. The design of the biological to mathematical mapping allows for separate use of biological and math components, and includes automatic mathematical simplification using pseudo-steady approximations and mass conservation relationships. This allows for direct specification of mathematical problems, performing simulations and analysis on those systems. The stand alone mathematics user interface is also a powerful tool for modeling reaction-diffusion systems. A transparent general purpose solver is used to translate the initial biological description into a set of concise mathematical problems. The solver is transparent to the average user, but is accessible to the theorist as the Math Editor component. The software is composed of three main components: 1. The modeling framework represents the physiological models of the Virtual Cell and allows for persistence and database support. 2. The mathematics framework transparently solves an important class of mathematical problems encountered in the cellular modeling. 3. The WWW accessible graphical user interface provides access to the technology mentioned above. The user interface has been developed using Java 2 Applets.

Proper citation: Virtual Cell at the National Resource for Cell Analysis and Modeling (RRID:SCR_007421) Copy   

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http://celldesigner.org/

CellDesigner is a structured diagram editor for drawing gene-regulatory and biochemical networks. Networks are drawn based on the process diagram, with graphical notation system proposed by Kitano, and are stored using the Systems Biology Markup Language (SBML), a standard for representing models of biochemical and gene-regulatory networks. Networks are able to link with simulation and other analysis packages through Systems Biology Workbench (SBW). By using CellDesigner, you can browse and modify existing SBML models with references to existing databases, simulate and view the dynamics through an intuitive graphical interface. Sponsors: ERATO-SORST program (JST); International Standard Development area of the International Joint Research Grant (NEDO); Strategic Japanese-Swedish Cooperative Program on Multidisciplinary BIO (JST-VINNOVA/SSF); Establishment of a Human Genome Network Platform (MEXT) and through the special coordination funds for promoting science and technology from the Japanese government''s Ministry of Education, Culture, Sports, Science and Technology (MEXT) Keywords: Cell, Designer, Gene, Biochemical, Network, Diagram, Biology, System, Gene, Biolohy, Database,

Proper citation: CellDesigner: A modeling tool of biochemical networks (RRID:SCR_007263) Copy   

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http://www.brainvisa.info/

BrainVISA is a modular an customizable software platform built to host heterogeneous tools dedicated to neuroimaging research. Many toolboxes have already been developed for BrainVISA (T1 MRI, sulcal identification and morphometry, cortical surface analysis, diffusion imaging and tractography, fMRI, nuclear imaging, EEG and MEG, TMS, histology and autoradiography, etc.). Anatomist is a software for interactive visualization of multimodal data and for manipulation of structured 3D objects. It allows to build scenes that merge or combine images, meshes, regions of interest, fibers, textures, color palettes, referential changes, etc. A user can interact in 3D and in real time with the objects of an Anatomist scene: change point of view, select objects, add/suppress objects, change colors, draw regions of interests, do manual registration, etc. BrainVISA main features are: * Harmonization of communications between different software. For instance, BrainVISA toolboxes are using home-made software but also third-party software such as FreeSurfer, FSL, SPM, nipy, R-project, Matlab, etc. * Ontology-based data organization allowing database sharing and automation of mass of data analysis. * Fusion and interactive visualization of multimodal data (using Anatomist software). * Automatic generation of graphical user interfaces. * Workflow monitoring and data quality checking. * Full customization possible. * Runs on Linux, Mac and Windows. * Programming Language: C++, Python * Supported Data Format: ANALYZE, DICOM, GIfTI, MINC, NIfTI-1, Other Format

Proper citation: BrainVISA / Anatomist (RRID:SCR_007354) Copy   

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https://cgc.umn.edu

Center that acquires, maintains, and distributes genetic stocks and information about stocks of the small free-living nematode Caenorhabditis elegans for use by investigators initiating or continuing research on this genetic model organism. A searchable strain database, general information about C. elegans, and links to key Web sites of use to scientists, including WormBase, WormAtlas, and WormBook are available.

Proper citation: Caenorhabditis Genetics Center (RRID:SCR_007341) Copy   

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http://fmri.wfubmc.edu/software/PickAtlas

A software toolbox that provides a method for generating Region of Interest (ROI) masks based on the Talairach Daemon database. The atlases include Brodmann area, Lobar, Hemisphere, Anatomic Label (gyral anatomy), and Tissue type. The atlases have been extended to the vertex in MNI space, and corrected for the precentral gyrus anomaly. Additional atlases (including non-human atlases) can be added without difficulty., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: WFU PickAtlas (RRID:SCR_007378) Copy   

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http://pbil.univ-lyon1.fr/cap3.php

This form allows you to assemble a set of contiguous sequences (contigs) with the CAP3 program. The CAP3 program has a capability to clip 5'' and 3'' low-quality regions of reads. It uses base quality values in computation of overlaps between reads, construction of multiple sequence alignments of reads, and generation of consensus sequences. The program also uses forward-reverse constraints to correct assembly errors and link contigs. Results of CAP3 on four BAC data sets are presented. The performance of CAP3 was compared with that of PHRAP on a number of BAC data sets. PHRAP often produces longer contigs than CAP3 whereas CAP3 often produces fewer errors in consensus sequences than PHRAP. It is easier to construct scaffolds with CAP3 than with PHRAP on low-pass data with forward-reverse constraints. Sponsors: This project was supported by NIH Grant R01HG01502-02 from NHGRI. Keywords: CAP3, Program, Form, Computation, DNA, Dataset, Database, Program,, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CAP3 Sequence Assembly Program (RRID:SCR_007250) Copy   

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http://compbio.mit.edu/cummeRbund/index.html

Software R package used for simplifying and analyzing Cufflink RNA-Seq output. This program takes various output files from a cuffdiff run and creates a SQLite database of the results that will describe the appropriate relationships between the genes, transcripts, transcription start sites and CDS regions.

Proper citation: CummeRbund (RRID:SCR_014568) Copy   

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http://csbg.cnb.csic.es/mbrole/

Software program for overrepresentation (enrichment) analysis of categorical annotations for a set of compounds. These categorical annotations correspond to biological and chemical information found in public databases and software. Annotations can be biological (pathways, enzyme interactions, pharmacological action) or chemical (taxonomy and chemical groups).

Proper citation: MBRole (RRID:SCR_014684) Copy   

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https://www.schrodinger.com/Phase/

Pharmacophore modeling software to create 3D structure activity relationships, screen databases, and generate hits through establishing a chemical space occupied by active ligands. Used in drug design.

Proper citation: Phase (RRID:SCR_014884) Copy   

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http://macvector.com

Software application that provides sequence editing, primer design, internet database searching, protein analysis, sequence confirmation, multiple sequence alignment, phylogenetic reconstruction, coding region analysis, agarose gel simulation and a variety of other functions.

Proper citation: MacVector (RRID:SCR_015700) Copy   

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http://www.diagram-consortium.org/

Consortium of researchers aiming to characterize the genetic basis of type 2 diabetes with a principal focus on samples of European descent. DIAGRAM also features a database of DIAGRAM publications and diabetes-related research data.

Proper citation: DIAGRAM (RRID:SCR_015675) Copy   

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http://ualcan.path.uab.edu/cgi-bin/ualcan-res.pl

Web application and database for analyzing cancer transcriptome data. It also has applications is facilitating tumor subgroup gene expression and survival analyses.

Proper citation: UALCAN (RRID:SCR_015827) Copy   

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http://app.cgu.edu.tw/circlnc/

Web application for mapping functional networks of long or circular forms of non-coding RNAs. It supports the uploading and processing of user-defined NGS-based gene expression matrix data.

Proper citation: circlncRNAnet (RRID:SCR_015794) Copy   

•   Source: SciCrunch Registry