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http://www.peroxisomedb.org/

The aim of the PEROXISOME database (PeroxisomeDB) is to gather, organize and integrate curated information on peroxisomal genes, their encoded proteins, their molecular function and metabolic pathway they belong to, and their related disorders. PeroxisomeDB contains the complete peroxisomal proteome of Homo sapiens (encoded by 85 genes) and Saccharomyces cerevisiae (encoded by 61 genes). Now, we have included 34 new organism genomes with the acquisition of 2426 new peroxisomal homolog proteins. PeroxisomeDB 2.0 integrates the peroxisomal metabolome of whole microbody family by the new incorporation of the glycosome proteomes of trypanosomatids and the glyoxysome proteome of Arabidopsis thaliana. The site also provides a Peroxisome Metabolome of peroxisomal genes and proteins, their molecular interactions and metabolic pathways, tools for comparative genomics, predictive tools. Sponsors: Preoxisome Database is funded by Institut de Gntique et deBiologie Molculaire et Cellulaire.

Proper citation: Peroxisome Database (RRID:SCR_008352) Copy   

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http://cssb.biology.gatech.edu/skolnick/files/gpcr/gpcr.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 19,2019.Database of tertiary structural modeling results of threading assembly refinement (TASSER) method for all 907 G protein-coupled receptors (GPCRs) in human genome. All sequences were collected from GPCR database http://www.gpcr.org/7tm/ and http://www.expasy.org/cgi-bin/lists?7tmrlist.txt. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. G protein-coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha) root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness of the in silico models for GPCR functional analysis. Sponsors: GPCR is funded by the University at Buffalo, Buffalo, New York.

Proper citation: Structure modeling of 907 G protein coupled receptors in the human genome (RRID:SCR_008351) Copy   

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http://genome.jgi.doe.gov/programs/metagenomes/index.jsf

Portal providing access to metagenomics projects, data and tools supported by the DOE Joint Genome Institute (JGI). A primary motivation for metagenomics is that most microbes found in nature exist in complex, interdependent communities and cannot readily be grown in isolation in the laboratory. One can, however, isolate DNA or RNA from the community as a whole, and studies of such communities have revealed a diversity of microbes far beyond those found in culture collections. It is suspected that these uncultivated organisms must harbor considerable as-yet undiscovered genomic, functional, and metabolic features and capabilities. Thus to fully explore microbial genomics, it is imperative that we access the genomes of these elusive players.

Proper citation: Metagenomics Program at JGI (RRID:SCR_008804) Copy   

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https://bbgre.brc.iop.kcl.ac.uk

A database and associated tools for investigating the genetic basis of neurodisability. It combines phenotype information from patients with neurodevelopmental and behavioral problems with clinical genetic data, and displays this information on the human genome map. Basic access to genetic information (deletions, duplications) relating to participants with neurodevelopmental disorders is provided without an account; access to the full dataset requires an account. The genetic information that is available to view comprises potentially pathogenic copy number variation across the genome, detected by array comparative genome hybridization (aCGH) using a customized 44K oligonucleotide array.

Proper citation: Brain and Body Genetic Resource Exchange (RRID:SCR_008959) Copy   

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http://hipathdb.kobic.re.kr/

hiPathDB is an integrated pathway database that combines the curated human pathway data of NCI-Nature PID, Reactome, BioCarta and KEGG. In total, it includes 1661 pathways consisting of 8976 distinct physical entities. (2010.03.09) hiPathDB provides two different types of integration. The pathway-level integration, conceptually a simple collection of individual pathways, was achieved by devising an elaborate model that takes distinct features of four databases into account and subsequently reformatting all pathways in accordance with our model. The entity-level integration creates a single unified pathway that encompasses all pathways by merging common components. Even though the detailed molecular-level information such as complex formation or post-translational modifications tends to be lost, such integration makes it possible to investigate signaling network over the entire pathways and allows identification of pathway cross-talks. Another strong merit of hiPathDB is the built-in pathway visualization module that supports explorative studies of complex networks in an interactive fashion. The layout algorithm is optimized for virtually automatic visualization of the pathways.

Proper citation: hiPathDB - human integrated Pathway DB with facile visualization (RRID:SCR_008900) Copy   

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http://www.medinfopoli.polimi.it/GFINDer/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 16, 2019. Multi-database system providing large-scale lists of user-classified sequence identifiers with genome-scale biological information and functional profiles biologically characterizing the different gene classes in the list. GFINDer automatically retrieves updated annotations of several functional categories from different sources, identifies the categories enriched in each class of a user-classified gene list, and calculates statistical significance values for each category. Moreover, GFINDer enables to functionally classify genes according to mined functional categories and to statistically analyze the obtained classifications, aiding in better interpreting microarray experiment results.

Proper citation: GFINDer: Genome Function INtegrated Discoverer (RRID:SCR_008868) Copy   

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http://bioinfo.au.tsinghua.edu.cn/atie/

A database of publicly available genes, alternatively translational isoforms and their detailed annotation. Alternative translational initiation is one of mechanisms to increase the complexity level of an organism by alternative gene expression pathways. The use of alternative translation initiation codons in a singe mRNA contributes to the generation of protein diversity. The genes produce two or more versions of the encoded proteins, and the shorter version, initiated from a downstream in-frame start codon, lacks the N-terminal amino acids fragment of the full-length isoform version. Since the first discovery of alternative translation initiation, a small, yet growing, number of mRNAs initiating translation from alternative start codons have been reported. Various studies began to emerge focusing on this new field in gene expression and revealed the biological significance of the use of alternative initiation. In response to the need for systematic studies on genes involving alternative translational initiation, Alternative Translational Initiation Database(ATID) is established to provide data of publicly available genes, alternatively translational isoforms and their detailed annotation.

Proper citation: ATID: Alternative Translational Initiation Database (RRID:SCR_009432) Copy   

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http://genomics.senescence.info/genes/

Collection of annotated and manually curated data of genes related to aging divided into genes related to longevity and/or aging in model organisms (yeast, worms, flies, mice, etc.) and aging related human genes.

Proper citation: GenAge (RRID:SCR_010223) Copy   

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http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000674.v1.p1

Human genetics data from an immense (78,000) and ethnically diverse population available for secondary analysis to qualified researchers through the database of Genotypes and Phenotypes (dbGaP). It offers the opportunity to identify potential genetic risks and influences on a broad range of health conditions, particularly those related to aging. The GERA cohort is part of the Research Program on Genes, Environment, and Health (RPGEH), which includes more than 430,000 adult members of the Kaiser Permanente Northern California system. Data from this larger cohort include electronic medical records, behavioral and demographic information from surveys, and saliva samples from 200,000 participants obtained with informed consent for genomic and other analyses. The RPGEH database was made possible largely through early support from the Robert Wood Johnson Foundation to accelerate such health research. The genetic information in the GERA cohort translates into more than 55 billion bits of genetic data. Using newly developed techniques, the researchers conducted genome-wide scans to rapidly identify single nucleotide polymorphisms (SNPs) in the genomes of the people in the GERA cohort. These data will form the basis of genome-wide association studies (GWAS) that can look at hundreds of thousands to millions of SNPs at the same time. The RPGEH then combined the genetic data with information derived from Kaiser Permanente''s comprehensive longitudinal electronic medical records, as well as extensive survey data on participants'' health habits and backgrounds, providing researchers with an unparalleled research resource. As information is added to the Kaiser-UCSF database, the dbGaP database will also be updated.

Proper citation: Resource for Genetic Epidemiology Research on Adult Health and Aging (RRID:SCR_010472) Copy   

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-8-S1-S21

A microarray platform that uses the Illumina and Affymetrix GeneChip microarray technology for genome and transcriptome analyses and a web-based database that consists exclusively of high quality Affymetrix data from immunological experiments hosted by a public, non-profit consortium of three scientific public institutions aimed to develop, integrate and disseminate Functional Genomics.

Proper citation: Genopolis (RRID:SCR_010975) Copy   

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http://www.genomicus.biologie.ens.fr/genomicus-72.01/cgi-bin/search.pl

A genome browser that enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversaly across different species, and chronologicaly along evolutionary time.

Proper citation: Genomicus (RRID:SCR_011791) Copy   

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http://metscape.ncibi.org

A software program that allows users to visualize and interpret human metabolim and expression profiling data by providing users with a bioinformatics framework. Its features include bulding and analyzing networks of genes and compounds, identifying enriched pathways from expression profiling data, and visualizing changes in metabolite data.

Proper citation: Metscape (RRID:SCR_014687) Copy   

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https://www.sanger.ac.uk/collaboration/sequencing-idd-regions-nod-mouse-genome/

Genetic variations associated with type 1 diabetes identified by sequencing regions of the non-obese diabetic (NOD) mouse genome and comparing them with the same areas of a diabetes-resistant C57BL/6J reference mouse allowing identification of single nucleotide polymorphisms (SNPs) or other genomic variations putatively associated with diabetes in mice. Finished clones from the targeted insulin-dependent diabetes (Idd) candidate regions are displayed in the NOD clone sequence section of the website, where they can be downloaded either as individual clone sequences or larger contigs that make up the accession golden path (AGP). All sequences are publicly available via the International Nucleotide Sequence Database Collaboration. Two NOD mouse BAC libraries were constructed and the BAC ends sequenced. Clones from the DIL NOD BAC library constructed by RIKEN Genomic Sciences Centre (Japan) in conjunction with the Diabetes and Inflammation Laboratory (DIL) (University of Cambridge) from the NOD/MrkTac mouse strain are designated DIL. Clones from the CHORI-29 NOD BAC library constructed by Pieter de Jong (Children's Hospital, Oakland, California, USA) from the NOD/ShiLtJ mouse strain are designated CHORI-29. All NOD mouse BAC end-sequences have been submitted to the International Nucleotide Sequence Database Consortium (INSDC), deposited in the NCBI trace archive. They have generated a clone map from these two libraries by mapping the BAC end-sequences to the latest assembly of the C57BL/6J mouse reference genome sequence. These BAC end-sequence alignments can then be visualized in the Ensembl mouse genome browser where the alignments of both NOD BAC libraries can be accessed through the Distributed Annotation System (DAS). The Mouse Genomes Project has used the Illumina platform to sequence the entire NOD/ShiLtJ genome and this should help to position unaligned BAC end-sequences to novel non-reference regions of the NOD genome. Further information about the BAC end-sequences, such as their alignment, variation data and Ensembl gene coverage, can be obtained from the NOD mouse ftp site.

Proper citation: Sequencing of Idd regions in the NOD mouse genome (RRID:SCR_001483) Copy   

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http://www.chickest.udel.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. A chicken EST Web site has been created to provide access to the data, and a set of unique sequences has been deposited with GenBank. This site contains over 40,000 EST sequences from the chicken cDNA libraries in the University of Delaware collection. Users can perform keyword searches, BLAST nucleotide sequences against our database, view clusters of similar or overlapping clones, and order clones. The cDNA and gene sequences of many mammalian cytokines and their receptors are known. However, corresponding information on avian cytokines is limited due to the lack of cross-species activity at the functional level or strong homology at the molecular level. To improve the efficiency of identifying cytokines and novel chicken genes, a directionally cloned cDNA library from T-cell-enriched activated chicken splenocytes was constructed, and the partial sequence of 5251 clones was obtained. Sequence clustering indicates that 2357 (42%) of the clones are present as a single copy, and 2961 are distinct clones, demonstrating the high level of complexity of this library. Comparisons of the sequence data with known DNA sequences in GenBank indicate that approximately 25% of the clones match known chicken genes, 39% have similarity to known genes in other species, and 11% had no match to any sequence in the database. Several previously uncharacterized chicken cytokines and their receptors were present in our library. This collection provides a useful database for cataloging genes expressed in T cells and a valuable resource for future investigations of gene expression in avian immunology. Therefore, the Chick EST database was created.

Proper citation: UD Chick EST Project (RRID:SCR_002236) Copy   

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http://soap.genomics.org.cn/

Software package that provides full solution to next generation sequencing data analysis consisting of an alignment tool (SOAPaligner/soap2), a re-sequencing consensus sequence builder (SOAPsnp), an indel finder ( SOAPindel ), a structural variation scanner ( SOAPsv ), a de novo short reads assembler ( SOAPdenovo ), and a GPU-accelerated alignment tool for aligning short reads with a reference sequence. (SOAP3/GPU)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SOAP (RRID:SCR_000689) Copy   

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http://www.genepaint.org/MapP56_01.htm

Abbreviated reference atlas for the P56 mouse. All sections were nissl stained and digitized. To assist in the initial identification of sites of gene expression sites, maps of brains are available for E15.5, P7 and the adult. These maps depict the boundaries of major brain regions (cortex, thalamus, striatum, globus pallidus, ventral striatum, septum, basal forebrain, hippocampus, midbrain, pons, medulla, cerebellum) and also show the more prominent nerve tracts. Maps are most efficiently used by placing the window depicting the map of interest next to the gene expression image. Browsing is permitted between planes of sectioning thus allowing the most appropriate plane to be selected. Abbreviations are found in a list accessed by clicking the see abbreviation link at the bottom of each map. Alternatively, passing the cursor directly across the abbreviation on the map will result in the appearance of the appropriate term in the rider on top of the map panel. The annotation of anatomical details such as brain nuclei is currently beyond the scope of the GenePaint database. Hence, such information on the anatomy of the brain and embryo should be obtained from published atlases of mouse anatomy (Kaufman, 1995; Paxinos and Franklin, 2001; Jacobowitz and Abbott, 1997; Schambra et al., 1992; Valverde1998).

Proper citation: GenePaint P56 Mouse Atlas (RRID:SCR_002788) Copy   

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http://mouse.brain-map.org/static/atlas

Allen Mouse Brain Atlas includes full color, high resolution anatomic reference atlas accompanied by systematic, hierarchically organized taxonomy of mouse brain structures. Enables interactive online exploration of atlas and to provide deeper level of 3D annotation for informatics analysis and viewing in Brain Explorer 3D viewer.

Proper citation: Allen Mouse Brain Reference Atlas (RRID:SCR_002978) Copy   

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https://dgrc.bio.indiana.edu/Home

Serves Drosophila research community by collecting and distributing DNA clones and vectors; collecting and distributing Drosophila cell lines; developing and testing genomics technologies for use in Drosophila and assisting members of the research community in their use.

Proper citation: Drosophila Genomics Resource Center (RRID:SCR_002845) Copy   

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http://ccr.coriell.org/Sections/Collections/NHGRI/?SsId=11

DNA samples and cell lines from fifteen populations, including the samples used for the International HapMap Project, the HapMap 3 Project and the 1000 Genomes Project (except for the CEPH samples). All of the samples were contributed with consent to broad data release and to their use in many future studies, including for extensive genotyping and sequencing, gene expression and proteomics studies, and all other types of genetic variation research. NHGRI led the contribution of the NIH to the International HapMap Project, which developed a haplotype map of the human genome. This haplotype map, called the HapMap is a publicly available tool that allows researchers to find genes and genetic variations that affect health and disease. The samples from four populations used to develop the HapMap were initially housed in the Human Genetic Cell Repository of the National Institute of General Medical Sciences (NIGMS). Except for the Utah CEPH samples that were in the NIGMS Repository before the initiation of the HapMap Project and remain there, the NHGRI Repository now houses all of the HapMap samples. The NHGRI repository also houses the extended set of HapMap samples, which includes additional samples from the HapMap populations and samples from seven additional populations. All of the samples were collected with extensive community engagement, including discussions with members of the donor communities about the ethical and social implications of human genetic variation research. These samples were studied as part of the HapMap 3 Project. The NHGRI repository also houses the samples for the International 1000 Genomes Project. This Project is lightly sequencing genome-wide 2500 samples from 27 populations. This project aims to provide a detailed map of human genetic variation, including common and rare SNPs and structural variants. This map will allow more precise localization of genomic regions that contribute to health and disease. The 1000 Genomes Project includes many of the samples from the HapMap and extended set of HapMap samples, as well as samples being collected from additional populations. Currently, samples from five additional populations are available; the others will become available during 2011 and 2012. No identifying or phenotypic information is available for the samples. Donors gave broad consent for use of the samples, including for genotyping, sequencing, and cellular phenotype studies. Samples collected from other populations for the study of human genetic variation may be added to the collection in the future. The NHGRI Repository distributes high quality lymphoblastoid cell lines and DNA from the samples to researchers. DNA is provided in plates or panels of 70 to 100 samples or as individual samples. Cell cultures and DNA samples are distributed only to qualified professional persons who are associated with recognized research, medical, educational, or industrial organizations engaged in health-related research or health delivery.

Proper citation: NHGRI Sample Repository for Human Genetic Research (RRID:SCR_004528) Copy   

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http://www.cs.cmu.edu/~jernst/stem/

The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database supporting GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Short Time-series Expression Miner (STEM) (RRID:SCR_005016) Copy   

•   Source: SciCrunch Registry