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http://www.crg.eu

International biomedical research institute created in December 2000 to discover and advance knowledge for benefit of society, public health and economic prosperity. Non profit foundation. Group leaders are recruited internationally and receive support from centre to set up and run their groups. External Scientific Advisory Board, made up of 15 world leaders in different areas, evaluates them.

Proper citation: Centre for Genomic Regulation; Barcelona; Spain (RRID:SCR_011147) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/seqtools

Software for sequence alignments that displays multiple match sequences aligned against a single genomic reference sequence. It can be used for manipulation, display and annotation of genomic data, to check the quality of an alignment, to find missing/misaligned sequence, and to identify splice sites and polyA sites.

Proper citation: Blixem (RRID:SCR_015994) Copy   

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http://starbase.sysu.edu.cn/index.php

Web based tool to visualize, analyze, discover and download of large-scale functional genomics data. Used for analysis of the CLIP-Seq and Degradome-Seq data sets, exploration of miRNA–target interactions and decoding RNA interaction networks from CLIP-Seq (HITS-CLIP, PAR-CLIP, iCLIP, CLASH) data. To show RNA-RNA and protein-RNA interaction networks in developmental, physiological and pathological processes.

Proper citation: Starbase V2.0 (RRID:SCR_016303) Copy   

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http://deweylab.biostat.wisc.edu/detonate/

Software tool to evaluate de novo transcriptome assemblies from RNA-Seq data. Consists of RSEM-EVAL and REF-EVAL packages. RSEM-EVAL is reference-free evaluation method. REF-EVAL is reference based and can be used to compare sets of any kinds of genomic sequences.

Proper citation: DETONATE (RRID:SCR_017035) Copy   

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http://bioinformatics.mdc-berlin.de/pigx/

Software application as a collection of genomic pipelines used for raw fastq read data of bisulfite experiments, RNAseq samples, single cell dropseq analysis, reads from ChIPseq experiments, analysis of sequence mutations in CRISPR-CAS9 targeted amplicon sequencing data.

Proper citation: PiGx (RRID:SCR_016476) Copy   

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https://software.broadinstitute.org/gatk/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 18th,2023. Software package for genome analysis. Used for analysis of next generation genomic data in cancer.

Proper citation: IndelGenotyper (RRID:SCR_016663) Copy   

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https://www.ncbi.nlm.nih.gov/Web/Search/entrezfs.html

Web portal for global query cross database search and retrieval system that provides access to all databases simultaneously with a single query string and user interface. Retrieves nucleotide and protein sequence data, gene centered and genomic mapping information, 3D structures, and references. Covers databases including protein sequence data from PIR-International, PRF, Swiss-Prot, and PDB and nucleotide sequence data from GenBank that includes information from EMBL and DDBJ.

Proper citation: Entrez (RRID:SCR_016640) Copy   

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http://bioconductor.org/packages/GenomicFeatures/

Software R package for making and manipulating transcript centric annotations. Used to download the genomic locations of the transcripts, exons and cds of a given organism, from either the UCSC Genome Browser or a BioMart database.

Proper citation: GenomicFeatures (RRID:SCR_016960) Copy   

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http://degradome.uniovi.es

A database of human, chimpanzee, mouse, and rat proteases and protease inhibitors, as well as as the growing number of hereditary diseases caused by mutations in protease genes. Analysis of the human and mouse genomes has allowed us to annotate 581 human, 580 chimpanzee, 667 mouse, and 655 rat protease genes. Proteases are classified in five different classes according to their mechanism of catalysis. Proteases are a diverse and important group of enzymes representing >2% of the human, chimpanzee, mouse and rat genomes. This group of enzymes is implicated in numerous physiological processes. The importance of proteases is illustrated by the existence of 99 different hereditary diseases due to mutations in protease genes. Furthermore, proteases have been implicated in multiple human pathologies, including vascular diseases, rheumatoid arthritis, neurodegenerative processes, and cancer. During the last ten years, our laboratory has identified and characterized more than 60 human protease genes. Due to the importance of proteolytic enzymes in human physiology and pathology, we have recently introduced the concept of Degradome, as the complete repertoire of proteases expressed by a tissue or organism. Thanks to the recent completion of the human, chimpanzee, mouse, and rat genome sequencing projects, we were able to analyze and compare for the first time the complete protease repertoire in those mammalian organisms, as well as the complement of protease inhibitor genes. This webpage also contains the Supplementary Material of Human and mouse proteases: a comparative genomic approach Nat Rev Genet (2003) 4: 544-558, Genome sequence of the brown Norway rat yields insights into mammalian evolution Nature (2004) 428: 493-521, A genomic analysis of rat proteases and protease inhibitors Genome Res. (2004) 14: 609-622, and Comparative genomic analysis of human and chimpanzee proteases Genomics (2005) 86: 638-647.

Proper citation: Mammalian Degradome Database (RRID:SCR_007624) Copy   

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http://www.ncbi.nlm.nih.gov/genomes/GenomesHome.cgi?taxid=2759&hopt=html

Curated sequence data and related information on organelles from NCBI Refseq for the community to use as a standard. The animal mitochondrial records are considered reviewed; that is, they have been manually curated by the NCBI staff. Other mitochondrial and chloroplast genome records are provisional and are presented with varying levels of review compared to the primary record used to build the RefSeq. Additionally, protein clusters for the metazoan and plastid genomes proteins can be reviewed with Entrez Protein Clusters.

Proper citation: Organelle Genome Resources (RRID:SCR_007838) Copy   

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http://statgen.ncsu.edu/asg/

Alternative splicing essentially increases the diversity of the transcriptome and has important implications for physiology, development and the genesis of diseases. This resource uses a different approach to investigate alternative splicing (instead of the conventional case-by case fashion) and integrates all transcripts derived from a gene into a single splicing graph. ASG is a database of splicing graphs for human genes, using transcript information from various major sources (Ensembl, RefSeq, STACK, TIGR and UniGene). Each transcript corresponds to a path in the graph, and alternative splicing is displayed by bifurcations. This representation preserves the relationships between different splicing variants and allows us to investigate systematically all possible putative transcripts. Web interface allows users to display the splicing graphs, to interactively assemble transcripts and to access their sequences as well as neighboring genomic regions. ASG also provide for each gene, an exhaustive pre-computed catalog of putative transcriptsin total more than 1.2 million sequences. It has found that ~65 of the investigated genes show evidence for alternative splicing, and in 5 of the cases, a single gene might produce over 100 transcripts.

Proper citation: Alternate splicing gallery (RRID:SCR_008129) Copy   

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https://wiki.cgb.indiana.edu/display/DGC/Home

The Daphnia Genomics Consortium (DGC) is an international network of investigators committed to mounting the freshwater crustacean Daphnia as a model system for ecology, evolution and the environmental sciences. Along with research activities, the DGC is: (1) coordinating efforts towards developing the Daphnia genomic toolbox, which will then be available for use by the general community; (2) facilitating collaborative cross-disciplinary investigations; (3) developing bioinformatic strategies for organizing the rapidly growing genome database; and (4) exploring emerging technologies to improve high throughput analyses of molecular and ecological samples. If we are to succeed in creating a new model system for modern life-sciences research, it will need to be a community-wide effort. Research activities of the DGC are primarily focused on creating genomic tools and information. When completed, the current projects will offer a first view of the Daphnia genome''s topography, including regions of high and low recombination, the distribution of transposable, repetitive and regulatory elements, the size and structure of genes and of their neighborhoods. This information is crucial in formulating testable hypotheses relating genetics and demographics to the evolutionary potential or constraints of natural populations. Projects aiming to compile identifiable genes with their function are also underway, together with robust methods to verify these findings. Finally, these tools are being tested, by exploring their uses in key ecological and toxicological investigations. Each project benefits from the leadership and expertise of many individuals. For further details, begin by contacting the project directors. The DGC consists of biologists from a broad spectrum of subdisciplines, including limnology, ecotoxicology, quantitative and population genetics, systematics, molecular biology and evolution, developmental biology, genomics and bioinformatics. In many regards, the rapid early success of the consortium results from its grass-roots origin promoting an international composition, under a cooperative model, with significant scientific breadth. We hold to this approach in building this network and encourage more people to participate. All the while, the DGC is structured to effectively reach specific goals. The consortium includes an advisory board (composed of experts of the various subdisciplines), whose responsibility is to act as the research community''s agent in guiding the development of Daphnia genomic resources. The advisors communicate directly to DGC members, who are either contributing genomic tools or actively seeking funds for this function. The consortium''s main body (given the widespread interest in applying genomic tools in environmental studies) are the affiliates, who make use of these tools for their research and who are soliciting support.

Proper citation: Daphnia genomics consortium (RRID:SCR_008148) Copy   

•   Source: SciCrunch Registry

http://baygenomics.ucsf.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The BayGenomics gene-trap resource provides researchers with access to thousands of mouse embryonic stem (ES) cell lines harboring characterized insertional mutations in both known and novel genes. The major goal of BayGenomics is to identify genes relevant to cardiovascular and pulmonary disease.

Proper citation: BayGenomics (RRID:SCR_008168) Copy   

•   Source: SciCrunch Registry

http://www.uni-wh.de/pcogr

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 20,2019.The COG-database has become a powerful tool in the field of comparative genomics. The construction of this data-base is based on sequence homologies of proteins from different completely sequenced genomes. Highly homologous proteins are assigned to clusters of orthologous groups. The updated collection of orthologous protein sets for prokaryotes and eukaryotes is expected to be a useful platform for functional annotation of newly sequenced genomes, including those of complex eukaryotes, and genome-wide evolutionary studies. The availability of multiple, essentially complete genome sequences of prokaryotes and eukaryotes spurred both the demand and the opportunity for the construction of an evolutionary classification of genes from these genomes. Such a classification system based on orthologous relationships between genes appears to be a natural framework for comparative genomics and should facilitate both functional annotation of genomes and large-scale evolutionary studies. Here is a major update of the previously developed system for delineation of Clusters of Orthologous Groups of proteins (COGs) from the sequenced genomes of prokaryotes and unicellular eukaryotes and the construction of clusters of predicted orthologs for 7 eukaryotic genomes, which we named KOGs after eukaryotic orthologous groups. The COG collection currently consists of 138,458 proteins, which form 4873 COGs and comprise 75% of the 185,505 (predicted) proteins encoded in 66 genomes of unicellular organisms. The eukaryotic orthologous groups (KOGs) include proteins from 7 eukaryotic genomes: three animals (the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster and Homo sapiens), one plant, Arabidopsis thaliana, two fungi (Saccharomyces cerevisiae and Schizosaccharomyces pombe), and the intracellular microsporidian parasite Encephalitozoon cuniculi. The current KOG set consists of 4852 clusters of orthologs, which include 59,838 proteins, or approximately 54% of the analyzed eukaryotic 110,655 gene products. Compared to the coverage of the prokaryotic genomes with COGs, a considerably smaller fraction of eukaryotic genes could be included into the KOGs; addition of new eukaryotic genomes is expected to result in substantial increase in the coverage of eukaryotic genomes with KOGs. Examination of the phyletic patterns of KOGs reveals a conserved core represented in all analyzed species and consisting of approximately 20% of the KOG set. This conserved portion of the KOG set is much greater than the ubiquitous portion of the COG set (approximately 1% of the COGs). In part, this difference is probably due to the small number of included eukaryotic genomes, but it could also reflect the relative compactness of eukaryotes as a clade and the greater evolutionary stability of eukaryotic genomes.

Proper citation: Phylogenetic Clusters of Orthologous Groups Ranking (RRID:SCR_008223) Copy   

•   Source: SciCrunch Registry

http://www.nisc.nih.gov/projects/comp_seq.html

Generates data for use in developing and refining computational tools for comparing genomic sequence from multiple species. The NISC Comparative Sequencing Program's goal is to establish a data resource consisting of sequences for the same set of targeted genomic regions derived from multiple animal species. The broader program includes plans for a diverse set of analytical studies using the generated sequence and the publication of a series of papers describing the results of those analysis in peer-reviewed journals in a timely fashion. Experimentally, this project involves the shotgun sequencing of mapped BAC clones. For each BAC, an assembly is first performed when a sufficient number of sequence reads have been generated to provide full shotgun coverage of the clone. At that time, the assembled sequence is submitted to the HTGS division of GenBank. Subsequent refinements of the sequence, including the generation of higher-accuracy finished sequence, results in the updating of the sequence record in GenBank. By immediately submitting our BAC-derived sequences to GenBank, it makes their data available as a public service to allow colleagues to speed up their research, consistent with the now well-established routine of sequencing centers participating in the Human Genome Project. However, at the same time, it has made considerable investment in acquiring these mapping and sequence data, including sizable efforts of graduate students, postdoctoral fellows, and other trainees. Furthermore, in most cases, large data sets involving multiple BAC sequences from multiple species must first be generated, often taking many months to accumulate, before the planned analysis can be performed and the resulting papers written and submitted for publication.

Proper citation: Comparative Vertebrate Sequencing (RRID:SCR_008213) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://www.uclahealth.org/departments/pathology/research-services/technology-center-genomics-bioinformatics-tcgb

Core is a fully automated, high-throughput genomic Center equipped with next generation sequencing and microarray platforms. TCGB provides genomics technologies, comprehensive services, specialized expertise and a wide range of trainings, enabling these services to serve basic science and translational/clinical research. In addition, TCGB provides pre-experiment consultation and post-experiment support, including preparation of grant applications, publications, and strategic planning for additional research steps. TCGB also provides educational training to faculty, staff, and students to raise awareness of new directions and major discoveries in the areas of genomics and bioinformatics.

Proper citation: University of California Los Angeles Technology Center for Genomics and Bioinformatics Core Facility (RRID:SCR_012204) Copy   

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http://cccb.dfci.harvard.edu

Core facility that provides the following services: Microarray and other genomic data analysis, MiSeq. The Center provides broad-based support for the generation, analysis, and interpretation of genomic and other large-scale data in the context of basic, clinical and translational research. The CCCB has three primary elements. * The CCCB sequencing facility offers a wide range of services to assist in the design and execution of next-generation sequencing projects. Utilizing the Illumina (Solexa) sequencing technology, they currently support a number of applications inlcuding ChIP-Seq, RNA-Seq, whole genome, whole exome, and targeted re-sequencing. * The analytical services and support platform aims to provide state-of-the-art assistance in the collection, management, analysis, and interpretation of large-scale data with a focus on data generated using ''''omic technologies. In addition, they offer software, services, and training designed to assist investigators in advancing their research. * The CCCB research program is focused on development of new methods for improving analysis and interpretation of genomic data through integration of diverse data types with the goal of creating open-source software tools to be made freely-available to the research community.

Proper citation: DFCI Center for Cancer Computational Biology (RRID:SCR_012688) Copy   

•   Source: SciCrunch Registry

http://faculty.washington.edu/browning/floss/floss.htm

Software application that performs ordered subset analysis using MERLIN's ouput .lod file created with the --perFamily option. Ordered subset analysis uses covariate information to identify a more homogenous subset of families for linkage analysis. The homogeneous subset of families does not need to be specified a priori, and the covariates can include environmental exposures, quantitative traits, or linkage scores at another locus in the genome. The evidence for linkage is evaluated with a permutation test. (entry from Genetic Analysis Software)

Proper citation: FLOSS (RRID:SCR_000836) Copy   

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http://null

Software application for calculating the heterozygosity, PIC, and LIC values for polymorphic markers (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: POLYMORPHISM (RRID:SCR_000828) Copy   

•   Source: SciCrunch Registry