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http://www.genoscope.cns.fr/externe/tetraodon/

The initial objective of Genoscope was to compare the genomic sequences of this fish to that of humans to help in the annotation of human genes and to estimate their number. This strategy is based on the common genetic heritage of the vertebrates: from one species of vertebrate to another, even for those as far apart as a fish and a mammal, the same genes are present for the most part. In the case of the compact genome of Tetraodon, this common complement of genes is contained in a genome eight times smaller than that of humans. Although the length of the exons is similar in these two species, the size of the introns and the intergenic sequences is greatly reduced in this fish. Furthermore, these regions, in contrast to the exons, have diverged completely since the separation of the lineages leading to humans and Tetraodon. The Exofish method, developed at Genoscope, exploits this contrast such that the conserved regions which can be identified by comparing genomic sequences of the two species, correspond only to coding regions. Using preliminary sequencing results of the genome of Tetraodon in the year 2000, Genoscope evaluated the number of human genes at about 30,000, whereas much higher estimations were current. The progress of the annotation of the human genome has since supported the Genoscope hypothesis, with values as low as 22,000 genes and a consensus of around 25,000 genes. The sequencing of the Tetraodon genome at a depth of about 8X, carried out as a collaboration between Genoscope and the Whitehead Institute Center for Genome Research (now the Broad Institute), was finished in 2002, with the production of an assembly covering 90 of the euchromatic region of the genome of the fish. This has permitted the application of Exofish at a larger scale in comparisons with the genome of humans, but also with those of the two other vertebrates sequenced at the time (Takifugu, a fish closely related to Tetraodon, and the mouse). The conserved regions detected in this way have been integrated into the annotation procedure, along with other resources (cDNA sequences from Tetraodon and ab initio predictions). Of the 28,000 genes annotated, some families were examined in detail: selenoproteins, and Type 1 cytokines and their receptors. The comparison of the proteome of Tetraodon with those of mammals has revealed some interesting differences, such as a major diversification of some hormone systems and of the collagen molecules in the fish. A search for transposable elements in the genomic sequences of Tetraodon has also revealed a high diversity (75 types), which contrasts with their scarcity; the small size of the Tetraodon genome is due to the low abundance of these elements, of which some appear to still be active. Another factor in the compactness of the Tetraodon genome, which has been confirmed by annotation, is the reduction in intron size, which approaches a lower limit of 50-60 bp, and which preferentially affects certain genes. The availability of the sequences from the genomes of humans and mice on one hand, and Takifugu and Tetraodon on the other, provide new opportunities for the study of vertebrate evolution. We have shown that the level of neutral evolution is higher in fish than in mammals. The protein sequences of fish also diverge more quickly than those of mammals. A key mechanism in evolution is gene duplication, which we have studied by taking advantage of the anchoring of the majority of the sequences from the assembly on the chromosomes. The result of this study speaks strongly in favor of a whole genome duplication event, very early in the line of ray-finned fish (Actinopterygians). An even stronger evidence came from synteny studies between the genomes of humans and Tetraodon. Using a high-resolution synteny map, we have reconstituted the genome of the vertebrate which predates this duplication - that is, the last common ancestor to all bony vertebrates (most of the vertebrates apart from cartilaginous fish and agnaths like lamprey). This ancestral karyotype contains 12 chromosomes, and the 21 Tetraodon chromosomes derive from it by the whole genome duplication and a surprisingly small number of interchromosomal rearrangements. On the contrary, exchanges between chromosomes have been much more frequent in the lineage that leads to humans. Sponsors: The project was supported by the Consortium National de Recherche en Genomique and the National Human Genome Research Institute.

Proper citation: Tetraodon Genome Browser (RRID:SCR_007079) Copy   

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http://weizhong-lab.ucsd.edu/cd-hit/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software program for clustering biological sequences with many applications in various fields such as making non-redundant databases, finding duplicates, identifying protein families, filtering sequence errors and improving sequence assembly etc. It is very fast and can handle extremely large databases. CD-HIT helps to significantly reduce the computational and manual efforts in many sequence analysis tasks and aids in understanding the data structure and correct the bias within a dataset. The CD-HIT package has CD-HIT, CD-HIT-2D, CD-HIT-EST, CD-HIT-EST-2D, CD-HIT-454, CD-HIT-PARA, PSI-CD-HIT, CD-HIT-OTU and over a dozen scripts. * CD-HIT (CD-HIT-EST) clusters similar proteins (DNAs) into clusters that meet a user-defined similarity threshold. * CD-HIT-2D (CD-HIT-EST-2D) compares 2 datasets and identifies the sequences in db2 that are similar to db1 above a threshold. * CD-HIT-454 identifies natural and artificial duplicates from pyrosequencing reads. * CD-HIT-OTU cluster rRNA tags into OTUs The usage of other programs and scripts can be found in CD-HIT user''s guide. CD-HIT was originally developed by Dr. Weizhong Li at Dr. Adam Godzik''s Lab at the Burnham Institute (now Sanford-Burnham Medical Research Institute)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CD-HIT (RRID:SCR_007105) Copy   

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http://hcv.lanl.gov/content/immuno/immuno-main.html

The HCV Immunology Database contains a curated inventory of immunological epitopes in HCV and their interaction with the immune system, with associated retrieval and analysis tools. The funding for the HCV database project has stopped, and this website and the HCV immunology database are no longer maintained. The site will stay up, but problems will not be fixed. The database was last updated in September 2007. The HIV immunology website contains the same tools, and may be usable for non-HCV-specific analyses. For new epitope information, users of this database can try the Immuno Epitope Database (http://www.immuneepitope.org).

Proper citation: HCV Immunology Database (RRID:SCR_007086) Copy   

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http://www.thebiogrid.org/

Curated protein-protein and genetic interaction repository of raw protein and genetic interactions from major model organism species, with data compiled through comprehensive curation efforts.

Proper citation: Biological General Repository for Interaction Datasets (BioGRID) (RRID:SCR_007393) Copy   

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http://www.e-cell.org/

Software platform, general technologies and theoretical supports for computational biology with the grand aim to make precise whole cell simulation at the molecular level possible.Technologies include formalisms and techniques, including technologies to predict, obtain or estimate parameters such as reaction rates and concentrations of molecules in the cell. The E-Cell System is a software platform for modeling, simulation and analysis of complex, heterogeneous and multi-scale system like the cell. The E-Cell Project is open to anyone who shares the view with u that development of cell simulation technology, and, even if such ultimate goal might not be within ten years of reach yet, solving various conceptual, computational and experimental problems that will continue to arise in the course of pursuing it, may have a multitude of eminent scientific, medical and engineering impacts on our society.

Proper citation: Electronic Cell Project (RRID:SCR_007381) Copy   

•   Source: SciCrunch Registry

http://consurfdb.tau.ac.il/

Collection of pre-calculated evolutionary conservation profiles for proteins of known structure in the Protein DataBase (PDB).

Proper citation: ConSurf-DB (RRID:SCR_007609) Copy   

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http://www.hpid.org

Database that provides human protein interaction information and integrated interaction and also finds proteins from databases that can potentially react with proteins submitted by users. The human protein interaction information was pre-computed by a statistical method from existing structural and experimental data, while the integrated human protein interactions are derived from BIND, DIP and HPRD. A score composed of three parts is assigned to the predicted interaction data, and those interactions with high scores were found reliable. HPID allows the user to use the protein IDs in EMBL, Ensembl, MIM, RefSeq, HPRD and NCBI to search protein interactions of interest. A set of web-based software tools has also been developed so that users can visualize and analyze protein interaction networks.

Proper citation: HPID - Human Protein Interaction database (RRID:SCR_007724) Copy   

•   Source: SciCrunch Registry

http://fmf.igh.cnrs.fr/ISSAID/infevers

Registry for Familial Mediterranean Fever (FMF) and hereditary inflammatory disorders mutations. As of 2014, it includes twenty genes including: MEFV, MVK, TNFRSF1A, NLRP3, NOD2, PSTPIP1, LPIN2 and NLRP7, and contains over 1338 sequence variants. Confidential data, simple and complex alleles are accepted. For each gene, a menu offers: 1) a tabular list of the variants that can be sorted by several parameters; 2) a gene graph providing a schematic representation of the variants along the gene; 3) statistical analysis of the data according to the phenotype, alteration type, and location of the mutation in the gene; 4) the cDNA and gDNA sequences of each gene, showing the nucleotide changes along the sequence, with a color-based code highlighting the gene domains, the first ATG, and the termination codon; and 5) a download menu making all tables and figures available for the users, which, except for the gene graphs, are all automatically generated and updated upon submission of the variants. The entire database was curated to comply with the HUGO Gene Nomenclature Committee (HGNC) and HGVS nomenclature guidelines, and wherever necessary, an informative note was provided.

Proper citation: INFEVERS (RRID:SCR_007738) Copy   

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http://thomsonreuters.com/metacore/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. An integrated software suite for functional analysis of experimental data. The scope of data types includes microarray and SAGE gene expression, SNPs and CGH arrays, proteomics, metabolomics, pathway analysis, Y2H and other custom interactions. MetaCore is based on a proprietary manually curated database of human protein-protein, protein-DNA and protein compound interactions, metabolic and signaling pathways and the effects of bioactive molecules in gene expression.

Proper citation: MetaCore (RRID:SCR_008125) Copy   

•   Source: SciCrunch Registry

http://caps.ncbs.res.in/imotdb/

The interacting motif database or iMOTdb , lists interacting motifs that are identified for all structural entries in the PDB. The conserved patterns or finger prints are identified for individual structural entries and also grouped together for reporting the common motifs shared among all superfamily members. The iMOT package has been employed for identifying the motifs in the database. Realization of conserved residues that represent a protein family is crucial for clearer understanding of biological function as well as for the better recognition of additional members in sequence databases. Functionally important residues are recognized well due to their high degree of conservation in closely related sequences and are annotated in functional motif databases. Structural motifs are central to the integrity of the fold and require careful analysis for their identification. It reports the availability of a database of spatially interacting motifs in single protein structures as well as those among distantly related protein structures that belong to a superfamily. Spatial interactions amongst conserved motifs are automatically measured using sequence similarity scores and distance calculations. Interactions between pairs of conserved motifs are described in the form of pseudoenergies. iMOTdb database provides information for 854,488 motifs corresponding to 60,849 protein structural domains and 22,648 protein structural entries. Interacting motifs has been shown to assist our understanding of proteins structure and function. Information on such motifs should be of valuable in protein folding, modeling and engineering experiments. As shown in previous studies conserved spatially interacting motifs act as important constraint in pattern based remote homology search methods. The iMOT DB is provided with links to aid sequence search protocol using PHI-BLAST and SCAN MOT employing the interacting motifs. The interacting motifs representing the superfamilies of proteins are derived from structural alignments obtained from PASS2. These motifs are finger prints for a given protein family and provides useful insights regarding the structural and functional role regarding the protein. Pseudo potential evaluated between the various pairs of motifs reflects the interacting strength between the regions and highlights the thermodynamic stability of the local substructure. The database would thus provide useful insight into the understanding of the folding, structural modeling and envisaging mutational exercise on a given polypeptide.

Proper citation: Database of Spatially Interacting Motifs in Proteins (RRID:SCR_008194) Copy   

•   Source: SciCrunch Registry

http://wwwmgs.bionet.nsc.ru/mgs/gnw/about.shtml

GeneNetWorks is designed for accumulation of experimental data, data navigation, data analysis, and analysis of dependencies in the field of gene expression regulation. It integrates the databases and programs for processing the data about structure and function of DNA, RNA, and proteins, together with the other information resources important for gene expression description. The unique property of above described system is that all the resources within the system GeneNetWorks are divided according to the natural hierarchy of molecular genetic systems and has the following levels: (1) DNA; (2) RNA; (3) proteins; and (4) gene networks. Each module contains: 1) experimental data represented as a database or some sample; 2) program for data analysis; 3) results of an automated data processing; 4) tools for the graphical representation of these data and the results of the data analyses.

Proper citation: GeneNetWorks (RRID:SCR_008034) Copy   

•   Source: SciCrunch Registry

http://www.gene-regulation.com/pub/databases.html

In an effort to strongly support the collaborative nature of scientific research, BIOBASE offers academic and non-profit organizations free access to reduced functionality versions of their products. TRANSFAC Professional provides gene regulation analysis solutions, offering the most comprehensive collection of eukaryotic gene regulation data. The professional paid subscription gives customers access to up-to-date data and tools not available in the free version. The public databases currently available for academic and non-profit organizations are: * TRANSFAC: contains data on transcription factors, their experimentally-proven binding sites, and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. * TRANSPATH: provides data about molecules participating in signal transduction pathways and the reactions they are involved in, resulting in a complex network of interconnected signaling components.TRANSPATH focuses on signaling cascades that change the activities of transcription factors and thus alter the gene expression profile of a given cell. * PathoDB: is a database on pathologically relevant mutated forms of transcription factors and their binding sites. It comprises numerous cases of defective transcription factors or mutated transcription factor binding sites, which are known to cause pathological defects. * S/MARt DB: presents data on scaffold or matrix attached regions (S/MARs) of eukaryotic genomes, as well as about the proteins that bind to them. S/MARs organize the chromatin in the form of functionally independent loop domains gained increasing support. Scaffold or Matrix Attached Regions (S/MARs) are genomic DNA sequences through which the chromatin is tightly attached to the proteinaceous scaffold of the nucleus. * TRANSCompel: is a database on composite regulatory elements affecting gene transcription in eukaryotes. Composite regulatory elements consist of two closely situated binding sites for distinct transcription factors, and provide cross-coupling of different signaling pathways. * PathoSign Public: is a database which collects information about defective cell signaling molecules causing human diseases. While constituting a useful data repository in itself, PathoSign is also aimed at being a foundational part of a platform for modeling human disease processes.

Proper citation: Gene Regulation Databases (RRID:SCR_008033) Copy   

•   Source: SciCrunch Registry

http://www.genomatix.de/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 13,2026. Genomatix is a privately held company that offers software, databases, and services aimed at understanding gene regulation at the molecular level representing a central part of systems biology. Its multilayer integrative approach is a working implementation of systems biology principles. Genomatix combines sequence analysis, functional promoter analysis, proprietary genome annotation, promoter sequence databases, comparative genomics, scientific literature data mining, pathway databases, biological network databases, pathway analysis, network analysis, and expression profiling into working solutions and pipelines. It also enables better understanding of biological mechanisms under different conditions and stimuli in the biological context of your data. Some of Genomatix'' most valuable assets are the strong scientific background and the years of experience in research & discovery as well as in development & application of scientific software. Their firsthand knowledge of all the complexities involved in the in-silico analysis of biological data makes them a first-rate partner for all scientific projects involving the evaluation of gene regulatory mechanisms. The Genomatix team has more than a decade of scientific expertise in the successful application of computer aided analysis of gene regulatory networks, which is reflected by more than 150 peer reviewed scientific publications from Genomatix'' scientists More than 35,000 researchers in industry and academia around the world use this technology. The software available in Genomatix are: - GenomatixSuite: GenomatixSuite is our comprehensive software bundle including ElDorado, Gene2Promoter, GEMS Launcher, MatInspector and MatBase. GenomatixSuite PE also includes BiblioSphere Pathway Edition. Chromatin IP Software - RegionMiner: Fast, extensive analysis of genomic regions. - ChipInspector: Discover the real power of your microarray data. Genome Annotation Software - ElDorado: Extended Genome Annotation. - Gene2Promoter: Retrieve & analyze promoters - GPD: The Genomatix Promoter Database, which is now included with Gene2Promoter. Knowledge Mining Software - BiblioSpere : The next level of pathway/genomics analysis. - LitInspector: Literature and pathway analysis for free. Sequence Analysis Software - GEMS Launcher: Our integrated collection of sequence analysis tools. - MalInspector: Search transcription factor binding sites - MatBase: The transcription factor knowledge base. Other (no registration required) Software - DiAlign: Multiple alignment of DNA/protein sequence. - Genomatix tools: Various small tools for sequence statistics, extraction, formatting, etc.

Proper citation: Genomatix Software: Understanding Gene Regulation (RRID:SCR_008036) Copy   

•   Source: SciCrunch Registry

http://www.osc.riken.jp/english/

Omics Science Center is aiming to develop a comprehensive system called Life Science Accelerator(LSA) for the advancement of omics research. The LSA is a comprehensive system consists of biological resources, human resources, technologies, know-how, and essential administrative ability. Ultimate goal of LSA is to support and accelerate the advancement in life science research. Omics is the comprehensive study of molecules in living organisms. The complete sequencing of genomes (the complete set of genes in an organism) has enabled rapid developments in the collection and analysis of various types of comprehensive molecular data such as transcriptomes (the complete set of gene expression data) and proteomes (the complete set of intracellular proteins). Fundamental omics research aims to link these omics data to molecular networks and pathways in order to advance the understanding of biological phenomena as systems at the molecular level.

Proper citation: RIKEN Omics Science Center (RRID:SCR_008241) Copy   

•   Source: SciCrunch Registry

http://abgent.com

Antibody supplier.

Proper citation: Abgent (RRID:SCR_008393) Copy   

•   Source: SciCrunch Registry

http://salilab.org/modeller/modeller.html

Software tool as Program for Comparative Protein Structure Modelling by Satisfaction of Spatial Restraints. Used for homology or comparative modeling of protein three dimensional structures. User provides alignment of sequence to be modeled with known related structures and MODELLER automatically calculates model containing all non hydrogen atoms.

Proper citation: MODELLER (RRID:SCR_008395) Copy   

•   Source: SciCrunch Registry

http://www.microsens.co.uk/

Commercial organization specializing in bacterial detection including tuberculosis, therapeutic protein and protein aggregation diseases. * Tools for rapid and simple bacteria and virus extraction including tuberculosis * Seprion technology for the detection and study of protein aggregates and protein aggregation diseases * LiMA technology for the ultra sensitive detection of bacteria and bacterial contamination

Proper citation: Microsens (RRID:SCR_003906) Copy   

•   Source: SciCrunch Registry

http://www.inspiralis.com/

Commercial organization supplying topoisimerase products and services to the pharmaceutical industry and academia to aid research in the anti-infectives and anti-cancer markets. Their aim is to provide pharmaceutical companies, and others involved in drug development, with the necessary tools to develop and screen novel anti-infective and anti-cancer compounds. Products All their proteins are expressed as the native sequences without additional tags. The only exception is the M. tuberculosis gyrase which is currently produced with a C-terminal His tag. An untagged version of this protein will be available soon. * Topoisomerase Enzymes and Assay Kits * Specific Gyrase Protein Domains * DNA Substrates and Markers * Antibodies Services * Gel Based Assays * Medium / High Throughput Assay * Investigation protein DNA interaction ReDCaT chip

Proper citation: Inspiralis (RRID:SCR_004082) Copy   

•   Source: SciCrunch Registry

http://www.biomol-informatics.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 12, 2021. Technology based company in Madrid that offers consulting services on Bioinformatics in areas of research, diagnostics and pharmaceutical industry.

Proper citation: Biomol-Informatics (RRID:SCR_004081) Copy   

•   Source: SciCrunch Registry

http://iubio.bio.indiana.edu/webapps/SeWeR/

Sequence analysis using Web Resources (SeWeR) is an integrated, Dynamic HTML (DHTML) interface to commonly used bioinformatics services available on the World Wide Web. It is highly customizable, extendable, platform neutral, completely server-independent and can be hosted as a web page as well as being used as stand-alone software running within a web browser. It doesn''t require any server to host itself. The goal of SeWeR is to turn your web-browser into a powerful sequence-analysis tool. It is written entirely in JavaScript1.2. SeWeR can be downloaded and mirrored freely. The whole package is just around 300K. You can even run it from a floppy. SeWeR is not compatible with Netscape 6. SeWeR now generates graphics. Savvy is a plasmid drawing software that generates plasmid map in the revolutionary Scalable Vector Graphics format from W3C.

Proper citation: SeWeR - SEquence analysis using WEb Resources (RRID:SCR_004167) Copy   

•   Source: SciCrunch Registry