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http://www.pdbj.org/

PDBj (Protein Data Bank Japan) maintains a centralized PDB archive of macromolecular structures and provides integrated tools, in collaboration with the RCSB, the BMRB in USA and the PDBe in EU.

Proper citation: PDBj - Protein Data Bank Japan (RRID:SCR_008912) Copy   

•   Source: SciCrunch Registry

http://hymenopteragenome.org/beebase/

Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.

Proper citation: BeeBase (RRID:SCR_008966) Copy   

•   Source: SciCrunch Registry

http://www.psort.org

Portal to the PSORT family of computer programs for the prediction of protein localization sites in cells, as well as other datasets and resources relevant to localization prediction. The standalone versions are available for download for larger analyses.

Proper citation: Psort (RRID:SCR_007038) Copy   

•   Source: SciCrunch Registry

http://prodom.prabi.fr/

Comprehensive set of protein domain families automatically generated from UniProt Knowledge Database. Automated clustering of homologous domains generated from global comparison of all available protein sequences., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ProDom (RRID:SCR_006969) Copy   

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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   

•   Source: SciCrunch Registry

http://medgen.ugent.be/rtprimerdb/

Database for primer and probe sequences used in real-time PCR assays employing popular chemistries (SYBR Green I, Taqman, Hybridization Probes, Molecular Beacon) to prevent time-consuming primer design and experimental optimization, and to introduce a certain level of uniformity and standardization among different laboratories. Researchers are encouraged to submit their validated primer and probe sequence, so that other users can benefit from their expertise. The database can be queried using the official gene name or symbol, Entrez or Ensembl Gene identifier, SNP identifier, or oligonucleotide sequence. Different options make it possible to restrict a query to a particular application (Gene Expression Quantification/Detection, DNA Copy Number Quantification/Detection, SNP Detection, Mutation Analysis, Fusion Gene Quantification/Detection, Chromatin immunoprecipitation (ChIP)), organism (Human, Mouse, Rat, and others) or detection chemistry.

Proper citation: RTPrimerDB- The Real-Time PCR and Probe Database (RRID:SCR_007106) 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://cagt.bu.edu/page/PRECISE_about

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Database of interactions between amino acid residues of enzyme and its ligands. Provides summary of interactions between amino acid residues of enzyme and its various ligands including substrate and transition state analogues, cofactors, inhibitors, and products., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRECISE (RRID:SCR_007874) 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://dictybase.org

This website contains the genome sequence of Dictyostelium discoideum. The determination of the entire information content of the Dictyostelium genome will be of great value to those working with this organism directly, as well as to those who would like to determine the functions of homologous genes from other species. Dictyostelium discoideum, a soil-living amoeba, is an excellent organism for the study of the molecular mechanisms of cell motility, signal transduction, cell-type differentiation and developmental processes. Genes involved in any of these processes can be knocked-out rapidly by targeted homologous recombination. Since Dictyostelium is haploid, mutants are readily isolated and the REMI (restriction enzyme mediated integration) technique of insertional mutagenesis allows the facile cloning of disrupted genes. The Dictyostelium genome is being sequenced with the chromosomal shotgun methodology on a chromosome by chromosome basis. The six Dictyostelium chromosomes with sizes ranging from four to seven Mb are being separated by PFGE (Pulsed Field Gel Electrophoresis) by Edward Cox, Princeton University. Chromosomal libraries with insert sizes between 1 and 4 kb are being generated by the Sanger Centre using pUC18 as a vector. For shotgun sequencing both forward and reverse reads from each clone randomly selected from the chromosome-enriched libraries are being produced. The read pairs will represent a useful mapping resource to assess contig order. For every Mb of DNA an estimated number of 20,000 - 25,000 single shotgun reads will be necessary. The hereditary information is carried on 6 chromosomes with sizes ranging from 4 to 7 Mb resulting in a total of about 34 Mb of DNA, a multicopy 90 kb extrachromosomal element that harbours the rRNA genes, and the 55 kb mitochondrial genome. The estimated number of genes in the genome is 8,000 to 10,000 and many of the known genes show a high degree of sequence similarity to homologues in vertebrate species.

Proper citation: Dictyostelium discoideum genome database (RRID:SCR_008149) Copy   

•   Source: SciCrunch Registry

http://nematode.lab.nig.ac.jp/

Expression pattern map of the 100Mb genome of the nematode Caenorhabditis elegans through EST analysis and systematic whole mount in situ hybridization. NEXTDB is the database to integrate all information from their expression pattern project and to make the data available to the scientific community. Information available in the current version is as follows: * Map: Visual expression of the relationships among the cosmids, predicted genes and the cDNA clones. * Image: In situ hybridization images that are arranged by their developmental stages. * Sequence: Tag sequences of the cDNA clones are available. * Homology: Results of BLASTX search are available. Users of the data presented on our web pages should not publish the information without our permission and appropriate acknowledgment. Methods are available for: * In situ hybridization on whole mount embryos of C.elegans * Protocols for large scale in situ hybridization on C.elegans larvae

Proper citation: NEXTDB (RRID:SCR_004480) Copy   

•   Source: SciCrunch Registry

http://metagenomics.atc.tcs.com/binning/SOrt-ITEMS/

Sequence orthology based software for improved taxonomic estimation of metagenomic sequences., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SOrt-ITEMS (RRID:SCR_004716) Copy   

•   Source: SciCrunch Registry

http://omics.informatics.indiana.edu/AbundanceBin/

An abundance-based software tool for binning metagenomic sequences, such that the reads classified in a bin belong to species of identical or very similar abundances. AbundanceBin also gives estimations of species abundances and their genome sizes -two important characteristic parameters for a microbial community.

Proper citation: AbundanceBin (RRID:SCR_004648) Copy   

•   Source: SciCrunch Registry

http://www.cbcb.umd.edu/software/phymm/

Software for Phylogenetic Classification of Metagenomic Data with Interpolated Markov Models to taxonomically classify DNA sequences and accurately classify reads as short as 100 bp. PhymmBL, the hybrid classifier included in this distribution which combines analysis from both Phymm and BLAST, produces even higher accuracy.

Proper citation: Phymm and PhymmBL (RRID:SCR_004751) Copy   

•   Source: SciCrunch Registry

http://www.genedb.org/Homepage/Tbruceibrucei927

Database of the most recent sequence updates and annotations for the T. brucei genome. New annotations are constantly being added to keep up with published manuscripts and feedback from the Trypanosomatid research community. You may search by Protein Length, Molecular Mass, Gene Type, Date, Location, Protein Targeting, Transmembrane Helices, Product, GO, EC, Pfam ID, Curation and Comments, and Dbxrefs. BLAST and other tools are available. T. brucei possesses a two-unit genome, a nuclear genome and a mitochondrial (kinetoplast) genome with a total estimated size of 35Mb/haploid genome. The nuclear genome is split into three classes of chromosomes according to their size on pulsed-field gel electrophoresis, 11 pairs of megabase chromosomes (0.9-5.7 Mb), intermediate (300-900 kb) and minichromosomes (50-100 kb). The T. brucei genome contains a ~0.5Mb segmental duplication affecting chromosomes 4 and 8, which is responsible for some 75 gene duplicates unique to this species. A comparative chromosome map of the duplicons can be accessed here (PubmedID 18036214). Protozoan parasites within the species Trypanosoma brucei are the etiological agent of human sleeping sickness and Nagana in animals. Infections are limited to patches of sub-Saharan Africa where insects vectors of the Glossina genus are endemic. The most recent estimates indicate between 50,000 - 70,000 human cases currently exist, with 17 000 new cases each year (WHO Factsheet, 2006). In collaboration with GeneDB, the EuPathDB genomic sequence data and annotations are regularly deposited on TriTrypDB where they can be integrated with other datasets and queried using customized queries.

Proper citation: GeneDB Tbrucei (RRID:SCR_004786) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/sra

Repository of raw sequencing data from next generation of sequencing platforms including including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, Complete Genomics, and Pacific Biosciences SMRT. In addition to raw sequence data, SRA now stores alignment information in form of read placements on reference sequence. Data submissions are welcome. Archive of high throughput sequencing data,part of international partnership of archives (INSDC) at NCBI, European Bioinformatics Institute and DNA Database of Japan. Data submitted to any of this three organizations are shared among them.

Proper citation: NCBI Sequence Read Archive (SRA) (RRID:SCR_004891) Copy   

•   Source: SciCrunch Registry

http://cortexassembler.sourceforge.net/index_cortex_var.html

A tool for genome assembly and variation analysis from sequence data. You can use it to discover and genotype variants on single or multiple haploid or diploid samples. If you have multiple samples, you can use Cortex to look specifically for variants that distinguish one set of samples (eg phenotype=X, cases, parents, tumour) from another set of samples (eg phenotype=Y, controls, child, normal). cortex_var features * Variant discovery by de novo assembly - no reference genome required * Supports multicoloured de Bruijn graphs - have multiple samples loaded into the same graph in different colours, and find variants that distinguish them. * Capable of calling SNPs, indels, inversions, complex variants, small haplotypes * Extremely accurate variant calling - see our paper for base-pair-resolution validation of entire alleles (rather than just breakpoints) of SNPs, indels and complex variants by comparison with fully sequenced (and finished) fosmids - a level of validation beyond that demanded of any other variant caller we are aware of - currently cortex_var is the most accurate variant caller for indels and complex variants. * Capable of aligning a reference genome to a graph and using that to call variants * Support for comparing cases/controls or phenotyped strains * Typical memory use: 1 high coverage human in under 80Gb of RAM, 1000 yeasts in under 64Gb RAM, 10 humans in under 256 Gb RAM

Proper citation: cortex var (RRID:SCR_005081) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ega/

Web service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The repository allows you to explore datasets from numerous genotype experiments, supplied by a range of data providers. The EGA''s role is to provide secure access to the data that otherwise could not be distributed to the research community. The EGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the EGA project. As an example, only members of the EGA team are allowed to process data in a secure computing facility. Once processed, all data are encrypted for dissemination and the encryption keys are delivered offline. The EGA also supports data access only for the consortium members prior to publication.

Proper citation: European Genome phenome Archive (RRID:SCR_004944) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/popset

Database containing a set of DNA sequences that have been collected to analyse the evolutionary relatedness of a population. The population could originate from different members of the same species, or from organisms from different species. Users may submit a Popset using Sequin.

Proper citation: NCBI Popset (RRID:SCR_005049) Copy   

•   Source: SciCrunch Registry

http://plaza.ufl.edu/xywang/Mpick.htm

A modularity-based clustering software for Operational Taxonomic Unit (OTU) picking of 16S rRNA sequences. The algorithm does not require a predetermined cut-off level, and our simulation studies suggest that it is superior to existing methods that require specified distance or variance levels to define OTUs.

Proper citation: M-pick (RRID:SCR_004995) Copy   

•   Source: SciCrunch Registry