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https://cell-innovation.nig.ac.jp/GNP/index_e.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Integrated database of experiment data generated by participating research institutes and public databases relating to: 1) transcription starting position of human genes in the human genome, 2) conjunction to control region on transcriptional factors and the human genome 3) protein-protein interaction with a central focus on transcription factors organized for use in genome level research. Gene Search is the function to search the integrated database by using keywords and public IDs. The search results can be visualized by: * Genome Explorer : provides annotation of landmarks (genes, transcription start sites, etc.) aligned in accordance with their genome locations. * PPI Network : provides a graphical view of protein-protein interaction (PPI) network from the experimental data generated under the project and the public datasets. * Expression Profile : clusters genes by expression pattern and display the result with heatmap. The function provides genes which have relation of coregulation and anti-coregulation. * Comparison Viewer : This function gives the view to compare the genomic regions between human and mouse homologous genes. The viewer shows the distribution of transcription start sites (TSS) as the way of separable by tissues or time points with other landmarks on genome region. * Gene Stock : This is the function to save the gene list that you are interested until the session is closed.

Proper citation: Genome Network Platform (RRID:SCR_001737) Copy   

•   Source: SciCrunch Registry

http://services.bio.ifi.lmu.de:1046/AutoPSIDB/

Searchable database for predicted protein sequences and structures. It has the ability to search through PDB ID, UniProt ID, and descriptive classifiers.

Proper citation: AutoPSI database of predicted SCOP classifications (RRID:SCR_001923) Copy   

•   Source: SciCrunch Registry

http://pepbank.mgh.harvard.edu/

A database of peptides based on sequence text mining and public peptide data sources. Only peptides that are 20 amino acids or shorter are stored. Only peptides with available sequences are stored. After submitting a query you can further refine the results using the new heat map retrieval tool to quickly find the entries that are most relevant to you. Text classification helps you find candidate peptides that are related to cancer, cardiovascular diseases, diabetes, apoptosis, angiogenesis and molecular imaging or peptides for which binding data exist.

Proper citation: PepBank Peptide Database (RRID:SCR_002086) Copy   

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http://www.cbil.upenn.edu/ParaDBs/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. These databases were constructed by extracting the organism specific ESTs from dbEST, removing polyA sequences from the ends and trimming 5' and 3' regions with greater than 25% N's in a 20 base pair window. These quality sequences were then aligned using the cap2 program and the consensus sequences thus generated put into a database that is available on the web. A number of parasitic organisms were chosen that have between 3000 and 15000 ESTs. The attempt here is to provide useful information and analyses to the scientific community without curating the results in any way. A total of 55192 ESTs, deposited into dbEST/GenBank, were included in the analyses. The resulting sequences have been clustered into nonredundant gene assemblies and deposited into a relational database that supports a variety of sequence and text searches. This database has been used to compare the gene assemblies using BLAST similarity comparisons to the public protein databases to identify putative genes. Of these new entries, approximately 15%-20% represent putative homologs with a conservative cutoff of p < 10(-9), thus identifying many conserved genes that are likely to share common functions with other well-studied organisms. Gene assemblies were also used to identify strain polymorphisms, examine stage-specific expression, and identify gene families. An interesting class of genes that are confined to members of this phylum and not shared by plants, animals, or fungi, was identified. These genes likely mediate the novel biological features of members of the Apicomplexa and hence offer great potential for biological investigation and as possible therapeutic targets.

Proper citation: Parasite Databases of Clustered ESTs (RRID:SCR_002262) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/compneur-srv/LGICdb/

Database providing access to information about transmembrane proteins that exist under different conformations, with three primary subfamilies: the cys-loop superfamily, the ATP gated channels superfamily, and the glutamate activated cationic channels superfamily. Due to the lack of evolutionary relationship, these three superfamilies are treated separately. It currently contains 554 entries of ligand-activated ion channel subunits. In this database one may find: the nucleic and proteic sequences of the subunits. Multiple sequence alignments can be generated, and some phylogenetic studies of the superfamilies are provided. Additionally, the atomic coordinates of subunits, or portion of subunits, are provided when available. Redundancy is kept to a minimum, i.e. one entry per gene. Each entry in the database has been manually constructed and checked by a researcher of the field in order to reduce the inaccuracies to a minimum. NOTE: This database is not actively maintained anymore. People should not consider it as an up-to-date trustable resource. For any new work, they should consider using alternative sources, such as UniProt, Ensembl, Protein Databank etc.

Proper citation: Ligand-Gated Ion Channel Database (RRID:SCR_002418) Copy   

•   Source: SciCrunch Registry

http://www.ifti.org/ootfd/

ooTFD (object-oriented Transcription Factors Database) is a successor to TFD, the original Transcription Factors Database. This database is aimed at capturing information regarding the polypeptide interactions which comprise and define the properties of transcription factors. ooTFD contains information about transcription factor binding sites, as well as composite relationships within transcription factors, which frequently occur as multisubunit proteins that form a complex interface to cellular processes outside the transcription machinery through protein-protein interactions. ooTFD contains information represented in TFD but also allows the representation of containment, composite, and interaction relationships between transcription factor polypeptides. It is designed to represent information about all transcription factors, both eukaryotic and prokaryotic, basal as well as regulatory factors, and multiprotein complexes as well as monomers.

Proper citation: object-oriented Transcription Factors Database (RRID:SCR_002435) Copy   

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http://genome.imim.es/datasets/abs2005/index.html

Public database of known binding sites identified in promoters of orthologous vertebrate genes that have been manually curated from bibliography. We have annotated 650 experimental binding sites from 68 transcription factors and 100 orthologous target genes in human, mouse, rat or chicken genome sequences. Computational predictions and promoter alignment information are also provided for each entry. For each gene, TFBSs conserved in orthologous sequences from at least two different species must be available. Promoter sequences as well as the original GenBank or RefSeq entries are additionally supplied in case of future identification conflicts. The final TSS annotation has been refined using the database dbTSS. Up to this release, 500 bps upstream the annotated transcription start site (TSS) according to REFSEQ annotations have been always extracted to form the collection of promoter sequences from human, mouse, rat and chicken. For each regulatory site, the position, the motif and the sequence in which the site is present are available in a simple format. Cross-references to EntrezGene, PubMed and RefSeq are also provided for each annotation. Apart from the experimental promoter annotations, predictions by popular collections of weight matrices are also provided for each promoter sequence. In addition, global and local alignments and graphical dotplots are also available.

Proper citation: ABS: A Database of Annotated Regulatory Binding Sites From Orthologous Promoters (RRID:SCR_002276) Copy   

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http://www.drugbank.ca/

Bioinformatics and cheminformatics database that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information.

Proper citation: DrugBank (RRID:SCR_002700) Copy   

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http://romi.bu.edu/elisa/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. ELISA is an online database that combines functional annotation with structure and sequence homology modeling to place proteins into sequence-structure-function neighborhoods. The atomic unit of the database is a set of sequences and structural templates that those sequences encode. A graph that is built from the structural comparison of these templates is called PDUG (protein domain universe graph). It introduces a method of functional inference through a probabilistic calculation done on an arbitrary set of PDUG nodes. Further, all PDUG structures are mapped onto all fully sequenced proteomes allowing an easy interface for evolutionary analysis and research into comparative proteomics. ELISA is the first database with applicability to evolutionary structural genomics explicitly in mind.

Proper citation: Evolutionary Lineage Inferred from Structural Analysis (RRID:SCR_002343) Copy   

•   Source: SciCrunch Registry

http://www.allgenes.org/

DoTS (Database Of Transcribed Sequences) is a human and mouse transcript index created from all publicly available transcript sequences. The input sequences are clustered and assembled to form the DoTS Consensus Transcripts that comprise the index. These transcripts are assigned stable identifiers of the form DT.123456 (and are often referred to as dots). The transcripts are in turn clustered to form putative DoTS Genes. These are assigned stable identifiers of the form DG.1234356. As of September 1, 2004, the DoTS annotation team has manually annotated 43,164 human and 78,054 mouse DoTS Transcripts (DTs), corresponding to 3,939 human and 7,752 mouse DoTS Genes (DGs). Use the manually annotated gene query to see the DoTS Transcripts that have been manually annotated. The focus of the DoTS project is integrating the various types of data (e.g., EST sequences, genomic sequence, expression data, functional annotation) in a structured manner which facilitates sophisticated queries that are otherwise not easy to perform. DoTS is built on the GUS Platform which includes a relational database that uses controlled vocabularies and ontologies to ensure that biologically meaningful queries can be posed in a uniform fashion. An easy way to start using the site is to search for DoTS Transcripts using an existing cDNA or mRNA sequence. Click on the BLAST tab at the top of the page and enter your sequence in the form provided. All the transcripts with significant sequence similarity to your query sequence will be displayed. Or use one of the provided queries to retrieve transcripts using a number of criteria. These queries are listed on the query page, which can also be reached by clicking on the tab marked query at the top of the page. Finally, the boolean query page allows these queries to be combined in a variety of ways. Sponsors: Funding provided by -NIH grant RO1-HG-01539-03 -DOE grant DE-FG02-00ER62893

Proper citation: Database of Transcribed Sequences (RRID:SCR_002334) Copy   

•   Source: SciCrunch Registry

http://machibase.gi.k.u-tokyo.ac.jp/

Database for Drosophila melanogaster transcription profiling that allows users to search the Drosophilia genome, see sequence overviews, and look at various transcripts. The data were generated in conjunction with the recently developed high-throughput genome sequencer Illumina / Solexa using a newly developed 5'-end mRNA collection method. Approximately 25 million 25-27 nucleotide (nt) 5'-end mRNA tags from the embryos, larvae, young males, young females, old males, old females, and S2 (culture cell line) of D. melanogaster were collected. By arranging this vast amount of expression tag with other annotated data, they have built a one-stop service for Drosophila melanogaster transcription profiling.

Proper citation: MachiBase (RRID:SCR_003078) Copy   

•   Source: SciCrunch Registry

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

Databases of protein sequences and 3D structures of proteins. Collection of sequences from several sources, including translations from annotated coding regions in GenBank, RefSeq and TPA, as well as records from SwissProt, PIR, PRF, and PDB.

Proper citation: NCBI Protein Database (RRID:SCR_003257) Copy   

•   Source: SciCrunch Registry

http://xavante.fmrp.usp.br/mammibase/

Database developed to assist the phylogeneticist user in retrieving individual gene sequence alignments for genes in complete mammalian mitochondrial genomes. Data retrieval in MamMiBase requires three stages. At the first stage, the user must select the mammalian species or group that (s)he wishes to study. In the second stage, the user will select the outgroup from a list that included all species selected in the first stage plus Xenopus laevis and Gallus gallus. Finally, at the third stage, the user will select individual mitochondrial gene alignments or a phylogenetic tree that (s)he wishes to download.

Proper citation: Mammalian Mitochondrial Genomics Database (RRID:SCR_003084) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/genbank/tpa/

Database designed to capture experimental or inferential results that support submitter-provided annotation for sequence data that the submitter did not directly determine but derived from GenBank primary data. Records are divided into two categories: * TPA:experimental: Annotation of sequence data is supported by peer-reviewed wet-lab experimental evidence. * TPA:inferential: Annotation of sequence data by inference (where the source molecule or its product(s) have not been the subject of direct experimentation) TPA records are retrieved through the Nucleotide Database and feature information on the sequence, how it was cataloged, and proper way to cite the sequence information.

Proper citation: TPA (RRID:SCR_003593) Copy   

•   Source: SciCrunch Registry

http://mouse.perlegen.com/mouse/index.html

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on August 12, 2014. Data, grouped by chromosome, available as flat files for download, of identified DNA polymorphisms (SNPs) in 15 commonly used strains of inbred laboratory mice. Perlegen's SNP, genotype (empirical and imputed), haplotype, trace, and PCR primer data has been compiled with NCBI Mouse Build information to produce data files for public use. Using high-density oligonuclueotide array technology, the study identified over 8 million SNPs and other genetic differences between these strains and the previously sequenced C57BL/6J reference strains (Phase 1). By leveraging data provided by Mark Daly's research team at the Broad Institute, genotypes were also predicted for 40 other common strains (Phase 2). Under an extension to the contract, Eleazar Eskin's group at UCLA has used this data to evaluate SNP associations with phenotypes from the Mouse Phenome Project (the Mouse Phenome Database), and to construct haplotype maps for a total of 94 inbred strains (the Mouse HapMap Project). SNP and genotype positions have been mapped from their original reference coordinates to NCBI Mouse Build 37 coordinates. Note that C57BL6/J strain was not selected for re-sequencing as this data would have been almost entirely redundant with the NCBI reference sequence. Since we did not actually determine genotypes for C57BL6/J, we did not submit genotypes for this strain to dbSNP. However, implicit genotypes for C57BL6/J can be obtained from the reference sequence at each SNP position (the reference allele is the first allele in the ALLELES column). The data is available for download in two different compressed file formats. The files are saved as both PC .zip files and Unix compressed .gz files. At this website, you can: * Learn more about the goals of the Perlegen mouse resequencing project. * Learn more about the array-based resequencing technology used in the project. * Download the SNPs, genotypes, and other data generated by the project, plus sequences of the long-range PCR primers used for SNP discovery. * Browse the mouse genome for SNPs. * View the haplotype blocks within the mouse genome. Mouse Genome Browser The Mouse Genome Browser can be used to visualize genes and the SNPs discovered in this study of genome-wide DNA variation in 15 commonly used, genetically diverse strains of inbred laboratory mice. The reference genome is the C57BL/6J strain NCBI build 37 mouse sequence. In addition to the experimentally-derived genotypes for the original 15 strains, the imputed genotypes for 40 additional inbred mouse strains can also be accessed. Mouse Haplotype Analysis The sequences of 16 commonly used, genetically diverse strains of inbred laboratory mice were analyzed to determine their haplotype structure. The Ancestry Browser shows which ancestral sequence each inbred strain most resembles, along with statistics on the pairwise similarity between the ancestral strains. The Haplotype Viewer shows the haplotype block boundaries and the pairwise similarity for all 56 strains: the 15 used for SNP discovery, the reference strain (C57BL/6J), and the 40 additional strains for which the genotypes were imputed.

Proper citation: Perlegen/NIEHS National Toxicology: Mouse Genome Resequencing Project (RRID:SCR_000726) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/mpr/lung

Data set of a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, researchers analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct sub-classes of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.

Proper citation: Classification of Human Lung Carcinomas by mRNA Expression Profiling Reveals Distinct Adenocarcinoma Sub-classes (RRID:SCR_003010) Copy   

•   Source: SciCrunch Registry

http://www.uniprot.org/program/Chordata

Data set of manually annotated chordata-specific proteins as well as those that are widely conserved. The program keeps existing human entries up-to-date and broadens the manual annotation to other vertebrate species, especially model organisms, including great apes, cow, mouse, rat, chicken, zebrafish, as well as Xenopus laevis and Xenopus tropicalis. A draft of the complete human proteome is available in UniProtKB/Swiss-Prot and one of the current priorities of the Chordata protein annotation program is to improve the quality of human sequences provided. To this aim, they are updating sequences which show discrepancies with those predicted from the genome sequence. Dubious isoforms, sequences based on experimental artifacts and protein products derived from erroneous gene model predictions are also revisited. This work is in part done in collaboration with the Hinxton Sequence Forum (HSF), which allows active exchange between UniProt, HAVANA, Ensembl and HGNC groups, as well as with RefSeq database. UniProt is a member of the Consensus CDS project and thye are in the process of reviewing their records to support convergence towards a standard set of protein annotation. They also continuously update human entries with functional annotation, including novel structural, post-translational modification, interaction and enzymatic activity data. In order to identify candidates for re-annotation, they use, among others, information extraction tools such as the STRING database. In addition, they regularly add new sequence variants and maintain disease information. Indeed, this annotation program includes the Variation Annotation Program, the goal of which is to annotate all known human genetic diseases and disease-linked protein variants, as well as neutral polymorphisms.

Proper citation: UniProt Chordata protein annotation program (RRID:SCR_007071) Copy   

•   Source: SciCrunch Registry

http://www.syfpeithi.de/

SYFPEITHI is a database comprising more than 7000 peptide sequences known to bind class I and class II MHC molecules. The entries are compiled from published reports only. It contains a collection of MHC class I and class II ligands and peptide motifs of humans and other species, such as apes, cattle, chicken, and mouse, for example, and is continuously updated. Searches for MHC alleles, MHC motifs, natural ligands, T-cell epitopes, source proteins/organisms and references are possible. Hyperlinks to the EMBL and PubMed databases are included. In addition, ligand predictions are available for a number of MHC allelic products. The database is based on previous publications on T-cell epitopes and MHC ligands. It contains information on: -Peptide sequences -anchor positions -MHC specificity -source proteins, source organisms -publication references Since the number of motifs continuously increases, it was necessary to set up a database which facilitates the search for peptides and allows the prediction of T-cell epitopes. The prediction is based on published motifs (pool sequencing, natural ligands) and takes into consideration the amino acids in the anchor and auxiliary anchor positions, as well as other frequent amino acids. The score is calculated according to the following rules: The amino acids of a certain peptide are given a specific value depending on whether they are anchor, auxiliary anchor or preferred residue. Ideal anchors will be given 10 points, unusual anchors 6-8 points, auxiliary anchors 4-6 and preferred residues 1-4 points. Amino acids that are regarded as having a negative effect on the binding ability are given values between -1 and -3. Sponsors: SYFPEITHI is supported by DFG-Sonderforschungsbereich 685 and theEuropean Union: EU BIOMED CT95-1627, BIOTECH CT95-0263, and EU QLQ-CT-1999-00713.

Proper citation: SYFPEITHI: A Database for MHC Ligands and Peptide Motifs (RRID:SCR_013182) Copy   

•   Source: SciCrunch Registry

http://xin.cz3.nus.edu.sg/group/trmp/trmp.asp

The Therapeutically Relevant Multiple Pathways Database is designed to provide information about such multiple pathways and related therapeutic targets described in the literatures, the targeted disease conditions, and the corresponding drugs/ligands directed at each of these targets. This database currently contains 11 entries of multiple pathways, 97 entries of individual pathways, 120 targets covering 72 disease conditions along with 120 sets of drugs directed at each of these targets. Each entry can be retrieved through multiple methods including multiple pathway name, individual pathway name and disease name. Additional information provided include protein name, synonyms, Swissprot AC number, species, gene name and location, protein sequence (AASEQ) and gene sequence (NTSEQ) as well as potential therapeutic implications while applicable. Cross-links to other databases are provided which include Genecard, GDB, Locuslink, NCBI, KEGG, OMIM, SwissProt to facilitate the access of more detailed information about various aspects of the particular target or non-target protein. Queries can be submitted by entering or selecting the required information in any one or combination of the fields in the form. User can specify full name or any part of the name in a text field, or choose one item from an selection field. Sponsors: TRMP is supported by the National University of Singapore.

Proper citation: Therapeutically Relevant Multiple Pathways Database (RRID:SCR_013471) Copy   

•   Source: SciCrunch Registry

https://hive.biochemistry.gwu.edu/dna.cgi?cmd=tissue_codon_usage&id=586358&mode=cocoputs

Database includes genomic codon-pair and dinucleotide statistics of all organisms with sequenced genome. Facilitates genetic variation analyses and recombinant gene design. Derived from all available GenBank and RefSeq data.

Proper citation: Codon and Codon-Pair Usage Tables (RRID:SCR_018504) Copy   

•   Source: SciCrunch Registry