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http://pbildb1.univ-lyon1.fr/virhostnet/

Public knowledge base specialized in the management and analysis of integrated virus-virus, virus-host and host-host interaction networks coupled to their functional annotations. It contains high quality and up-to-date information gathered and curated from public databases (VirusMint, Intact, HIV-1 database). It allows users to search by host gene, host/viral protein, gene ontology function, KEGG pathway, Interpro domain, and publication information. It also allows users to browse viral taxonomy.

Proper citation: VirHostNet: Virus-Host Network (RRID:SCR_005978) Copy   

•   Source: SciCrunch Registry

http://bioinfo.iitk.ac.in/MIPModDB/

This is a database of comparative protein structure models of MIP (Major Intrinsic Protein) family of proteins. The nearly completed sets of MIPs have been identified from the completed genome sequence of organisms available at NCBI. The structural models of MIP proteins were created by defined protocol. The database aims to provide key information of MIPs in particular based on sequence as well as structures. This will further help to decipher the function of uncharacterized MIPs. For each MIP entry, this database contains information about the source, gene structure, sequence features, substitutions in the conserved NPA motifs, structural model, the residues forming the selectivity filter and channel radius profile. For selected set of MIPs, it is possible to derive structure-based sequence alignment and evolutionary relationship. Sequences and structures of selected MIPs can be downloaded from MIPModDB database.

Proper citation: MIPModDB (RRID:SCR_006058) Copy   

•   Source: SciCrunch Registry

http://recountdb.cbrc.jp/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database for corrected read counts and genome mapping on NCBI's Short Read Archive. The corrected count was done using RECOUNT and the mapping with LAST. We also provide information of reference genome to which we aligned the short reads. We focus on transcriptomic data, specifically TSS-Seq and RNA-Seq. Because this is the type of data for which sequence count correction is most important. Hence we do not include the genomic reads. The current version contains 2,265 entries from 45 organisms, with read lengths from 17 to 100bp. Via a searchable and browseable interface users can obtain corrected data in formats useful for transcriptomic analysis. We provide the data grouped according to the genome, type of studies and submitter in TAB , PSL and BAM format. They contain the mapping position and annotation of reads observed and corrected counts.

Proper citation: RecountDB (RRID:SCR_006117) Copy   

•   Source: SciCrunch Registry

http://prorepeat.bioinformatics.nl/

ProRepeat is an integrated curated repository and analysis platform for in-depth research on the biological characteristics of amino acid tandem repeats. ProRepeat collects repeats from all proteins included in the UniProt knowledgebase, together with 85 completely sequenced eukaryotic proteomes contained within the RefSeq collection. It contains non-redundant perfect tandem repeats, approximate tandem repeats and simple, low-complexity sequences, covering the majority of the amino acid tandem repeat patterns found in proteins. The ProRepeat web interface allows querying the repeat database using repeat characteristics like repeat unit and length, number of repetitions of the repeat unit and position of the repeat in the protein. Users can also search for repeats by the characteristics of repeat containing proteins, such as entry ID, protein description, sequence length, gene name and taxon. ProRepeat offers powerful analysis tools for finding biological interesting properties of repeats, such as the strong position bias of leucine repeats in the N-terminus of eukaryotic protein sequences, the differences of repeat abundance among proteomes, the functional classification of repeat containing proteins and GC content constrains of repeats' corresponding codons.

Proper citation: ProRepeat (RRID:SCR_006113) Copy   

•   Source: SciCrunch Registry

http://pcidb.russelllab.org/

The database of protein-chemical structural interactions includes all existing 3D structures of complexes of proteins with low molecular weight ligands. When one considers the proteins and chemical vertices of a graph, all these interactions form a network. Biological networks are powerful tools for predicting undocumented relationships between molecules. The underlying principle is that existing interactions between molecules can be used to predict new interactions. For pairs of proteins sharing a common ligand, we use protein and chemical superimpositions combined with fast structural compatibility screens to predict whether additional compounds bound by one protein would bind the other. The current version includes data from the Protein Data Bank as of August 2011. The database is updated monthly.

Proper citation: ProtChemSI (RRID:SCR_006115) Copy   

•   Source: SciCrunch Registry

http://www.yeastract.com

A curated repository of more than 206000 regulatory associations between transcription factors (TF) and target genes in Saccharomyces cerevisiae, based on more than 1300 bibliographic references. It also includes the description of 326 specific DNA binding sites shared among 113 characterized TFs. Further information about each Yeast gene has been extracted from the Saccharomyces Genome Database (SGD). For each gene the associated Gene Ontology (GO) terms and their hierarchy in GO was obtained from the GO consortium. Currently, YEASTRACT maintains a total of 7130 terms from GO. The nucleotide sequences of the promoter and coding regions for Yeast genes were obtained from Regulatory Sequence Analysis Tools (RSAT). All the information in YEASTRACT is updated regularly to match the latest data from SGD, GO consortium, RSA Tools and recent literature on yeast regulatory networks. YEASTRACT includes DISCOVERER, a set of tools that can be used to identify complex motifs found to be over-represented in the promoter regions of co-regulated genes. DISCOVERER is based on the MUSA algorithm. These algorithms take as input a list of genes and identify over-represented motifs, which can then be compared with transcription factor binding sites described in the YEASTRACT database.

Proper citation: Yeast Search for Transcriptional Regulators And Consensus Tracking (RRID:SCR_006076) Copy   

•   Source: SciCrunch Registry

https://www.arb-silva.de

High quality ribosomal RNA databases providing comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukarya). Supplementary services include a rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. The extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches. Alignment tool, SINA, is available for download as well as available for use online.

Proper citation: SILVA (RRID:SCR_006423) Copy   

•   Source: SciCrunch Registry

http://prism.ccbb.ku.edu.tr/hotregion/index.php

Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. HotRegion provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. The number of interfaces in the database is 147909 and still growing.

Proper citation: HotRegion - A Database of Cooperative Hotspots (RRID:SCR_006022) Copy   

•   Source: SciCrunch Registry

http://viralzone.expasy.org/

ViralZone is a SIB Swiss Institute of Bioinformatics web-resource for all viral genus and families, providing general molecular and epidemiological information, along with virion and genome figures. Each virus or family page gives an easy access to UniProtKB/Swiss-Prot viral protein entries. ViralZone project is handled by the virus program of SwissProt group. Proteins popups were developed in collaboration with Prof. Christian von Mering and Andrea Franceschini, Bioinformatics Group , Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland, funded in part by the SIB Swiss Institute of bioinformatics. All pictures in ViralZone are copyright of the SIB Swiss Institute of Bioinformatics.

Proper citation: ViralZone (RRID:SCR_006563) Copy   

•   Source: SciCrunch Registry

http://neuroelectro.org

A database of elecrophysiological properties text-mined from the biomedical literature as a function of neuron type. Specifically, NeuroElectro seeks to extract information about the electrophysiological properties (e.g. resting membrane potentials and membrane time constants) of diverse neuron types from the existing literature and place it into a centralized database. There are 252 neurons currently available, with the naming convention established in NeuroLex.

Proper citation: neuroelectro (RRID:SCR_006274) Copy   

•   Source: SciCrunch Registry

http://scansite.mit.edu/

Scansite searches for motifs within proteins that are likely to be phosphorylated by specific protein kinases or bind to domains such as SH2 domains, 14-3-3 domains or PDZ domains. The Motifscanner program utilizes an entropy approach that assesses the probability of a site matching the motif using the selectivity values and sums the logs of the probability values for each amino acid in the candidate sequence. The program then indicates the percentile ranking of the candidate motif in respect to all potential motifs in proteins of a protein database. When available, percentile scores of some confirmed phosphorylation sites for the kinase of interests or confirmed binding sites of the domain of interest are provided for comparison with the scores of the candidate motifs.

Proper citation: Scansite (RRID:SCR_007026) Copy   

•   Source: SciCrunch Registry

http://www.iiserpune.ac.in/~coee/histome/

Database of human histone variants, sites of their post-translational modifications and various histone modifying enzymes. The database covers 5 types of histones, 8 types of their post-translational modifications and 13 classes of modifying enzymes. Many data fields are hyperlinked to other databases (e.g. UnprotKB/Swiss-Prot, HGNC, OMIM, Unigene etc.). Additionally, this database also provides sequences of promoter regions (-700 TSS +300) for all gene entries. These sequences were extracted from the UCSC genome browser. Sites of post-translational modifications of histones were manually searched from PubMed listed literature. Current version contains information for about ~50 histone proteins and ~150 histone modifying enzymes. HIstome is a combined effort of researchers from two institutions, Advanced Center for Treatment, Research and Education in Cancer (ACTREC), Navi Mumbai and Center of Excellence in Epigenetics (CoEE), Indian Institute of Science Education and Research (IISER), Pune.

Proper citation: HIstome: The Histone Infobase (RRID:SCR_006972) Copy   

•   Source: SciCrunch Registry

http://microkit.biocuckoo.org/

MiCroKit database is the first integrative resource to pin point most of identified components and related scientific information of midbody, centrosome and kinetochore. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, and/or midbody from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens. From the related literature of PubMed, numerous proteins have been manually curated to be localized on at least one of the sub-cellular localizations of kinetochore, centrosome and midbody. And to promise the quality of data, based on the rationale of Seeing is believing (Bloom K et al., 2005), these proteins have been unambiguously observed under fluorescent microscope as directly supportive evidences. Then an integrated and searchable database MiCroKit - Midbody, Centrosome and Kinetochore has been established. The version 1.0 of MiCroKit database was set up on Nov. 2nd, 2005, containing 1,065 unique proteins. The MiCroKit version 2.0 was released on Jun. 5th, 2006, with 1,120 entries. Currently, the MiCroKit 3.0 database was updated on July 9, 2009, containing 1,489 unique protein entries. The online service of MiCroKit 3.0 was implemented in PHP + MySQL + JavaScript. And the local packages of MiCroKit 3.0 were developed in JAVA 1.5 (J2SE). The database will be updated routinely as new microkit proteins are reported.

Proper citation: Midbody, Centrosome and Kinetochore (RRID:SCR_007052) Copy   

•   Source: SciCrunch Registry

http://www.biocarta.com/

BioCarta Pathways allows users to observe how genes interact in dynamic graphical models. Online maps available within this resource depict molecular relationships from areas of active research. In an open source approach, this community-fed forum constantly integrates emerging proteomic information from the scientific community. It also catalogs and summarizes important resources providing information for over 120,000 genes from multiple species. Find both classical pathways as well as current suggestions for new pathways.

Proper citation: BioCarta Pathways (RRID:SCR_006917) Copy   

•   Source: SciCrunch Registry

http://www.imgt.org/IMGTindex/LIGM.html

IMGT/LIGM-DB is a comprehensive database of immunoglobulin (IG) and T cell receptor (TR) nucleotide sequences from human and other vertebrate species (270). IMGT/LIGM-DB includes all germline (non-rearranged) and rearranged IG and TR genomic DNA (gDNA) and complementary DNA (cDNA) sequences published in generalist databases. IMGT/LIGM-DB allows searches from the Web interface according to biological and immunogenetic criteria through five distinct modules depending on the user interest. Users can search the catalogue by accession number, mnemonic, definition, creation date, length, or annotation level. They also have the option to search through taxonomic classification, keywords, and annotated labels. For a given entry, nine types of display are available including the IMGT flat file, the translation of the coding regions and the analysis by the IMGT/V-QUEST tool (see parent org. below). IMGT/LIGM-DB distributes expertly annotated sequences. The annotations hugely enhance the quality and the accuracy of the distributed detailed information. They include the sequence identification, the gene and allele classification, the constitutive and specific motif description, the codon and amino acid numbering, and the sequence obtaining information, according to the main concepts of IMGT-ONTOLOGY. They represent the main source of IG and TR gene and allele knowledge stored in IMGT/GENE-DB and in the IMGT reference directory., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: IMGT/LIGM-DB (RRID:SCR_006931) Copy   

•   Source: SciCrunch Registry

http://datf.cbi.pku.edu.cn/

Database that collects all arabidopsis transcription factors (totally 1922 Loci; 2290 Gene Models) and classifies them into 64 families. It uses not only locus (gene), but also gene model (transcript, protein) and the detail information is for each gene model not for locus. It adds multiple alignment of the DNA-binding domain of each family, Neighbor-Joining phylogenetic tree of each family, the GO annotation, homolog with the Database of Rice Transcription Factors (DRTF). It also keeps old information items such as the unique cloned and sequenced information of about 1200 transcription factors, protein domains, 3D structure information with BLAST hits against PDB, predicted Nuclear Location Signals, UniGene information, as well as links to literature reference.

Proper citation: Database of Arabidopsis Transcription Factors (RRID:SCR_007101) Copy   

•   Source: SciCrunch Registry

http://www.polygenicpathways.co.uk

Database of disease genes and risk factors and of host pathogen/interactomes. Lists genes, pathways and environmental risk factors positively associated with diseases and conditions such as Alzheimer's disease, schizophrenia, multiple sclerosis, childhood obesity, anorexia nervosa, HIV-1/AIDS, and helicobacter pylori. Details of polymorphisms as well as negative/positive association data can be found via Useful links. Throughout the site are links to Entrez Gene and Pubmed.

Proper citation: Polygenic Pathways (RRID:SCR_006962) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/mammals/haploreg/haploreg.php

HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs at disease-associated loci. Using linkage disequilibrium (LD) information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with their predicted chromatin state in nine cell types, conservation across mammals, and their effect on regulatory motifs. HaploReg is designed for researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation.

Proper citation: HaploReg (RRID:SCR_006796) Copy   

•   Source: SciCrunch Registry

http://phospho.elm.eu.org/

Database of experimentally verified phosphorylation sites in eukaryotic proteins. Entries are manually curated with links to literature references, information about structure, interaction partners and sub-cellular compartment tissues, and sequences from the UniProt database.

Proper citation: Phospho.ELM (RRID:SCR_001109) Copy   

•   Source: SciCrunch Registry

http://aclame.ulb.ac.be/

A database dedicated to the collection and classification of mobile genetic elements (MGEs) from various sources, comprising all known phage genomes, plasmids and transposons. In addition to provide information on the full genomes and genetic entities, it aims at building a comprehensive classification of the functional modules of MGE's at the protein, gene, and higher levels. Prophinder, a tool dedicated to the detection of prophages in sequenced bacterial genomes, is available on ACLAME.

Proper citation: A Classification of Mobile genetic Elements (RRID:SCR_001694) Copy   

•   Source: SciCrunch Registry