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http://appris.bioinfo.cnio.es/

A database that houses annotations of human splice isoforms. It adds reliable protein structural and functional data and information from cross-species conservation. A visual representation of the annotations for each gene allows users to easily identify functional changes brought about by splicing events. In addition to collecting, integrating and analyzing reliable predictions of the effect of splicing events, it also selects a single reference sequence for each gene, termed the principal isoform, based on the annotations of structure, function and conservation for each transcript.

Proper citation: APPRIS (RRID:SCR_012019) Copy   

•   Source: SciCrunch Registry

http://www.sdbonline.org/fly/aimain/1aahome.htm

The InterActive Fly is an online database of Drosophilia development and metazoan evolution. It contains information on biochemical pathways, organs, images, a cis-decoder, and EvoPrinter, a machine that allows users to identify Evolutionarily Resilient DNA Sequences.

Proper citation: Interactive Fly (RRID:SCR_012784) Copy   

•   Source: SciCrunch Registry

https://omictools.com/fusiondb-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. FusionDB is a database of bacterial and archaeal gene fusion events - also known as Rosetta stones. Gene-fusion events are not the only resource to determine functional links between two proteins. Similar phylogenetic profiles and conserved chromosomal co-localization can also be used as an indicator for such interactions.

Proper citation: FusionDB (RRID:SCR_013314) Copy   

•   Source: SciCrunch Registry

http://epi.grants.cancer.gov/CFR/about_colon.html

It is an international research infrastructure for investigators interested in conducting population and clinic-based interdisciplinary studies on the genetic and molecular epidemiology of colon cancer and its behavioral implications. A central goal of the C-CFR is the translation of this research to the clinical and prevention setting for the benefit of Registry participants and the general public. The C-CFR has information and biospecimens contributed by greater than 11,300 families across the spectrum of risk for colon cancers and from population-based or relative controls. Of particular interest are: identification and characterization of cancer susceptibility genes definition of gene-gene and gene-environment interactions in cancer etiology translational, preventive, and behavioral implications of research findings Special features include: population-based and clinic-based ascertainment systematic collection of validated family history epidemiologic risk factor data clinical and follow-up data biospecimens (including tumor blocks and EBV transformed cell lines) ongoing molecular characterization of the participating families Goals: to contribute to the development of public health measures for the general population by increasing knowledge on genetic factors affecting cancer susceptibility and modification by environmental and lifestyle factors to protect those with increased susceptibility from developing cancer to provide life-prolonging treatment to genetically susceptible individuals Objectives: to establish a comprehensive research resource infrastructure to assist with the implementation of collaborative, interdisciplinary research protocols in the genetic epidemiology of cancer to identify, characterize, and follow-up a cohort of individuals and their family members, spanning the spectrum of cancer risk to identify diverse genetically susceptible populations that could benefit from enrollment in preventive and therapeutic interventions to develop an adaptive and evolving informatics model to support ongoing and future research consortia Sponsor. This study was supported by National Cancer Institute Grants R01 CA47147, R01 CA47305, and R01 CA69664.

Proper citation: Colon CFR (RRID:SCR_013162) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/thornton-srv/databases/MACiE/

MACiE, which stands for Mechanism, Annotation and Classification in Enzymes, is a collaborative project on enzyme reaction mechanisms. MACiE currently contains 223 fully annotated enzyme reaction mechanisms, which comprise 218 EC numbers (161 EC sub-subclasses) and 310 distinct CATH codes. It is a joint effortbetween the Mitchell Group at the Unilever Centre for Molecular Informatics part of the University of Cambridge and the Thornton Group at the European Bioinformatics Institute.

Proper citation: MACiE (RRID:SCR_013296) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions/index.html

The Division of Acquired Immunodeficiency Syndrome (DAIDS) of the National Institute of Allergy and Infectious Diseases (NIAID) has initiated a project, in collaboration with Southern Research Institute and the National Center for Biotechnology Information (NCBI), designed to compile a comprehensive database of the described interactions between HIV-1 and cellular proteins. The goal of this project is to provide scientists in the field of HIV/AIDS research a concise, yet detailed, summary of all known interactions of HIV-1 proteins with host cell proteins, other HIV-1 proteins, or proteins from disease organisms associated with HIV/AIDS. This database has been designed to track the following information for each protein-protein interaction identified in the literature: * NCBI Reference Sequence (RefSeq) protein accession numbers. * NCBI Entrez Gene ID numbers. * Amino acids from each protein that are known to be involved in the interaction. * Brief description of the protein-protein interaction. * Keywords to support searching for interactions. * National Library of Medicine (NLM) PubMed identification numbers (PMIDs) for all journal articles describing the interaction.

Proper citation: HIV-1, Human Protein Interaction Database (RRID:SCR_013214) Copy   

•   Source: SciCrunch Registry

http://www.phenomicdb.de/

PhenomicDB is a multi-organism phenotype-genotype database including human, mouse, fruit fly, C.elegans, and other model organisms. The inclusion of gene indices (NCBI Gene) and orthologs (same gene in different organisms) from HomoloGene allows to compare phenotypes of a given gene over many organisms simultaneously. PhenomicDB contains data from publicly available primary databases: FlyBase, Flyrnai.org, WormBase, Phenobank, CYGD, MatDB, OMIM, MGI, ZFIN, SGD, DictyBase, NCBI Gene, and HomoloGene. We brought this wealth of data into a single integrated resource by coarse-grained semantic mapping of the phenotypic data fields, by including common gene indexes (NCBI Gene), and by the use of associated orthology relationships (HomoloGene). PhenomicDB is thought as a first step towards comparative phenomics and will improve the understanding of the gene functions by combining the knowledge about phenotypes from several organisms. It is not intended to compete with the much more dedicated primary source databases but tries to compensate its partial loss of depth by linking back to the primary sources. The basic functional concept of PhenomicDB is an integrated meta-search-engine for phenotypes. Users should be aware that comparison of genotypes or even phenotypes between organisms as different as yeast and man can have serious scientific hurdles. Nevertheless finding that the phenotype of a given mouse gene is described as ��similar to psoriasis�� and at the same time that the human ortholog has been described as a gene causing skin defects can lead to novelty and interesting hypotheses. Similarly, a gene involved in cancer in mammalian organisms could show a proliferation phenotype in a lower organism such as yeast and thus, give further insights to a researcher.

Proper citation: PhenomicDB (RRID:SCR_013051) Copy   

•   Source: SciCrunch Registry

http://www.scmbb.ulb.ac.be/Users/benoit/LigASite

A gold-standard dataset of biologically relevant binding sites in protein structures. It consists of proteins with one unbound structure and at least one structure of the protein-ligand complex. Both a redundant and a non-redundant (sequence identity lower than 25) version is available. Quaternary structures proposed by PQS (2) are used for all structures in the dataset. The availability of both unbound and bound structures for each protein guarantees that our dataset can be used to benchmark binding site prediction methods, in conditions that mimic cases where the binding site is truly unknown. In cases where several different bound structures are available for a given protein, all are used to define the binding sites.

Proper citation: LIGand Attachment SITE Database (RRID:SCR_013172) Copy   

•   Source: SciCrunch Registry

http://www.dbali.org

DBAli is a database that includes a comprehensive all-against-all comparison of protein structures in the PDB database. It is not currently being updated; however, updates should resume in the near future. All pairwise structural comparisons in DBAli have been obtained using the MAMMOTH program developed in the group of Prof. Angel R. Ortiz. All multiple structure alignments in DBAli have been obtained using the SALIGN command in MODELLER developed in the group of Prof. Andrej Sali.

Proper citation: DBAli. A Database of Structure Alignments. (RRID:SCR_013418) Copy   

•   Source: SciCrunch Registry

http://www.domins.org/

DomIns is a web resource aimed at providing comprehensive information on domain insertions in proteins of known structure. We have followed the definition of protein domains as in the SCOP (Structural Classification of Proteins) database in order to identify insertions. We have considered only the major five classes (All-alpha, All-beta, alpha/beta, alpha+beta and Small Proteins), the fold and the superfamily level of SCOP hierarchy for identifying insertions. Apart from browsing insertions in whole PDB, we also provide an option to browse insertions in a pre-computed list of non-redundant PDB chains provided by PDB_Select with a sequence identity threshold of 90%.

Proper citation: DomIns: A Web Resource for Domain Insertions in Known Protein Structures (RRID:SCR_013417) Copy   

•   Source: SciCrunch Registry

http://knottin.cbs.cnrs.fr/

The KNOTTIN database provides standardized data on the knottin structural family (also referred to as the Inhibitor Cystine Knot (ICK) motif/family/fold). Knottins are intriguing miniproteins with strong potential in drug design. This knot is achieved when one disulfide bridge crosses the macrocycle formed by the two other disulfides and the interconnecting backbone.

Proper citation: KNOTTIN database (RRID:SCR_013263) Copy   

•   Source: SciCrunch Registry

http://www.h-invitational.jp/

H-Invitational Database (H-InvDB) is an integrated database of human genes and transcripts. By extensive analyses of all human transcripts, we provide curated annotations of human genes and transcripts that include gene structures, alternative splicing isoforms, non-coding functional RNAs, protein functions, functional domains, sub-cellular localizations, metabolic pathways, protein 3D structure, genetic polymorphisms (SNPs, indels and microsatellite repeats) , relation with diseases, gene expression profiling, and molecular evolutionary features , protein-protein interactions (PPIs) and gene families/groups. This database is produced by the Genome Information Integration Project (2005-) based upon the annotation technology established in the H-Invitational Project for annotation of human full-length cDNAs.

Proper citation: H-InvDB (RRID:SCR_013265) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/ExTopoDB/

A publicly accessible database of experimentally derived topological models of transmembrane proteins. It contains experimental information about the topology of 2143 transmembrane proteins. This information was collected from studies in the literature that reported the use of biochemical methods for the determination of the topology of transmembrane proteins. Each record contains unique information about the given protein, such as its sequence, cross-references to many publicly available databases worldwide, the protein''s name and organism source. The web interface of the database offers the user the ability to submit advanced queries for text search within ExTopoDB''s protein entries and there is also an interface for running BLAST against the database. Furthermore, the results of topology prediction using the HMM-TM algorithm are included for each protein in the database (unconstrained prediction) and we also incorporated the experimental information about the topology of the proteins in the HMM-TM prediction procedure, producing more reliable topology models (constrained prediction).

Proper citation: ExTopoDB (RRID:SCR_013143) Copy   

•   Source: SciCrunch Registry

http://chloroplast.cbio.psu.edu/

The Chloroplast Genome Database contains annotated chloroplast/plastid genomes from the NCBI Organelle Genomes section at NCBI. Users can search for genes by their annotated names, conduct flexible BLAST searches, download protein and nucleotide sequences extracted from a selected chloroplast genome, and browse the putative protein families (tribes) created using TribeMCL.

Proper citation: Chloroplast Genome Database (RRID:SCR_013421) Copy   

•   Source: SciCrunch Registry

http://cutdb.burnham.org

The CutDB focuses on the annotation of individual proteolytic events, both actual and predicted. Its offers searchable lists of proteases, Merops code, substrate, and diseases from which users can specify their desired queries in order to obtain more specific information. CutDB is one of the first systematic efforts to build an easily accessible collection of documented proteolytic events for natural proteins in vivo or in vitro. A CutDB entry is defined by a unique combination of these three attributes: protease, protein substrate and cleavage site. Currently, CutDB integrates 3070 proteolytic events for 470 different proteases captured from public archives (such as MEROPS and HPRD) and publications. CutDB supports various types of data searches and displays, including clickable network diagrams. Most importantly, CutDB is a community annotation resource based on a Wikipedia approach, providing a convenient user interface to input new data online. A recent contribution of 568 proteolytic events by several experts in the field of matrix metallopeptidases suggests that this approach will significantly accelerate the development of CutDB content.

Proper citation: CutDB (RRID:SCR_013420) Copy   

•   Source: SciCrunch Registry

http://prodata.swmed.edu/malisam

MALISAM is a database of pairwise, structure-based alignments for structurally analogous motifs in proteins. Homology and analogy are two alternative scenarios to explain structural similarities among proteins. Homologs inherit similar features from their common ancestor, while analogs converge to similar structures due to a limited number of energetically favorable ways to pack secondary structural elements. Analogous pairs in this database are in three categories: a hybrid motif and a core motif, an interface motif and a core motif, an artificial protein and a natural protein. During evolution, a protein family usually preserves a common core while accumulating insertions and deletions in the periphery. A core motif is composed entirely of secondary structure elements belonging to the evolutionary core. A hybrid motif consists of both core elements and peripheral insertions that are not present in the majority of the family members. An interface motif uses secondary structural elements from two or more domains or subunits contacting along that interface.

Proper citation: MALISAM: Manual ALIgnments of Structurally Analogous Motifs (RRID:SCR_013380) Copy   

•   Source: SciCrunch Registry

http://www.pahdb.mcgill.ca

A database of centralized mutation data on the PAH gene. Searchable fields of the database available to users are: mutation name, polymorphic haplotype, population, geographic location, gene region, codon number, mutation type, substitution, phenotype, author's name and many more. The complete information provided for each mutation is regularly updated from both published data and personal communications.

Proper citation: Phenylalanine Hydroxylase Locus Knowledgebase (RRID:SCR_013381) Copy   

•   Source: SciCrunch Registry

http://jbirc.jbic.or.jp/h-dbas/

A specialized database for human alternative splicing (AS) based on H-Invitational full-length cDNAs. H-DBAS offers unique data and viewer for human Alternative Splicing (AS) analysis. It contains: * Genome-wide representative alternative splicing variants (RASVs) identified from following datasets * H-Inv full-length cDNAs (resource summary): H-Invitational cDNA dataset * H-Inv all transcripts (resource summary): Published human mRNA dataset * Mouse full-length cDNAs (resource summary): Mouse cDNA dataset * RASVs affecting protein functions such as protein motif, GO, subcellular localization signal and transmembrane domain * Conserved RASVs compared with mouse genome and the full-length cDNAs (H-Inv full-length cDNAs only)

Proper citation: Human Transcriptome Database for Alternative Splicing (RRID:SCR_013305) Copy   

•   Source: SciCrunch Registry

http://tcm.lifescience.ntu.edu.tw/index.html

TCMGeneDIT is a database system providing association information about traditional Chinese medicines (TCMs), genes, diseases, TCM effects and TCM ingredients automatically mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information collected from public databases are also available. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in deducing possible synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. TCMGeneDIT is a unique database of various association information about TCMs. The database integrating TCMs with life sciences and biomedical studies would facilitate the modern clinical research and the understanding of therapeutic mechanisms of TCMs and gene regulations.

Proper citation: TCMGeneDIT (RRID:SCR_013396) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/Projects/D_rerio/

Database of zebrafish genome.

Proper citation: Zebrafish Genome Project (RRID:SCR_013157) Copy   

•   Source: SciCrunch Registry