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http://www.uta.fi/imt/bioinfo/KinMutBase/
KinMutBase is a comprehensive database of disease-causing mutations in protein kinase domains. The current release of the database contains 582 mutations in 20 tyrosine kinase domains and 13 serine/threonine kinase domains. The database refers 1790 cases from 1322 families. KinMutBase is a registry of mutations in human protein kinases related to disorders. Kinases are essential cellular signaling molecules, in which mutations can lead to diseases, including immunodeficiencies, cancers and endocrine disorders. Mutations appear both in conserved hallmark residues of the kinases as well as in non-homologous sites. The KinMutBase WWW pages provide plenty of information, namely mutation statistics and display, clickable sequences with mutations and changes to restriction enzyme patterns.
Proper citation: KinMutBase: A registry of disease-causing mutations in protein kinase domains (RRID:SCR_007759) Copy
A database ofhuman disease-related mutated proteins identified by mass-spectrometry (MS). For achieving this goal, we collected human mutated sequences known to be related to diseases till now. After surveying mutated sequence sources: PMD, OMIM, SwissProt polymorphism, HGMD, etc, we found that currently HGMD contains the largest human gene mutation information. However, because, for academic users, HGMD does not provide with whole data download service, we decided to systematically extract and curate mutation information from PMD, OMIM, SwissProt, MSIPI database to form SysPIMP and provide it free for academic users.
Proper citation: Systematic Platform for Identifying Mutated Proteins (SysPIMP) (RRID:SCR_007954) Copy
SYSTERS is a database of protein sequences grouped into homologous families and superfamilies. The SYSTERS project aims to provide a meaningful partitioning of the whole protein sequence space by a fully automatic procedure. A refined two-step algorithm assigns each protein to a family and a superfamily. The sequence data underlying SYSTERS release 4 now comprise several protein sequence databases derived from completely sequenced genomes (ENSEMBL, TAIR, SGD and GeneDB), in addition to the comprehensive Swiss-Prot/TrEMBL databases. To augment the automatically derived results, information from external databases like Pfam and Gene Ontology are added to the web server. Furthermore, users can retrieve pre-processed analyses of families like multiple alignments and phylogenetic trees. New query options comprise a batch retrieval tool for functional inference about families based on automatic keyword extraction from sequence annotations. A new access point, PhyloMatrix, allows the retrieval of phylogenetic profiles of SYSTERS families across organisms with completely sequenced genomes. Gene, Human, Vertebrate, Genome, Human ORFs
Proper citation: SYSTERS (RRID:SCR_007955) Copy
http://supfam.org/SUPERFAMILY/
SUPERFAMILY is a database of structural and functional protein annotations for all completely sequenced organisms. The SUPERFAMILY annotation is based on a collection of hidden Markov models, which represent structural protein domains at the SCOP superfamily level. A superfamily groups together domains which have an evolutionary relationship. The annotation is produced by scanning protein sequences from over 1,700 completely sequenced genomes against the hidden Markov models.
Proper citation: SUPERFAMILY (RRID:SCR_007952) Copy
Database to explore known and predicted interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins. Each proposed interaction can be traced back to the original data sources. The database contains interaction information for over 68,000 different chemicals, including 2200 drugs, and connects them to 1.5 million genes across 373 genomes and their interactions contained in the STRING database.
Proper citation: Search Tool for Interactions of Chemicals (RRID:SCR_007947) Copy
http://splicenest.molgen.mpg.de/
A web based graphical tool for exploring gene structure of the human genome, including alternative splicing. It is based on a mapping of the EST consensus sequences (contigs) from GeneNest to the complete human genome. SpliceNest is integrated with GeneNest and the SYSTERS protein sequence cluster set in one framework, permitting an overall exploration of the whole sequence space covering protein, mRNA and EST sequences, as well as genomic DNA. Users can search for alignments by browsing, utilizing the graphical chromosome display feature, or performing a cluster, keyword or BLAST search.
Proper citation: spliceNest (RRID:SCR_007946) Copy
http://www.sbg.bio.ic.ac.uk/~ino/
A database containing compound microsatellite-SNP markers in human, dog, mouse, rat and chicken. SNPSTRs are a relatively new type of compound genetic marker which combines a STR marker with one or more tightly linked SNPs. This combination of co-inherited markers evolving at different rates may offer the possibility of gaining better resolved insights into population genetic processes compared to when these different marker types are used separately. SNPSTRs were first described by Mountain et al (2002) who developed experimental protocols for autosomal SNPSTRs which contain a SNP and a microsatellite within 500 base pairs apart. microsatellite-SNP, dog microsatellite-SNP, mouse microsatellite-SNP, rat microsatellite-SNP, chicken microsatellite-SNP
Proper citation: SNPSTR (RRID:SCR_007945) Copy
This is a database of human C/D box and H/ACA modification guide RNAs. Information on a particular snoRNA can be accessed by three ways: 1- On the Search page, just type the name of the snoRNA (for example ACA17) in the Id window. 2- The Find guide RNA contains the sequences of the human ribosomal rRNAs 28S, 18S and 5.8S, and of the snRNAs U1, U2, U4, U5 and U6, with the positions of modified (2''O-ribose methylated or pseudo-uridinylated) nucleotides, and the identity of the corresponding modification guide RNAs. You can click on the name of the relevant snoRNA. 3- By utilizing the link to the UCSC Human Genome Browser.
Proper citation: snoRNABase- a comprehensive database of human H/ACA and C/D box snoRNAs. (RRID:SCR_007939) Copy
https://omictools.com/sno-scarnabase-tool
A curated database for small nucleolar RNAs and small cajal body-specific RNAs. It presents sno/scaRNA-associated genetic and functional data and provides access to several other database sources via web-accessible search interfaces. Consisting of 1979 sno/scaRNA records obtained from 85 organisms, sno/scaRNAbase is a combination of systematic literature curation and annotation effort. small nucleolar RNA, small cajal body-specific RNA
Proper citation: Sno/scaRNAbase (RRID:SCR_007938) Copy
http://www.compbio.dundee.ac.uk/SNAPPI/downloads.jsp
An object-oriented database of domain-domain interactions observed in structural data. SNAPPI-DB is a useful resource for any analysis of structures but has been opitmised for analysis on domain-domain interactions and domain-ligand interactions. The database has already been employed for 3 studies on the properties of domain-domain interactions and is currently being employed to train a protein-protein interaction predictor and a functional residue predictor. SNAPPI-DB has several features which are not available in other databases, including links to the MSD, speed, being object oriented, storage of multiple domain definitions, and storage of Protein Quaternary Structures (PQS).
Proper citation: SNAPPI (RRID:SCR_007937) Copy
https://www.oxfordjournals.org/our_journals/nar/database/summary/954
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 19, 2016. A database for the study of protein inter-atomic distance distribution. Currently, the distances are extracted from the protein structures determined through X-ray Crystallography, but they could also be obtained from NMR structural models. The known structures with the resolution higher than 2A and less than 70% sequence similarities are selected. Each type of distances is specified in terms of the types of the atoms it involves, the types of the residues containing the atoms, and the types of the residues in between the two end residues in sequence. An automated system is built to generate and process the data dynamically. The system consists of two levels of databases. The first one stores the sequence and structure information for a large set of high-resolution protein structures, with a similar data structure as the structural data represented in the PDB Data Bank. The second one stores the information for the distance distributions, with each record corresponding to a distribution function. The second database is built dynamically from the first one. The database can provide structural information in terms of distance distributions to structural biologists. Such information can be valuable for the study of many fundamental biological problems including protein structure prediction and determination, protein dynamics simulation, molecular design, protein structural analysis and classification, etc.
Proper citation: PIDD (RRID:SCR_007854) Copy
http://www.bioinfodatabase.com/pint/
A protein-protein interactions thermodynamic database which contains data of several thermodynamic parameters along with sequence and structural information experimental conditions and literature information. Each entry contains numerical data for features of the interacting proteins such as the free energy change, dissociation constant, association constant, enthalpy change, and heat capacity change. PINT includes: the name and source of the proteins involved in binding, SWISS-PROT and Protein Data Bank (PDB) codes, secondary structure and solvent accessibility of residues at mutant positions, measuring methods, and experimental conditions such as buffers, ions and additives, and literature information. PINT is cross-linked with other related databases such as PIR, SWISS-PROT, PDB and the NCBI PUBMED literature database.
Proper citation: PINT (RRID:SCR_007856) Copy
An online comparative genomics resource that is built upon publicly available sequence and map information from a diverse set of plant species, with a focus on the angiosperms, or flowering plants. It provides an interface to the results from a variety of phylogenomic analyses. Phytome is designed to facilitate functional genomics, molecular breeding and evolutionary studies in model and non-model plant species. Currently, Phytome contains phylogenetic and functional information for predicted protein sequences ("Unipeptides"). Future development will incorporate data and tools for analysis of sequence-based comparative maps.
Proper citation: Phytome (RRID:SCR_007852) Copy
Collection of transmembrane protein datasets containing experimentally derived topology information from the literature and from public databases. Web interface of TOPDB includes tools for searching, relational querying and data browsing, visualisation tools for topology data.
Proper citation: Topology Data Bank of Transmembrane Proteins (RRID:SCR_007964) Copy
TassDB stores extensive data about alternative splice events at GYNGYN donors and NAGNAG acceptors. Currently, 114,554 tandem splice sites of eight species are contained in the database, 5,209 of which have EST/mRNA evidence for alternative splicing. Users can search by Transcript Accession Number and Gene Symbol, SQL Query, and Tandem Donor/Tandem Acceptor pairs.
Proper citation: TAndem Splice Site DataBase (RRID:SCR_007961) Copy
TargetDB, a target registration database, provides information on the experimental progress and status of targets selected for structure determination. Search sequences from the PSI Structural Genomics Centers and other Structural Genomics projects.For more information about how these proteins were cloned, expressed, purified, or other experimental protocols please go to the Protein expression, purification, and crystallization DataBase.
Proper citation: TargetDB: Structural Genomics Target Search (RRID:SCR_007960) Copy
http://tbestdb.bcm.umontreal.ca/searches/welcome.php
The taxonomically broad EST database TBestDB serves as a repository for EST data from a wide range of eukaryotes, many of which have previously not been thoroughly investigated. Users can search by annotated name, EC#, and view datasets that contain classification hierarchies for pathways, for reactions (the enzyme nomenclature system), for compounds, and for genes. Most of the data contained in TBestDB has been generated by the labs of the Protist EST Program located in six universities across Canada.
Proper citation: Taxonomically Broad EST Database (RRID:SCR_007962) Copy
SYSTOMONAS is a comprehensive database of molecular networks in Pseudomonas focusing on Pseudomonas aeruginosa. We use a systems biology approach to get a deeper understanding of all cellular processes of P. aeruginosa during infection. Our long term goal is the development of a dynamic model simulating P. aeruginosa during infection. The basis for such an approach is SYSTOMONAS, a comprehensive database that includes systems data from all levels of analysis as microarray and proteomics data, metabolite measurements, sequence data, gene-regulatory networks and enzyme data. Therefore, we started with metabolomics analysis and extended to transcriptomics, genomics, and proteomics aspects. Along with the wet lab results additional data is stored, which is extracted from literature or derived from other external databases. Major sources of SYSTOMONAS are KEGG, PRODORIC, BRENDA (see section ''Sources''), which are partly stored via the data warehouse system and partly dynamically connected via SOAP, a platform-independent data transfer protocol. Comparing a Pseudomonas protein of interest with other well-characterized proteins may deliver useful insights into the evolution, distribution, and species specific function. Therefore, we searched for all deduced proteins of the SYSTOMONAS database for orthologous proteins in other Pseudomonas species to obtain orthologous protein clusters. Pseudomonas aeruginosa, systems biology, transcriptomics, genomics, proteomics
Proper citation: SYSTOMONAS: SYSTems biology of pseudOMONAS (RRID:SCR_007958) Copy
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1669717/
This is a dataset of clinical HIV sequences, including a method of decoding the evolutionary pathways by which HIV evolves drug resistance. "Fitness landscape" describing how HIV proteins can evolve, is shown as a kinetic network. Drug resistance is a major problem in the treatment of AIDS, due to the very high mutation rate of human immunodeficiency virus (HIV) and subsequent rapid development of resistance to new drugs. Identification of mutations associated with drug resistance is critical for both individualized treatment selection and new drug design. We have performed an automated mutation analysis of HIV Type 1 (HIV-1) protease and reverse transcriptase (RT) from approximately 50,000 AIDS patient plasma samples sequenced by Specialty Laboratories Inc. from 1999 to mid-2002. This dataset provides a nearly complete mutagenesis of HIV protease and enables the calculation of statistically significant Ka/Ks values for each individual amino acid mutation in protease and RT. Positive selection (i.e., Ka/Ks>1 indicating increased reproductive fitness) detected 19 of 23 known drug-resistant mutation positions in protease and 20 of 34 such positions in RT. We also discovered 163 new amino acid mutations in HIV protease and RT that are strong candidates for drug resistance or fitness. Our results match available independent data on protease mutations associated with specific drug treatments and mutations with positive reproductive fitness, with high statistical significance (the P values for the observed matches to occur by random chance are 1e-5.2 and 1e-16.6, respectively). Our data indicate that positive selection mapping is an analysis that can yield powerful insights from high-throughput sequencing of rapidly mutating pathogens. This database has been made possible by the generous contribution of HIV sequence chromatograms by Specialty Laboratories, Inc.
Proper citation: The HIV Positive Selection Mutation Database (RRID:SCR_007957) Copy
http://smartdb.bioinf.med.uni-goettingen.de/
It collects information about scaffold/matrix attached regions and the nuclear matrix proteins that are supposed be involved in the interaction of these elements with the nuclear matrix. It covers the whole range from yeast to human. The SMAR table gives information on individual sequence elements of experimentally proven matrix binding activity. In release 2.3 it contains 500 entries. The sequences therein can be assigned to more than 150 genes from eukaryotic species ranging from yeast to human. The SMARbinder table contains 96 entries (release 2.3), but this figure does not reflect the number of independent S/MAR binding proteins. First of all, homologous factors from different species such as human and mouse SATB1 are given in different entries since they may differ in some aspects. Moreover, products of distinct but very similar genes or alternative splice products are included as separate entries. In some cases a more general term defining a S/MAR-binding activity may appear as one entry eventhough it might be composed of two or more subunits. The SMARbinder table will only contain those proteins of nuclear localization for which an interaction with a well defined S/MAR has been shown. Besides that the SMARbinder table will also include proteins that are proven components of the the salt-resitent (LIS-resistent) nuclear matrix. Gene entries, besides of giving the gene name in a long and a short (abbreviated) denomination, collect all links to individual S/MARs given in S/MARt DB and/or provide pointers to "S/MARbinders". The entries also contain links to transcription factor binding sites listed in TRANSFAC and give a link to the corresponding TRRD entry describing the regulatory features of the gene on different hierarchical levels.
Proper citation: S/MARt DB (RRID:SCR_007910) Copy
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