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https://www.rostlab.org/services/snpdbe/

A database to fill the annotation gap left by the high cost of experimental testing for functional significance of protein variants. It joins related bits of knowledge, currently distributed throughout various databases, into a consistent, easily accessible, and updatable resource. It currently covers over 155,000 protein sequences which come from more than 2,600 organisms. Overall more than one million single amino acid substitutions (SAASs) are referenced consisting of natural variants, SAASs from mutagenesis experiments and sequencing conflicts. SNPdbe offers the following pieces of information (if available) on each SAAS: * Experimentally derived functional and structural impact * Predicted functional effect * Associated disease * Average heterozygosity * Experimental evidence of the nsSNP * Evolutionary conservation of wildtype and mutant amino acid * Link-outs to external databases A convenient webinterface to query SAASs on the following levels is offered: * Protein and gene identifiers and keywords * Disease keywords * Protein sequence on different sequence identity thresholds * Variant identifier (dbSNP rs, SwissVar, PMD) or specific mutant like XposY and specified sequence They offer the possibility to submit protein sequences along with experimentally substantiated mutations in order to predict their functional effect and inclusion into our database.

Proper citation: SNPdbe (RRID:SCR_005190) Copy   

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http://www.bioextract.org/GuestLogin

An open, web-based system designed to aid researchers in the analysis of genomic data by providing a platform for the creation of bioinformatic workflows. Scientific workflows are created within the system by recording tasks performed by the user. These tasks may include querying multiple, distributed data sources, saving query results as searchable data extracts, and executing local and web-accessible analytic tools. The series of recorded tasks can then be saved as a reproducible, sharable workflow available for subsequent execution with the original or modified inputs and parameter settings. Integrated data resources include interfaces to the National Center for Biotechnology Information (NCBI) nucleotide and protein databases, the European Molecular Biology Laboratory (EMBL-Bank) non-redundant nucleotide database, the Universal Protein Resource (UniProt), and the UniProt Reference Clusters (UniRef) database. The system offers access to numerous preinstalled, curated analytic tools and also provides researchers with the option of selecting computational tools from a large list of web services including the European Molecular Biology Open Software Suite (EMBOSS), BioMoby, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The system further allows users to integrate local command line tools residing on their own computers through a client-side Java applet.

Proper citation: BioExtract (RRID:SCR_005397) Copy   

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http://llama.mshri.on.ca/synergizer/translate/

The Synergizer database is a growing repository of gene and protein identifier synonym relationships. This tool facilitates the conversion of identifiers from one naming scheme (a.k.a namespace) to another. The Synergizer is a service for translating between sets of biological identifiers. It can, for example, translate Ensembl Gene IDs to Entrez Gene IDs, or IPI IDs to HGNC gene symbols, and much more. Unlike some other tools for this purpose, The Synergizer is simple and easy to learn. The Synergizer works via a web interface (for users who are not programmers) or through a web service (for programmatic access).

Proper citation: Synergizer (RRID:SCR_005308) Copy   

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http://users-birc.au.dk/biopv/php/fabox/

Tools for splitting, joining and otherwise manipulating FASTA format sequence files. The first tools in the toolbox is for manipulating fasta headers, cropping alignments and doing some sequence comparison allowing users to combine the description of data (often in excel spreadsheets) with the actual data (often DNA sequences). Also, producing correct input files for a range of programs seems to be problematic for the average user. Hence, some converters in some of the services have been included as well as some stand-alone converters. The converters are not necessarily meant to provide the final input file, but you''ll get a valid input file for Arlequin, MrBayes etc. - that you may further edit so it suit your needs. This means that you may need to combine several of the tools to finish your handling - but it keeps it relatively simple to use. Please note that FaBox is written in PHP and ONLY RUNS ON A WEBSERVER.

Proper citation: FaBox (RRID:SCR_005350) Copy   

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http://www.jcvi.org/cgi-bin/tigrfams/index.cgi

Consists curated multiple sequence alignments, Hidden Markov Models (HMMs) for protein sequence classification, and associated information designed to support automated annotation of (mostly prokaryotic) proteins. Starting with release 10.0, TIGRFAMs models use HMMER3, which provides excellent search speed as well as exquisite search sensitivity. See the "TIGRFAMs Complete Listing" page to review the accession, protein name, model type, and EC number (if assigned) of all models. TIGRFAMs is a member database in InterPro. The HMM libraries and supporting files are available to download and use for free from our FTP site.

Proper citation: TIGRFAMS (RRID:SCR_005493) Copy   

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

Central location for voluntary submission of genetic test information by providers including the test''s purpose, methodology, validity, evidence of the test''s usefulness, and laboratory contacts and credentials. GTR aims to advance the public health and research into the genetic basis of health and disease. GTR is accepting registration of clinical tests for Mendelian disorders, complex tests and arrays, and pharmacogenetic tests. These tests may include multiple methods and may include multiple major method categories such as biochemical, cytogenetic, and molecular tests. GTR is not currently accepting registration of tests for somatic disorders, research tests or direct-to-consumer tests.

Proper citation: Genetic Testing Registry (RRID:SCR_005565) Copy   

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http://orphelia.gobics.de/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23,2022. A metagenomic open reading frame (ORF) finding tool for the prediction of protein coding genes in short, environmental DNA sequences with unknown phylogenetic origin. The resource is based on a two-stage machine learning approach that uses linear discriminants to extract features from the ORFs. An artificial neural network then combines the features and computes a gene probability for each ORF fragment.

Proper citation: Orphelia (RRID:SCR_000119) Copy   

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http://www.gobics.de/fabian/treephyler.php

A software tool for fast taxonomic profiling of metagenomes.

Proper citation: Treephyler (RRID:SCR_000109) Copy   

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http://caps.ncbs.res.in/gendis/home.html

Genomic Distribution of structural Superfamilies identifies and classifies evolutionary related proteins at the superfamily level in whole genome databases. GenDiS has been curated in direct correspondence with SCOP and represents 4001 highly resolved domains in 1194 structural superfamilies across protein sequence databases. Sequences showing reliable homology to entries in SCOP and PASS2 databases have been obtained from the non-redundant protein sequence database and aligned. Similar alignments of the superfamily members are provided in the genome level. GenDiS provides a platform for cross genome comparison at the superfamily level. GenDis relates proteins sequence information across all strata of taxonomy. One may navigate through the database to obtain structural homologues across different levels in taxonomic classification. The nomenclature of the various genomes and their hierarchy is in direct correspondence with the taxonomy database maintained at the NCBI. Sequence homologues for the various structural members are obtained from the non-redundant protein sequence database employing sensitive sequence search methods. Multiple approaches such as PSI-BLAST, HMMsearch of the HMMer suite and an interacting motif constrained PHI-BLAST have been employed to identify homologues in the sequence databases.

Proper citation: Genomic Distribution of structural Superfamilies (RRID:SCR_007670) Copy   

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http://mendel.gene.cwru.edu/adamslab/cgi-bin/paml/pbrowser.py

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. It provides access to the results of tests for positive selection in 14,000 human genes. Multiple alignments of protein-coding regions of genes from human and other mammals were extracted from whole-genome alignments available from UC-Santa Cruz. Each gene was analyzed using the maximum likelihood tests of selection using PAML. Branch, site, and branch+site tests were performed, each with at least one matching null model.

Proper citation: Human PAML Browser (RRID:SCR_007715) Copy   

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http://dbptm.mbc.nctu.edu.tw/

dbPTM is a database that compiles information on protein post-translational modifications (PTM) such as the modified sites, solvent accessibility of surrounding amino acids, protein secondary and tertiary structures, protein domains, and protein variations. The version 2.0 of dbPTM integrates the experimentally validated PTM sites with referable literatures from Swiss-Prot, Phospho.ELM, O-GLYCBASE, and UbiProt. In all of the collected PTM information, about 25 types of PTM with enough experimentally validated sites are trained the profile hidden Markov models (HMMs) to detect the potential PTM sites with 100% specificity against Swiss-Prot proteins. To help users investigating more detail in each type of PTM, the substrate peptide specificity such as positional amino acid frequency, solvent accessibility and secondary structure surrounding the modified sites are also provided. Moreover, the information of orthologous protein clusters is provided to users for analyzing whether the PTM sites located in the evolutionary conserved regions or not., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: dbPTM: An informational repository of proteins and post-translational modifications (RRID:SCR_007619) Copy   

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http://firedb.bioinfo.cnio.es/

A database of Protein Data Bank structures, ligands and annotated functional site residues. The database can be accessed by PDB codes or UniProt accession numbers as well as keywords. FireDB contains information on every chemical compound in the PDB, including their descriptions, the PDB structures in which the compounds are found and the amino acids that are in contact with the ligand.

Proper citation: FireDB (RRID:SCR_007655) Copy   

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http://cgl.imim.es/fcp/

FCP is a publicly accessible web tool dedicated to analyzing the current state and trends of available proteome structures along the classification schemes of enzymes and nuclear receptors. It offers both graphical and quantitative data on the degree of functional coverage in that portion of the proteome by existing structures and on the bias observed in the distribution of those structures among proteins. Users can choose to search the website based on structures or ligands, and can also sort by enzyme or receptor. Users can also view data based on structural and population (species) filters.

Proper citation: Functional Coverage of the Proteome (RRID:SCR_007654) Copy   

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http://caps.ncbs.res.in/imotdb/

Comprehensive collection of spatially interacting motifs in proteins. Interacting motif database lists interacting motifs that are identified for all structural entries in PDB. Conserved patterns or finger prints are identified for individual structural entries and also grouped together for reporting common motifs shared among all superfamily members.

Proper citation: Database of Spatially Interacting Motifs in Proteins (RRID:SCR_007735) Copy   

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http://pimp.starflr.info/

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   

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http://systers.molgen.mpg.de/

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   

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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   

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http://stitch.embl.de

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   

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http://topdb.enzim.hu

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   

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http://mips.gsf.de/simap/

It provides a database based on a pre-computed similarity matrix covering the similarity space formed by >4 million amino acid sequences from public databases and completely sequenced genomes. The database is capable of handling very large datasets and is updated incrementally. For sequence similarity searches and pairwise alignments, we implemented a grid-enabled software system, which is based on FASTA heuristics and the Smith Waterman algorithm. SimpleSIMAP and AdvancedSIMAP retrieve homologs for given protein sequences that need to be contained in the SIMAP database. While SimpleSIMAP provides only selected parameters and preconfigured search spaces, the AdvancedSIMAP allows the user to specify search space, filtering and sorting parameters in a flexible manner. Both types of queries result in lists of homologs that are linked in turn to their homologs. So the web interfaces allow users to explore quickly and interactively the protein world by homology. Sponsors: SIMAP is supported by the Department of Genome Oriented Bioinformatics of the Technische Universitt Mnchen and the Institute for Bioinformatics of the GSF-National Research Center for Environment and Health.

Proper citation: SIMAP (RRID:SCR_007927) Copy   

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