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http://andromeda.gsf.de/litminer

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The LitMiner software is a literature data-mining tool that facilitates the identification of major gene regulation key players related to a user-defined field of interest in PubMed abstracts. The prediction of gene-regulatory relationships is based on co-occurrence analysis of key terms within the abstracts. LitMiner predicts relationships between key terms from the biomedical domain in four categories (genes, chemical compounds, diseases and tissues). The usefulness of the LitMiner system has been demonstrated recently in a study that reconstructed disease-related regulatory networks by promoter modeling that was initiated by a LitMiner generated primary gene list. To overcome the limitations and to verify and improve the data, we developed WikiGene, a Wiki-based curation tool that allows revision of the data by expert users over the Internet. It is based on the annotation of key terms in article abstracts followed by statistical co-citation analysis of annotated key terms in order to predict relationships. Key terms belonging to four different categories are used for the annotation process: -Genes: Names of genes and gene products. Gene name recognition is based on Ensembl . Synonyms and aliases are resolved. -Chemical Compounds: Names of chemical compounds and their respective aliases. -Diseases and Phenotypes: Names of diseases and phenotypes -Tissues and Organs: Names of tissues and organs LitMiner uses a database of disease and phenotype terms for literature annotation. Currently, there are 2225 diseases or phenotypes, 801 tissues and organs, and 10477 compounds in the database.

Proper citation: LitMiner (RRID:SCR_008200) Copy   

•   Source: SciCrunch Registry

http://dnatraffic.ibb.waw.pl/

DNAtraffic database is dedicated to be an unique comprehensive and richly annotated database of genome dynamics during the cell life. DNAtraffic contains extensive data on the nomenclature, ontology, structure and function of proteins related to control of the DNA integrity mechanisms such as chromatin remodeling, DNA repair and damage response pathways from eight model organisms commonly used in the DNA-related study: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Escherichia coli and Arabidopsis thaliana. DNAtraffic contains comprehensive information on diseases related to the assembled human proteins. Database is richly annotated in the systemic information on the nomenclature, chemistry and structure of the DNA damage and drugs targeting nucleic acids and/or proteins involved in the maintenance of genome stability. One of the DNAtraffic database aim is to create the first platform of the combinatorial complexity of DNA metabolism pathway analysis. Database includes illustrations of pathway, damage, protein and drug. Since DNAtraffic is designed to cover a broad spectrum of scientific disciplines it has to be extensively linked to numerous external data sources. Database represents the result of the manual annotation work aimed at making the DNAtraffic database much more useful for a wide range of systems biology applications. DNAtraffic database is freely available and can be queried by the name of DNA network process, DNA damage, protein, disease, and drug.

Proper citation: DNAtraffic (RRID:SCR_008886) Copy   

•   Source: SciCrunch Registry

http://pbil.univ-lyon1.fr/databases/homolens.php

Database of homologous genes from Ensembl organisms, structured under ACNUC sequence database management system. It allows to select sets of homologous genes among species, and to visualize multiple alignments and phylogenetic trees. It is possible to search for orthologous genes in a wide range of taxons. HOMOLENS is particularly useful for comparative sequence analysis, phylogeny and molecular evolution studies. More generally, HOMOLENS gives an overall view of what is known about a peculiar gene family. Note that HOMOLENS is split into two databases on this server: HOMOLENS contains the protein sequences while HOMOLENSDNA contains the nucleotide sequences. Protein sequences of HOMOLENS have been generated by translating the CDS of HOMOLENSDNA and using associated cross-references to generate the annotations.

Proper citation: Homologous Sequences in Ensembl Animal Genomes (RRID:SCR_008356) Copy   

•   Source: SciCrunch Registry

http://rsat.ulb.ac.be/rsat/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Retrieve-ensembl-seq is included in the software suite regulatory sequence analysis tools (RSAT), allowing instant submission of retrieved sequences to further analysis tools. AVAILABILITY: retrieve-ensembl-seq is integrated in the RSAT suite: http://rsat.ulb.ac.be/rsat. Web site: http://rsat.ulb.ac.be/rsat/retrieve-ensembl-seq_form.cgi. Web services: http://rsat.ulb.ac.be/rsat/web_services/RSATWS.wsdl. Stand-alone distribution: freely available under an academic licence to download from the RSAT web site. The complete manual, a convenient tutorial and demos are available from the RSAT website. Additional help can be found on the RSAT public forum.

Proper citation: Regulatory Sequence Analysis Tools (RRID:SCR_008560) Copy   

•   Source: SciCrunch Registry

http://gump.qimr.edu.au/general/daleN/SNPSpD/

SNPSpD is a method of correcting for non-independance of single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with each other, on the basis of the spectral decomposition (SpD) of matrices of LD between SNP''s. Additionally, output from SNPSpD includes eigenvalues, principal-component coefficients, and factor loadings after varimax rotation, enabling the selection of a subset of SNPs that optimize the information in a genomic region.

Proper citation: Single Nucleotide Polymorphism Spectral Decomposition (SNPSpD) (RRID:SCR_008621) Copy   

•   Source: SciCrunch Registry

http://wwwmgs.bionet.nsc.ru/mgs/programs/panalyst/

WebProAnalyst provides web-accessible analysis for scanning the quantitative structure-activity relationships in protein families. It searches for a sequence region, whose substitutions are correlated with variations in the activities of a homologous protein set, the so-called activity modulating sites. WebProAnalyst allows users to search for the key physicochemical characteristics of the sites that affect the changes in protein activities. It enables the building of multiple linear regression and neural networks models that relate these characteristics to protein activities. WebProAnalyst implements multiple linear regression analysis, back propagation neural networks and the Structure-Activity Correlation/Determination Coefficient (SACC/SADC). A back propagation neural network is implemented as a two-layered network, one layer as input, the other as output (Rumelhart et al, 1986). WebProAnalyst uses alignment of amino acid sequences and data on protein activity (pK, Km, ED50, among others). The input data are the numerical values for the physicochemical characteristics of a site in the multiple alignment given by a slide window. The output data are the predicted activity values. The current version of WebProAnalyst handles a single activity for a single protein. The SACC/SADC may be defined as an estimate of the strongest multiple correlation between the physicochemical characteristics of a site in a multiple alignment and protein activities. The SACC/SADC coefficient makes possible the calculation of the possible highest correlation achievable for the quantitative relationship between the physicochemical properties of sites and protein activities. The SACC/SADC is a convenient means for an arrangement of positions by their functional significance. WebProAnalyst outputs a list of multiple alignment positions, the respective correlation values, also regression analysis parameters for the relationships between the amino acid physicochemical characteristics at these positions and the protein activity values.

Proper citation: Webproanalyst (RRID:SCR_008348) Copy   

•   Source: SciCrunch Registry

http://www.cmbi.ru.nl/GeneSeeker/

The GeneSeeker allows you to search across different databases simultaneously, given a known human genetic location and expression/phenotypic pattern. The GeneSeeker returns any found gene names which are located on the specified location and expressed in the specified tissue. To search for more expression location in one search, just enter them in the textbox for the expression location and separate them with logical operators (and, or, not). You can specify as many tissues as you want, the program starts 20 queries simultaneously, and then waits for a query to finish before starting another query, to keep server loads to a minimum. You can also search only for expression, just leave the cytogenetic location fields blank, and do the query. If you only want to look for one cytogenetic location, only fill in the first location field, and the GeneSeeker will search with only this one. Housekeeping genes , found in Swissprot can be excluded, or genes that are to be excluded can be specified. Human chromosome localizations are translated with an oxford-grid to mouse chromosome localizations, and then submitted to the Mgd. Sponsors: GeneSeeker is a service provided by the Centre for Molecular and Biomolecular Informatics (CMBI).

Proper citation: GeneSeeker (RRID:SCR_008347) Copy   

•   Source: SciCrunch Registry

http://tools.neb.com/NEBcutter2/

This tool will take a DNA sequence and find the large, non-overlapping open reading frames using the E.coli genetic code and the sites for all Type II and commercially available Type III restriction enzymes that cut the sequence just once. By default, only enzymes available from NEB are used, but other sets may be chosen. Just enter your sequence and submit. Further options will appear with the output. The maximum size of the input file is 1 MByte, and the maximum sequence length is 300 KBases. NEBcutter produces a variety of outputs including restriction enzyme maps, theoretical digests and links into the restriction enzyme database, REBASE (http://rebase.neb.com/rebase/rebase.html). Importantly, its table of recognition sites is updated daily from REBASE and it marks all sites that are potentially affected by DNA methylation (Dam, Dcm, etc.). Many options exist to choose the enzymes used for digestion, including all known specificities, subsets of those that are commercially available or sets of enzymes that produce compatible termini.

Proper citation: NEBcutter (RRID:SCR_010664) Copy   

•   Source: SciCrunch Registry

http://www.mutationtaster.org/

Evaluates disease-causing potential of sequence alterations.

Proper citation: MutationTaster (RRID:SCR_010777) Copy   

•   Source: SciCrunch Registry

http://www.cs.tau.ac.il/~spike/

Database of curated human signaling pathways with an associated interactive software tool for analysis and dynamic visualization of pathways. Individual pathway maps can be viewed and downloaded; the entire database may be browsed, or launched via a map viewer tool that allows dynamic visualization of the database and save networks in XGMML format that can be viewed in all generic XGMML viewers. Map Topics * Cell cycle progress and check points * DNA damage response * Programmed cell death related processes * Stress-activated transcription factors * Mitogen-activated protein kinase pathways * Immune response signaling * HEarSpike: hearing related pathways

Proper citation: SPIKE (RRID:SCR_010466) Copy   

•   Source: SciCrunch Registry

http://www.findbase.org

FINDbase Worldwide is an online repository of information about the frequency of different mutations leading to inherited disorders in various populations around the globe. Frequency data about 32 disorders, 25 genes within 98 populations covering 1226 mutations is now available. 28 curators worldwide contributed to this database containing data from 37 submissions.

Proper citation: FINDbase Worldwide (RRID:SCR_012744) Copy   

•   Source: SciCrunch Registry

http://data-analysis.charite.de/care/

Comprehensive database of cancer relevant proteins and compound interactions supported by experimental knowledge.Knowledgebase for drug-target relationships related to cancer as well as for supporting information or experimental data.

Proper citation: CancerResource (RRID:SCR_011945) Copy   

•   Source: SciCrunch Registry

http://evs.gs.washington.edu/EVS/

The goal of the project is to discover novel genes and mechanisms contributing to heart, lung and blood disorders by pioneering the application of next-generation sequencing of the protein coding regions of the human genome across diverse, richly-phenotyped populations and to share these datasets and findings with the scientific community to extend and enrich the diagnosis, management and treatment of heart, lung and blood disorders. The groups participating and collaborating in the NHLBI GO ESP include: Seattle GO - University of Washington, Seattle, WA Broad GO - Broad Institute of MIT and Harvard, Cambridge, MA WHISP GO - Ohio State University Medical Center, Columbus, OH Lung GO - University of Washington, Seattle, WA WashU GO - Washington University, St. Louis, MO Heart GO - University of Virginia Health System, Charlottesville, VA ChargeS GO - University of Texas Health Sciences Center at Houston

Proper citation: NHLBI Exome Sequencing Project (ESP) (RRID:SCR_012761) Copy   

•   Source: SciCrunch Registry

http://tools.genxpro.net/omiras/

A web server for the annotation, comparison and visualization of interaction networks of non-coding RNAs derived from small RNA-Sequencing experiments of two different conditions.

Proper citation: omiRas (RRID:SCR_010833) Copy   

•   Source: SciCrunch Registry

http://www.genoread.org/

A sequence verification pipeline where users can submit trace files to verify if a clone''s physical sequence matches its reference sequence.

Proper citation: GenoREAD (RRID:SCR_012007) 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.benoslab.pitt.edu/comir/

Data analysis service that predicts whether a given mRNA is targeted by a set of miRNAs. ComiR uses miRNA expression to improve and combine multiple miRNA targets for each of the four prediction algorithms: miRanda, PITA, TargetScan and mirSVR. The composite scores of the four algorithms are then combined using a support vector machine trained on Drosophila Ago1 IP data.

Proper citation: ComiR (RRID:SCR_013023) 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://www.fugu-sg.org/

THIS RESOURCE IS NO LONGER IN SERVICE,documented on August 16, 2019. Fugu genome is among the smallest vertebrate genomes and has proved to be a valuable reference genome for identifying genes and other functional elements such as regulatory elements in the human and other vertebrate genomes, and for understanding the structure and evolution of vertebrate genomes. This site presents version 4 of the Fugu genome, released in October 2004 by the International Fugu Genome Consortium. Fugu rubripes has a very compact genome, with less than 15 consisting of dispersed repetitive sequence, which makes it ideal for gene discovery. A draft sequence of the fugu genome was determined by the International Fugu Genome Consortium in 2002 using the ''whole-genome shotgun'' sequencing strategy. Fugu is the second vertebrate genome to be sequenced, the first being the human genome. This webpage presents the annotation made on the fourth assembly by the IMCB team using the Ensembl annotation pipeline. We are continuing with the gap filling work and linking of the scaffolds to obtain super-contigs.

Proper citation: Fugu Genome Project (RRID:SCR_013014) Copy   

•   Source: SciCrunch Registry

http://zope.bioinfo.cnio.es/plan2l/plan2l.html

A web-based online search system that integrates text mining and information extraction techniques to access systematically information useful for analyzing genetic, cellular and molecular aspects of the plant model organism Arabidopsis thaliana. The system facilitates a more efficient retrieval of information relevant to heterogeneous biological topics, from implications in biological relationships at the level of protein interactions and gene regulation, to sub-cellular locations of gene products and associations to cellular and developmental processes, i.e. cell cycle, flowering, root, leaf and seed development. Beyond single entities, also predefined pairs of entities can be provided as queries for which literature-derived relations together with textual evidences are returned.

Proper citation: PLAN2L (RRID:SCR_013346) Copy   

•   Source: SciCrunch Registry