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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.mutationtaster.org/

Evaluates disease-causing potential of sequence alterations.

Proper citation: MutationTaster (RRID:SCR_010777) 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://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.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://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.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://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

http://www.deathdomain.org/

A manually curated database of protein-protein interactions for Death Domain Superfamily. The Death Domain Database provides a detailed summary of PPI data, which fits into 3 categories: interaction, characterization, and functional role. Users can find in-depth information specified in the literature on relevant analytical methods, structural information. The DD superfamily currently comprises four subfamilies: * Death domain (DD) subfamily * Death effector domain (DED) subfamily * Caspase recruitment domain (CARD) subfamily * Pyrin domain (PYD) subfamily

Proper citation: Death Domain database (RRID:SCR_013231) Copy   

•   Source: SciCrunch Registry

http://dsap.cgu.edu.tw/

A web server designed to provide a total solution to analyze small RNAs sequencing data generated by SOLEXA., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DSAP (RRID:SCR_013352) Copy   

•   Source: SciCrunch Registry

http://unicarb-db.biomedicine.gu.se

An experimental glycomic MS database initially created to meet the in-house need to store structural and MS-glycomic data. Users can search by taxonomy and tissue, mass and composition, and MS/MS.

Proper citation: UniCarb-DB (RRID:SCR_014407) Copy   

•   Source: SciCrunch Registry

http://toxodb.org/toxo/

A genome and functional genomic database for the protozoan parasite Toxoplasma gondii. It incorporates the sequence and annotation of the T. gondii ME49 strain, as well as genome sequences for the GT1, VEG and RH (Chr Ia, Chr Ib) strains. Sequence information is integrated with various other genomic-scale data, including community annotation, ESTs, gene expression and proteomics data. Organisms * Toxoplasma gondii (ME49, RH, GT1, Veg strains) * Neospora caninum * environmental isolate sequences from numerous species Tools * BLAST: Identify Sequence Similarities * Sequence Retrieval: Retrieve Specific Sequences using IDs and coordinates * PubMed and Entrez: View the Latest Toxoplasma, Neospora Pubmed and Entrez Results * Genome Browser: View Sequences and Features in the genome browser * Ancillary Genome Browse: Access Additional info like Probeset data and Toxoplasma Array info

Proper citation: ApiDB ToxoDB (RRID:SCR_013453) Copy   

•   Source: SciCrunch Registry

http://www.kazusa.or.jp/huge/

The HUGE protein database has been created to publicize the Human cDNA project at the Kazusa DNA Research Institute. This project will sequence and analyze long (>4 kb) human cDNAs and establish methods by using the sequence data how to predict the primary structure of proteins of various biological activities. Currently, it focuses on the analysis of cDNA clones encoding particularly large proteins (>50 kDa). The HUGE protein database contains various types of information derived from the predicted primary structure data of newly identified human proteins. The HUGE protein database are expected to cover various sets of large human proteins of hitherto unidentified functions. They are likely to be involved in cellular structure/motility (such as cytoskeleton, membrane skeleton, and motor proteins), gene expression and nucleic acid metabolism, cell signaling/communication (such as cellular adhesion, signal transduction, channels, and receptors), and so on.

Proper citation: HUGE - Human Unidentified Gene-Encoded large proteins (RRID:SCR_013482) Copy   

•   Source: SciCrunch Registry

http://db.systemsbiology.net/kaviar/

A database containing a compilation of SNVs, indels, and complex variants observed in humans, designed to facilitate testing for the novelty and frequency of observed variants.

Proper citation: KAVIAR (RRID:SCR_013737) Copy   

•   Source: SciCrunch Registry

http://toppcluster.cchmc.org/

A tool for performing multi-cluster gene functional enrichment analyses on large scale data (microarray experiments with many time-points, cell-types, tissue-types, etc.). It facilitates co-analysis of multiple gene lists and yields as output a rich functional map showing the shared and list-specific functional features. The output can be visualized in tabular, heatmap or network formats using built-in options as well as third-party software. It uses the hypergeometric test to obtain functional enrichment achieved via the gene list enrichment analysis option available in ToppGene.

Proper citation: ToppCluster (RRID:SCR_001503) Copy   

•   Source: SciCrunch Registry

http://statalign.github.io/

Software package for Bayesian analysis of protein, DNA and RNA sequences. It utilizes multiple alignments, phylogenetic trees and evolutionary parameters to quantify uncertainty in these analyses. It is written in Java.

Proper citation: StatAlign (RRID:SCR_001892) Copy   

•   Source: SciCrunch Registry

http://www.nactem.ac.uk/facta/

Text mining tool to discover associations between biomedical concepts from MEDLINE articles. Use the service from your browser or via a Web Service. The whole MEDLINE corpus containing more than 20 million articles is indexed with an efficient text search engine, and it allows you to navigate such associations and their textual evidence in a highly interactive manner - the system accepts arbitrary query terms and displays relevant concepts immediately. A broad range of important biomedical concepts are covered by the combination of a machine learning-based term recognizer and large-scale dictionaries for genes, proteins, diseases, and chemical compounds. There is also a FACTA+ visualization service that can be found here: http://www.nactem.ac.uk/facta-visualizer/

Proper citation: FACTA+. (RRID:SCR_001767) Copy   

•   Source: SciCrunch Registry