Tools   Select Another Resource Report Type

https://www.encodeproject.org/

Consortium to build comprehensive parts list of functional elements in human genome. This includes elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Data from 2012-present.

Proper citation: Encode (RRID:SCR_015482) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/oligo.html

Software package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).

Proper citation: oligo (RRID:SCR_015729) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/seqtools

Software for multiple sequence alignment viewing, editing and phylogeny. It includes a set of user-configurable modes to color residues used to create high-quality reference alignments.

Proper citation: Belvu (RRID:SCR_015989) Copy   

•   Source: SciCrunch Registry

http://www.alliancegenome.org/

Organization that aims to develop and maintain sustainable genome information resources to promote understanding of the genetic and genomic basis of human biology, health, and disease. The Alliance is composed of FlyBase, Mouse Genome Database (MGD), the Gene Ontology Consortium (GOC), Saccharomyces Genome Database (SGD), Rat Genome Database (RGD), WormBase, and the Zebrafish Information Network (ZFIN).

Proper citation: Alliance of Genome Resources (RRID:SCR_015850) Copy   

•   Source: SciCrunch Registry

http://bioplex.hms.harvard.edu/

Database of cell lines with each expressing a tagged version of a protein from the ORFeome collection. The overarching project goal is to determine protein interactions for every member of the collection.

Proper citation: BioPlex (RRID:SCR_016144) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/seqtools

Software for sequence alignment that is a graphical dot-matrix program for detailed comparison of two sequences.

Proper citation: Dotter (RRID:SCR_016080) Copy   

•   Source: SciCrunch Registry

https://github.com/PacificBiosciences/FALCON

Software package for aligning long sequencing reads as a diploid-aware genome assembler. Used for assembling non-inbred or rearranged heterozygous genomes.

Proper citation: Falcon (RRID:SCR_016089) Copy   

•   Source: SciCrunch Registry

http://baderlab.org/Software/EnrichmentMap

Source code of a Cytoscape plugin for functional enrichment visualization. It organizes gene-sets, such as pathways and Gene Ontology terms, into a network to reveal which mutually overlapping gene-sets cluster together.

Proper citation: EnrichmentMap (RRID:SCR_016052) Copy   

•   Source: SciCrunch Registry

https://github.com/jbelyeu/SV-plaudit

Software for rapidly curating structural variant (SVs) predictions. SV-plaudit provides a pipeline for creating image views of genomic intervals, automatically storing them in the cloud, deploying a website to view/score them, and retrieving scores for analysis.

Proper citation: SV-plaudit (RRID:SCR_016285) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/LJP/

Interactive on line tool where signatures are tagged with user selected metadata and external transcript signatures are projected onto network. Browser to visualize signatures from breast cancer cell lines treated with single molecule perturbations.

Proper citation: LINCS Joint Project - Breast Cancer Network Browser (RRID:SCR_016181) Copy   

•   Source: SciCrunch Registry

http://www.biodas.org

The Distributed Annotation System (DAS) defines a communication protocol used to exchange annotations on genomic or protein sequences. It is motivated by the idea that such annotations should not be provided by single centralized databases, but should instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is done by DAS clients. The advantages of this system are that control over the data is retained by data providers, data is freed from the constraints of specific organisations and the normal issues of release cycles, API updates and data duplication are avoided. DAS is a client-server system in which a single client integrates information from multiple servers. It allows a single machine to gather up sequence annotation information from multiple distant web sites, collate the information, and display it to the user in a single view. Little coordination is needed among the various information providers. DAS is heavily used in the genome bioinformatics community. Over the last years we have also seen growing acceptance in the protein sequence and structure communities. A DAS-enabled website or application can aggregate complex and high-volume data from external providers in an efficient manner. For the biologist, this means the ability to plug in the latest data, possibly including a user''s own data. For the application developer, this means protection from data format changes and the ability to add new data with minimal development cost. Here are some examples of DAS-enabled applications or websites for end users: :- Dalliance Experimental Web/Javascript based Genome Viewer :- IGV Integrative Genome Viewer java based browser for many genomes :- Ensembl uses DAS to pull in genomic, gene and protein annotations. It also provides data via DAS. :- Gbrowse is a generic genome browser, and is both a consumer and provider of DAS. :- IGB is a desktop application for viewing genomic data. :- SPICE is an application for projecting protein annotations onto 3D structures. :- Dasty2 is a web-based viewer for protein annotations :- Jalview is a multiple alignment editor. :- PeppeR is a graphical viewer for 3D electron microscopy data. :- DASMI is an integration portal for protein interaction data. :- DASher is a Java-based viewer for protein annotations. :- EpiC presents structure-function summaries for antibody design. :- STRAP is a STRucture-based sequence Alignment Program. Hundreds of DAS servers are currently running worldwide, including those provided by the European Bioinformatics Institute, Ensembl, the Sanger Institute, UCSC, WormBase, FlyBase, TIGR, and UniProt. For a listing of all available DAS sources please visit the DasRegistry. Sponsors: The initial ideas for DAS were developed in conversations with LaDeana Hillier of the Washington University Genome Sequencing Center.

Proper citation: Distributed Annotation System (RRID:SCR_008427) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/mpg/grail/

A tool to examine relationships between genes in different disease associated loci. Given several genomic regions or SNPs associated with a particular phenotype or disease, GRAIL looks for similarities in the published scientific text among the associated genes. As input, users can upload either (1) SNPs that have emerged from a genome-wide association study or (2) genomic regions that have emerged from a linkage scan or are associated common or rare copy number variants. SNPs should be listed according to their rs#''s and must be listed in HapMap. Genomic Regions are specified by a user-defined identifier, the chromosome that it is located on, and the start and end base-pair positions for the region. Grail can take two sets of inputs - Query regions and Seed regions. Seed regions are definitely associated SNPs or genomic regions, and Query regions are those regions that the user is attempting to evaluate agains them. In many applications the two sets are identical. Based on textual relationships between genes, GRAIL assigns a p-value to each region suggesting its degree of functional connectivity, and picks the best candidate gene. GRAIL is developed by Soumya Raychaudhuri in the labs of David Altshuler and Mark Daly at the Center for Human Genetic Research of Massachusetts General Hospital and Harvard Medical School, and the Broad Institute. GRAIL is described in manuscript, currently in preparation.

Proper citation: Gene Relationships Across Implicated Loci (RRID:SCR_008537) Copy   

•   Source: SciCrunch Registry

http://go.princeton.edu/cgi-bin/GOTermFinder

The Generic GO Term Finder finds the significant GO terms shared among a list of genes from an organism, displaying the results in a table and as a graph (showing the terms and their ancestry). The user may optionally provide background information or a custom gene association file or filter evidence codes. This tool is capable of batch processing multiple queries at once. GO::TermFinder comprises a set of object-oriented Perl modules GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. This implementation, developed at the Lewis-Sigler Institute at Princeton, depends on the GO-TermFinder software written by Gavin Sherlock and Shuai Weng at Stanford University and the GO:View module written by Shuai Weng. It is made publicly available through the GMOD project. The full source code and documentation for GO:TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Generic GO Term Finder (RRID:SCR_008870) Copy   

•   Source: SciCrunch Registry

http://www.textpresso.org/

An information extracting and processing package for biological literature that can be used online or installed locally via a downloadable software package, http://www.textpresso.org/downloads.html Textpresso's two major elements are (1) access to full text, so that entire articles can be searched, and (2) introduction of categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., methods, etc). A search engine enables the user to search for one or a combination of these categories and/or keywords within an entire literature. The Textpresso project serves the biological and biomedical research community by providing: * Full text literature searches of model organism research and subject-specific articles at individual sites. Major elements of these search engines are (1) access to full text, so that the entire content of articles can be searched, and (2) search capabilities using categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or identify one (e.g., cell, gene, allele, etc). The search engines are flexible, enabling users to query the entire literature using keywords, one or more categories or a combination of keywords and categories. * Text classification and mining of biomedical literature for database curation. They help database curators to identify and extract biological entities and facts from the full text of research articles. Examples of entity identification and extraction include new allele and gene names and human disease gene orthologs; examples of fact identification and extraction include sentence retrieval for curating gene-gene regulation, Gene Ontology (GO) cellular components and GO molecular function annotations. In addition they classify papers according to curation needs. They employ a variety of methods such as hidden Markov models, support vector machines, conditional random fields and pattern matches. Our collaborators include WormBase, FlyBase, SGD, TAIR, dictyBase and the Neuroscience Information Framework. They are looking forward to collaborating with more model organism databases and projects. * Linking biological entities in PDF and online journal articles to online databases. They have established a journal article mark-up pipeline that links select content of Genetics journal articles to model organism databases such as WormBase and SGD. The entity markup pipeline links over nine classes of objects including genes, proteins, alleles, phenotypes, and anatomical terms to the appropriate page at each database. The first article published with online and PDF-embedded hyperlinks to WormBase appeared in the September 2009 issue of Genetics. As of January 2011, we have processed around 70 articles, to be continued indefinitely. Extension of this pipeline to other journals and model organism databases is planned. Textpresso is useful as a search engine for researchers as well as a curation tool. It was developed as a part of WormBase and is used extensively by C. elegans curators. Textpresso has currently been implemented for 24 different literatures, among them Neuroscience, and can readily be extended to other corpora of text.

Proper citation: Textpresso (RRID:SCR_008737) Copy   

•   Source: SciCrunch Registry

http://hymenopteragenome.org/beebase/

Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.

Proper citation: BeeBase (RRID:SCR_008966) Copy   

•   Source: SciCrunch Registry

http://itools.loni.usc.edu/

An infrastructure for managing of diverse computational biology resources - data, software tools and web-services. The iTools design, implementation and meta-data content reflect the broad NCBC needs and expertise (www.NCBCs.org).

Proper citation: iTools (RRID:SCR_009626) Copy   

•   Source: SciCrunch Registry

http://weblogo.berkeley.edu

Web application to generate sequence logos, graphical representations of patterns within multiple sequence alignment. Designed to make generation of sequence logos easy. Sequence logo generator.

Proper citation: WEBLOGO (RRID:SCR_010236) Copy   

•   Source: SciCrunch Registry

http://www.crossmodel.org/

An international consortium whose goals are to enable faster comparative studies and develop tools that make analysis accessible to the wider scientific community. InterMOD is an open source data warehouse where users can query and input their own data, access analysis tools, and create their own InterMine. Five core mines make make up InterMOD: RGD, SGD ZFIN, MGI, and WormBase.

Proper citation: InterMOD (RRID:SCR_013808) Copy   

•   Source: SciCrunch Registry

https://github.com/fbreitwieser/pavian

Software R package for interactive analysis of metagenomics classification results with a special focus on infectious disease diagnosis. Used for analyzing and visualization of metagenomics classification results from classifiers such as Kraken, Centrifuge and MetaPhlAn. Provides an alignment viewer for validation of matches to a particular genome.

Proper citation: Pavian (RRID:SCR_016679) Copy   

•   Source: SciCrunch Registry

https://github.com/lh3/fermi

Software assembler and analysis tool for whole-genome short-gun sequencing for Illumina reads. Provides tools for error correction, sequence-to-read alignment and comparison between read sets. Used for large genomes.

Proper citation: fermi (RRID:SCR_016652) Copy   

•   Source: SciCrunch Registry