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http://ligand-expo.rutgers.edu/

An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.

Proper citation: Ligand Expo (RRID:SCR_006636) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ontology-lookup/

Interactive and programmatic interfaces to query, browse and navigate an increasing number of biomedical ontologies and controlled vocabularies. It provides a web service interface to query multiple ontologies from a single location with a unified output format. It can integrate any ontology available in the Open Biomedical Ontology (OBO) format. The database can be queried to obtain information on a single term or to browse a complete ontology using AJAX. Auto-completion provides a user-friendly search mechanism. An AJAX-based ontology viewer is available to browse a complete ontology or subsets of it. A weekly MySQL database export file can be downloaded from the EBI public FTP directory.

Proper citation: Ontology Lookup Service (RRID:SCR_006596) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/mgihome/GXD/gxdgen.shtml

A unified resource that combines text-based and 3D graphical methods to store, display, and analyze mouse developmental gene expression information. The Mouse Gene Expression Information Resource resource will integrate the following components: * Gene Expression Database (GXD) - Integrates different types of expression data and provides links to many other resources to place the data into the larger biological and analytical context. * Anatomy Database - Provides the standard nomenclature for developmental anatomy. * 3D Atlas / Graphical Gene Expression Database - Provides a high-resolution digital representation of mouse anatomy reconstructed from serial sections of single embryos at each representative developmental stage enabling 3D graphical display and analysis of in situ expression data.

Proper citation: Mouse Genome Informatics: The Mouse Gene Expression Information Resource Project (RRID:SCR_006630) Copy   

•   Source: SciCrunch Registry

http://www.doi.org/

A system for identifying content objects in the digital environment. DOI names are assigned to any entity for use on digital networks. They are used to provide current information, including where they (or information about them) can be found on the Internet. Information about a digital object may change over time, including where to find it, but its DOI name will not change. The DOI System provides a framework for persistent identification, managing intellectual content, managing metadata, linking customers with content suppliers, facilitating electronic commerce, and enabling automated management of media. DOI names can be used for any form of management of any data, whether commercial or non-commercial. The DOI System is an ISO International Standard. Using DOI names as identifiers makes managing intellectual property in a networked environment much easier and more convenient, and allows the construction of automated services and transactions.

Proper citation: DOI (RRID:SCR_006632) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/niftysim/

A high-performance nonlinear finite element solver. A key feature is the option of GPU-based execution, which allows the solver to significantly out-perform equivalent commercial packages.

Proper citation: NiftySim (RRID:SCR_006591) Copy   

•   Source: SciCrunch Registry

https://wiki.nci.nih.gov/display/LexEVS/LexGrid

LexGrid (Lexical Grid) provides support for a distributed network of lexical resources such as terminologies and ontologies via standards-based tools, storage formats, and access/update mechanisms. The Lexical Grid Vision is for a distributed network of terminological resources. It is the foundation of the National Center for Biomedical Ontology BioPortal interface and web-services, and can parse OBO format, as well as other formats such as OWL. Currently, there are many terminologies and ontologies in existence. Just about every terminology has its own format, its own set of tools, and its own update mechanisms. The only thing that most of these pieces have in common with each other is their incompatibility. This makes it very hard to use these resources to their full potential. We have designed the Lexical Grid as a way to bridge terminologies and ontologies with a common set of tools, formats and update mechanisms. The Lexical Grid is: * accessible through a set of common APIs * joined through shared indices * online accessible * downloadable * loosely coupled * locally extendable * globally revised * available in web-space on web-time * cross-linked The realization of this vision requires three interlocking components, which are: * Standards - access methods and formats need to be published and openly available * Tools - standards based tools must be readily available * Content - commonly used terminologies have to be available for access and download Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: LexGrid (RRID:SCR_006627) Copy   

•   Source: SciCrunch Registry

http://www.alexaplatform.org/alexa_seq/index.htm

A method for using massively parallel paired-end transcriptome sequencing for ''alternative expression analysis''.

Proper citation: ALEXA-Seq (RRID:SCR_006700) Copy   

•   Source: SciCrunch Registry

http://rice.plantbiology.msu.edu/

Database and resource that provides sequence and annotation data for the rice genome. This website provides genome sequence from the Nipponbare subspecies of rice and annotation of the 12 rice chromosomes. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 75 tracks of annotation. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads. Rice is a model species for the monocotyledonous plants and the cereals which are the greatest source of food for the world''s population. While rice genome sequence is available through multiple sequencing projects, high quality, uniform annotation is required in order for genome sequence data to be fully utilized by researchers. The existence of a common gene set and uniform annotation allows researchers within the rice community to work from a common resource so that their results can be more easily interpreted by other scientists. The objective of this project has always been to provide high quality annotation for the rice genome. They generated, refined and updated gene models for the estimated 40,000-60,000 total rice genes, provided standardized annotation for each model, linked each model to functional annotation including expression data, gene ontologies, and tagged lines. They have provided a resource to extend the annotation of the rice genome to other plant species by providing comparative alignments to other plant species. Analysis/Tools are available including: BLAST, Locus Name Search, Functional Term Search, Protein Domain Search, Anatomy Expression Viewer, Highly Expressed Genes

Proper citation: Rice Genome Annotation (RRID:SCR_006663) Copy   

•   Source: SciCrunch Registry

http://ctsaconnect.org/

THIS RESOURCE IS NO LONGER IS SERVICE. Documented on December 5th, 2022. Semantic framework to integrate information about research activities, clinical activities, and scientific resources to facilitate the production and consumption of Linked Open Data about investigators, physicians, biomedical research resources, services, and clinical activities. The goal is to enable software to consume data from multiple sources and allow the broadest possible representation of researchers'''' and clinicians'''' activities and research products. Current research tracking and networking systems rely largely on publications, but clinical encounters, reagents, techniques, specimens, model organisms, etc., are equally valuable for representing expertise. CTSAConnect will provide linkage between semantic representations of a wide range of clinical and research data using controlled vocabularies mapped to the Unified Medical Language System (UMLS) as a bridge between the two subject areas. The data sources include data from Medicaid, hospital billing systems, CTSAShareCenter, and other CTSA resource data, eagle-i and VIVO. It allows institutions to leverage existing tools and data sources by making the information they contain more discoverable and easier to integrate. For instance, with the ISF, researchers can be characterized by organizational affiliations, grant and project participation, research resources that they have generated, and publications that they have (co)-authored. Clinicians can be characterized by training and credentials, by clinical research topic, and by the kinds of procedures and specialization that can be inferred from encounter data. LOD refers to data that has been given a specific Uniform Resource Identifier (URI), for the purpose of sharing and linking data and information on the Semantic Web. While a large amount of data is published as LOD, there remains a significant gap in the representation of research resources and clinical expertise. Researchers can be characterized by the organization to which they belong, the grants and research in which they have participated, the research topics and research resources (reagents, biospecimens, animal models) they have generated, as well as the publications they have (co)-authored. Clinician profiles on the other hand, can be defined by their credentials, clinical research topics, and the kinds of procedures and specialization that can be inferred from clinical encounter data. They believe that integrating and relating this diversity of information sources and platforms requires addressing the overlap between research resources and the attributes and activities of researchers and clinicians. CTSAconnect aims to promote integration and discovery of research activities, resources, and clinical expertise. To this end, they will publish their ontologies and LOD via their website, which will also illustrate repeatable methods and examples of how to extract, consume, and utilize this valuable new LOD using freely available tools like VIVO, eagle-i, and Google APIs. CTSAconnect is a collaboration between Oregon Health & Science University, Stony Brook University, Cornell University, Harvard University, University at Buffalo, and the University of Florida, and leverages the work of eagle-i (eagle-i.net), VIVO (vivoweb.org), and ShareCenter (ctsasharecenter.org).

Proper citation: CTSAconnect (RRID:SCR_005225) Copy   

•   Source: SciCrunch Registry

http://www.qcmg.org/bioinformatics/tiki-index.php

A single nucleotide variant caller optimised for identifying somatic variants in low cellularity cancer samples.

Proper citation: qSNP (RRID:SCR_005105) Copy   

•   Source: SciCrunch Registry

http://www.damonrunyon.org/

The Damon Runyon Cancer Research Foundation funds early career cancer researchers who have the energy, drive and creativity to become leading innovators in their fields. We identify the best young scientists in the nation and support them through four award programs: our Fellowship, Pediatric Cancer Fellowship, Clinical Investigator and Innovation Awards. Damon Runyon awards give young scientists: * Freedom to follow their own ideas, explore new paths and take risks * A prestigious endorsement that attracts further funding, advances their careers and accelerates their research * Guaranteed financial support, sparing them hours applying for grants Since 1946, Damon Runyon has invested more than $240 million in the best young minds in the nation. Our alumni include 11 Nobel Laureates and leaders of major cancer centers across the United States. Many of our 3,300 scientists have gone on to make breakthroughs in the way we prevent, diagnose and treat many forms of cancer. The Damon Runyon Cancer Research Foundation is a registered nonprofit with 501(c)(3) status.

Proper citation: Damon Runyon Cancer Research Foundation (RRID:SCR_005106) Copy   

•   Source: SciCrunch Registry

http://samtools.sourceforge.net/mpileup.shtml

Provide various utilities for manipulating alignments in the SAM format, including sorting, merging, indexing and generating alignments in a per-position format.

Proper citation: SAMtools/BCFtools (RRID:SCR_005227) Copy   

•   Source: SciCrunch Registry

http://www.raetschlab.org/suppl/mitie

Software framework for simultaneous RNA-Seq-based Transcript Identification and Quantification in Multiple Samples. They define a likelihood function based on the negative binomial distribution, use a regularization approach to select a few transcripts collectively explaining the observed read data, and show how to find the optimal solution using Mixed Integer Programming. MiTie can a) take advantage of known transcripts, b) reconstruct and quantify transcripts simultaneously in multiple samples, as well as c) resolve the location of multi-mapping reads. It is designed for genome- and assembly-based transcriptome reconstruction.

Proper citation: MiTie (RRID:SCR_005228) Copy   

•   Source: SciCrunch Registry

http://orman.sourceforge.net/Home

A software tool for resolving multi-mappings within an RNA-Seq SAM file.

Proper citation: ORMAN (RRID:SCR_005188) Copy   

•   Source: SciCrunch Registry

https://github.com/vezzi/FRC_align

Software package containing tools to process bam files in order to evaluate and analyze de novo assembly / assemblers and identify Structural Variations suspicious genomics regions. The tools have been already successfully applied in several de novo and resequencing projects. This package contains two tools: # FRCbam: tool to compute Feature Response Curves in order to validate and rank assemblies and assemblers # FindTranslocations: tool to identify chromosomal rearrangements using Mate Pairs

Proper citation: FRCbam (RRID:SCR_005189) Copy   

•   Source: SciCrunch Registry

http://www.ukzn.ac.za/

University with five campuses in the province of KwaZulu-Natal in South Africa. It was formed on 1 January 2004 after the merger between the University of Natal and the University of Durban-Westville.

Proper citation: University of KwaZulu-Natal; Durban; South Africa (RRID:SCR_005222) Copy   

•   Source: SciCrunch Registry

http://seqant.genetics.emory.edu/

A free web service and open source software package that performs rapid, automated annotation of DNA sequence variants (single base mutations, insertions, deletions) discovered with any sequencing platform. Variant sites are characterized with respect to their functional type (Silent, Replacement, 5' UTR, 3' UTR, Intronic, Intergenic), whether they have been previously submitted to dbSNP, and their evolutionary conservation. Annotated variants can be viewed directly on the web browser, downloaded in a tab delimited text file, or directly uploaded in a Browser Extended Data (BED) format to the UCSC genome browser. SeqAnt further identifies all loci harboring two or more coding sequence variants that help investigators identify potential compound heterozygous loci within exome sequencing experiments. In total, SeqAnt resolves a significant bottleneck by allowing an investigator to rapidly prioritize the functional analysis of those variants of interest.

Proper citation: SeqAnt (RRID:SCR_005186) Copy   

•   Source: SciCrunch Registry

http://stothard.afns.ualberta.ca/downloads/NGS-SNP/

A collection of command-line scripts for providing rich annotations for SNPs identified by the sequencing of transcripts or whole genomes from organisms with reference sequences in Ensembl. Included among the annotations, several of which are not available from any existing SNP annotation tools, are the results of detailed comparisons with orthologous sequences. These comparisons allow, for example, SNPs to be sorted or filtered based on how drastically the SNP changes the score of a protein alignment. Other fields indicate the names of overlapping protein domains or features, and the conservation of both the SNP site and flanking regions. NCBI, Ensembl, and Uniprot IDs are provided for genes, transcripts, and proteins when applicable, along with Gene Ontology terms, a gene description, phenotypes linked to the gene, and an indication of whether the SNP is novel or known. A ?Model_Annotations? field provides several annotations obtained by transferring in silico the SNP to an orthologous gene, typically in a well-characterized species.

Proper citation: NGS-SNP (RRID:SCR_005182) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/cga/indelocator

A software tool for calling short indels in next generation sequencing data.

Proper citation: Indelocator (RRID:SCR_005258) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.knowledgeblog.org/

Series of tutorial material covering a broad selection of topics in bioinformatics. Categories include: Bioinformatics APIs, Data integration, Events, Grid and Cloud Computing, Metabolic modelling, Reviews, Software Comparisons, Statistics, Systems Biology, Transcriptomics, Tutorials.

Proper citation: Bioinformatics Knowledgeblog (RRID:SCR_005379) Copy   

•   Source: SciCrunch Registry