Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Open source viewer / browser software for the SAM / BAM format commonly used in the assembly tasks of Next Generation Sequencing data.
Proper citation: GenoViewer (RRID:SCR_001203) Copy
http://www.broadinstitute.org/science/programs/genome-biology/computational-rd/somaticcall-manual
Software program that finds single-base differences (substitutions) between sequence data from tumor and matched normal samples. It is designed to be highly stringent, so as to achieve a low false positive rate. It takes as input a BAM file for each sample, and produces as output a list of differences (somatic mutations). Note: This software package is no longer supported and information on this page is provided for archival purposes only.
Proper citation: SomaticCall (RRID:SCR_001196) Copy
http://www.bioinformatics.org/peakanalyzer/wiki/
A set of standalone software programs for the automated processing of any genomic loci, with an emphasis on datasets consisting of ChIP-derived signal peaks. The software is able to identify individual binding / modification sites from enrichment loci, retrieve peak region sequences for motif discovery, and integrate experimental data with different classes of annotated elements throughout the genome. PeakAnalyzer requires a peak file and a feature annotation file in BED or GTF format. Complete annotation files for the current builds of the human (HG19) and mouse (MM9) genomes are provided with the software distribution.
Proper citation: PeakAnalyzer (RRID:SCR_001194) Copy
http://ishtar.sourceforge.net/
A program for designing primer pairs that amplify multiple target sequences using DNA thermodynamics and one class support vector machines. Written in Python.
Proper citation: Ishtar (RRID:SCR_000538) Copy
http://sourceforge.net/projects/denovogear/
A software for detecting de novo mutations using sequencing data. It utilizes likelihood-based error modeling to reduce the false positive rate of mutative discovery in exome analysis. It also uses fragment information to identify the parental origin of germ-line mutations.
Proper citation: DeNovoGear (RRID:SCR_000670) Copy
A service that provides low cost DNA sequencing. They utilize microfluidic technology.
Proper citation: Functional Biosciences (RRID:SCR_000943) Copy
Non profit research organization for genome sequences to advance understanding of biology of humans and pathogens in order to improve human health globally. Provides data which can be translated for diagnostics, treatments or therapies including over 100 finished genomes, which can be downloaded. Data are publicly available on limited basis, and provided more extensively upon request.
Proper citation: Wellcome Trust Sanger Institute; Hinxton; United Kingdom (RRID:SCR_011784) Copy
http://clones.invitrogen.com/cloneranger.php
The Invitrogen Clone Collection: * Ultimate ORF Clones: Full-insert sequenced human and mouse open reading frames (ORFs) in a Gateway entry vector offering the highest utility for your downstream analysis needs. * GeneStorm Clones: GeneStorm Clones are human ORFs cloned and tested for expression in a mammalian, insect, or bacterial expression system. They are sequenced for identity and classification and are not guaranteed at the nucleotide level. * Full-Length Clones: An unparalleled repository of clones enriched for full-length inserts, derived from both public and proprietary sources. * BAC/PAC Clones: Invitrogen offers several genomic libraries from a selection of tissues and sources to facilitate your research and discovery. These collections are available in a variety of formats including clones, plates, pools and high-density colony membrane filters. * Yeast Deletions: Each yeast deletion represents a unique gene-knockout of the S. cerevisiae genome. Each open reading frame is knocked out using a PCR-based gene deletion strategy. Yeast deletions are available as clones, pools, plates and complete collections. * Yeast GFP Clones: The Yeast GFP Clone Collection of S. cerevisiae tagged open reading frames were generated by Dr. Erin O''Shea and Dr. Jonathan Weissman at University of California-San Francisco. The GFP fusion proteins are integrated into the yeast chromosome through homologous recombination and are expressed using endogenous promoters.
Proper citation: Invitrogen Clones (RRID:SCR_005371) Copy
http://www.dnastar.com/t-sub-solutions-molecular-biology-Sanger-Sequence-Assembly.aspx
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software suite for the assembly and analysis of Sanger sequencing data within the SeqMan Pro application. The software's functions include: assembling reads into groups based on sequence names, trimming vector and poor quality data, restoration of sequence ends and designing of sequence primers.
Proper citation: DNASTAR: Lasergene Core Suite (RRID:SCR_000291) Copy
http://www.sanger.ac.uk/resources/software/vagrent/
Software tool set for calculating the biological consequences of genomic variations. The suite of perl modules compares genomic variations with reference genome annotations and generates the possible effects each variant may have on the transcripts it overlaps. It evaluates each variation/transcript combination and describes the effects in the mRNA, CDS and protein sequence contexts. It provides details of the sequence and position of the change within the transcript / protein as well as Sequence Ontology terms to classify its consequences.
Proper citation: VAGrENT (RRID:SCR_005180) Copy
http://www-personal.umich.edu/~jianghui/rseq/
A software toolkit for RNA sequence data analysis. It contains programs that cover several aspects of RNA-Seq data analysis such as read quality assessment, reference sequence generation, sequence mapping, and gene and isoform expressions estimations.
Proper citation: rSeq (RRID:SCR_000562) Copy
http://iimcb.genesilico.pl/MetaLocGramN/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.A tool for subcellular localization prediction of Gram-negative proteins. You can also use MetaGramLocN via SOAP. SOAP enables you to invoke our method from scripts written in your programming language of choice.
Proper citation: MetaLocGramN (RRID:SCR_003154) Copy
Data collection for Xenopus laevis and Xenopus tropicalis biology and genomics.
Proper citation: Xenbase (RRID:SCR_003280) Copy
http://brainarray.mbni.med.umich.edu/Brainarray/Database/ProbeMatchDB/ncbi_probmatch_para_step1.asp
Matches a list of microarray probes across different microrarray platforms (GeneChip, EST from different vendors, Operon Oligos) and species (human, mouse and rat), based on NCBI UniGene and HomoloGene. The capability to match protein sequence IDs has just been added to facilitate proteomic studies. The ProbeMatchDB is mainly used for the design of verification experiments or comparing the microarray results from different platforms. It can be used for finding equivalent EST clones in the Research Genetics sequence verified clone set based on results from Affymetirx GeneChips. It will also help to identify probes representing orthologous genes across human, mouse and rat on different microarray platforms.
Proper citation: ProbeMatchDB 2.0 (RRID:SCR_003433) Copy
http://virome.diagcomputing.org/#view=home
A web-application designed for scientific exploration of metagenome sequence data collected from viral assemblages occurring within a number of different environmental contexts. The VIROME informatics pipeline focuses on the classification of predicted open-reading frames (ORFs) from viral metagenomes. The portal allows you to submit your viral metagenome to be processed through the VIROME analysis pipeline, and enable you to investigate your data via the VIROME user interface., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: VIROME (RRID:SCR_004362) Copy
A collaborative ontology for the definition of sequence features used in biological sequence annotation. SO was initially developed by the Gene Ontology Consortium. Contributors to SO include the GMOD community, model organism database groups such as WormBase, FlyBase, Mouse Genome Informatics group, and institutes such as the Sanger Institute and the EBI. Input to SO is welcomed from the sequence annotation community. The OBO revision is available here: http://sourceforge.net/p/song/svn/HEAD/tree/ SO includes different kinds of features which can be located on the sequence. Biological features are those which are defined by their disposition to be involved in a biological process. Biomaterial features are those which are intended for use in an experiment such as aptamer and PCR_product. There are also experimental features which are the result of an experiment. SO also provides a rich set of attributes to describe these features such as polycistronic and maternally imprinted. The Sequence Ontologies use the OBO flat file format specification version 1.2, developed by the Gene Ontology Consortium. The ontology is also available in OWL from Open Biomedical Ontologies. This is updated nightly and may be slightly out of sync with the current obo file. An OWL version of the ontology is also available. The resolvable URI for the current version of SO is http://purl.obolibrary.org/obo/so.owl.
Proper citation: SO (RRID:SCR_004374) Copy
http://rgp.dna.affrc.go.jp/E/index.html
Rice Genome Research Program (RGP) is an integral part of the Japanese Ministry of Agriculture, Forestry and Fisheries (MAFF) Genome Research Project. RGP now aims to completely sequence the entire rice genome and subsequently to pursue integrated goals in functional genomics, genome informatics and applied genomics. It is jointly coordinated by the National Institute of Agrobiological Sciences (NIAS), a government research institute under MAFF and the Society for Techno-innovation of Agriculture, Forestry and Fisheries (STAFF), a semi-private research organization managed and supported by MAFF and a consortium of some twenty Japanese companies. The research is funded with yearly grants from MAFF and additional funds from the Japan Racing Association (JRA). It is now the leading member of the International Rice Genome Sequencing Project (IRGSP), a consortium of ten countries sharing the sequencing of the 12 rice chromosomes. The IRGSP adopts the clone-by-clone shotgun sequencing strategy so that each sequenced clone can be associated with a specific position on the genetic map and adheres to the policy of immediate release of the sequence data to the public domain. In December 2004, the IRGSP completed the sequencing of the rice genome. The high-quality and map-based sequence of the entire genome is now available in public databases.
Proper citation: Rice Genome Research Project (RRID:SCR_002268) Copy
http://www.structuralgenomics.org/
The Structural Genomics Project aims at determination of the 3D structure of all proteins. It also aims to reduce the cost and time required to determine three-dimensional protein structures. It supports selection, registration, and tracking of protein families and representative targets. This aim can be achieved in four steps : -Organize known protein sequences into families. -Select family representatives as targets. -Solve the 3D structure of targets by X-ray crystallography or NMR spectroscopy. -Build models for other proteins by homology to solved 3D structures. PSI has established a high-throughput structure determination pipeline focused on eukaryotic proteins. NMR spectroscopy is an integral part of this pipeline, both as a method for structure determinations and as a means for screening proteins for stable structure. Because computational approaches have estimated that many eukaryotic proteins are highly disordered, about 1 year into the project, CESG began to use an algorithm. The project has been organized into two separate phases. The first phase was dedicated to demonstrating the feasibility of high-throughput structure determination, solving unique protein structures, and preparing for a subsequent production phase. The second phase, PSI-2, has focused on implementing the high-throughput structure determination methods developed in PSI-1, as well as homology modeling and addressing bottlenecks like modeling membrane proteins. The first phase of the Protein Structure Initiative (PSI-1) saw the establishment of nine pilot centers focusing on structural genomics studies of a range of organisms, including Arabidopsis thaliana, Caenorhabditis elegans and Mycobacterium tuberculosis. During this five-year period over 1,100 protein structures were determined, over 700 of which were classified as unique due to their < 30% sequence similarity with other known protein structures. The primary goal of PSI-1 was to develop methods to streamline the structure determination process, resulted in an array of technical advances. Several methods developed during PSI-1 enhanced expression of recombinant proteins in systems like Escherichia coli, Pichia pastoris and insect cell lines. New streamlined approaches to cell cloning, expression and protein purification were also introduced, in which robotics and software platforms were integrated into the protein production pipeline to minimize required manpower, increase speed, and lower costs. The goal of the second phase of the Protein Structure Initiative (PSI-2) is to use methods introduced in PSI-1 to determine a large number of proteins and continue development in streamlining the structural genomics pipeline. Currently, the third phase of the PSI is being developed and will be called PSI: Biology. The consortia will propose work on substantial biological problems that can benefit from the determination of many protein structures Sponsors: PSI is funded by the U.S. National Institute of General Medical Sciences (NIGMS),
Proper citation: Protein Structure Initiative (RRID:SCR_002161) Copy
Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.
Proper citation: Ensembl (RRID:SCR_002344) Copy
http://www.ncbi.nlm.nih.gov/SNP/
Database as central repository for both single base nucleotide substitutions and short deletion and insertion polymorphisms. Distinguishes report of how to assay SNP from use of that SNP with individuals and populations. This separation simplifies some issues of data representation. However, these initial reports describing how to assay SNP will often be accompanied by SNP experiments measuring allele occurrence in individuals and populations. Community can contribute to this resource.
Proper citation: dbSNP (RRID:SCR_002338) Copy
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the ASWG Resources search. From here you can search through a compilation of resources used by ASWG and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that ASWG has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on ASWG then you can log in from here to get additional features in ASWG such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into ASWG you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the sources that were queried against in your search that you can investigate further.
Here are the categories present within ASWG that you can filter your data on
Here are the subcategories present within this category that you can filter your data on
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.