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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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://sequenceontology.org/

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   

•   Source: SciCrunch Registry

http://caintegrator-info.nci.nih.gov/rembrandt

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. REMBRANDT is a data repository containing diverse types of molecular research and clinical trials data related to brain cancers, including gliomas, along with a wide variety of web-based analysis tools that readily facilitate the understanding of critical correlations among the different data types. REMBRANDT aims to be the access portal for a national molecular, genetic, and clinical database of several thousand primary brain tumors that is fully open and accessible to all investigators (including intramural and extramural researchers), as well as the public at-large. The main focus is to molecularly characterize a large number of adult and pediatric primary brain tumors and to correlate those data with extensive retrospective and prospective clinical data. Specific data types hosted here are gene expression profiles, real time PCR assays, CGH and SNP array information, sequencing data, tissue array results and images, proteomic profiles, and patients'''' response to various treatments. Clinical trials'''' information and protocols are also accessible. The data can be downloaded as raw files containing all the information gathered through the primary experiments or can be mined using the informatics support provided. This comprehensive brain tumor data portal will allow for easy ad hoc querying across multiple domains, thus allowing physician-scientists to make the right decisions during patient treatments., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Repository of molecular brain neoplasia data (RRID:SCR_004704) Copy   

•   Source: SciCrunch Registry

http://blast.ncbi.nlm.nih.gov/Blast.cgi

Web search tool to find regions of similarity between biological sequences. Program compares nucleotide or protein sequences to sequence databases and calculates statistical significance. Used for identifying homologous sequences.

Proper citation: NCBI BLAST (RRID:SCR_004870) Copy   

•   Source: SciCrunch Registry

http://www.aftol.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented Jan 13, 2022; To enhance the understanding of the evolution of the Kingdom Fungi, 1500+ species were sampled for eight gene loci across all major fungal clades, plus a subset of taxa for a suite of morphological and ultrastructural characters with resulting data: AFTOL Molecular Database (generated by WASABI - Web Accessible Sequence Analysis for Biological Inference), Blast search the AFTOL Database (generated by WASABI), AFTOL primers (generated by WASABI), AFTOL primers by species (generated by WASABI), AFTOL alignments, and the AFTOL Structural and Biochemical Database. Users may submit samples to the AFTOL project. AFTOL is a collaboration centered around four universities in the United States: Duke University (Francois Lutzoni and Rytas Vilgalys), Clark University (David Hibbett), Oregon State University (Joey Spatafora), and University of Minnesota (David McLaughlin). Participants throughout the world have donated vouchers, taxon samples, and gene sequences. The aim of the project is to reconstruct the fungal tree of life using all available data for eight loci (nuclear ribosomal DNA: LSU, SSU, ITS (including 5.8s, ITS1 and ITS2); RNA polymerase II: RPB1, RPB2; elongation factor 1-alpha; mitochondrial SSU rDNA, and mitochondrial ATP synthase protein subunit 6). A further objective of this study is to summarize and integrate current knowledge regarding fungal subcellular features within this new phylogenetic framework. The name of the bioinformatic package developed for AFTOL is WASABI which provides an efficient communication platform to facilitate the collection and dissemination of molecular data to (and from) the laboratories and participants. All molecular data can be viewed, downloaded, verified, and corrected by the participants of AFTOL. A central goal of the WASABI interface is to establish an automated analysis framework that includes basecalling of newly generated chromatograms, contig assembly, quality verification of sequences (including a local BLAST), sequence alignment, and congruence test. Gene sequences that pass all tests and are finally verified by their authors will undergo automated phylogenetic analysis on a regular schedule. Although all steps are initially carried out noninteractively, the users can verify and correct the results at any step and thus initiate the reanalysis of dependent data.

Proper citation: AFTOL (RRID:SCR_004650) Copy   

•   Source: SciCrunch Registry

http://phast.wishartlab.com/

A web server designed to rapidly and accurately identify, annotate and graphically display prophage sequences within bacterial genomes or plasmids. It accepts either raw DNA sequence data or partially annotated GenBank formatted data and rapidly performs a number of database comparisons as well as phage cornerstone feature identification steps to locate, annotate and display prophage sequences and prophage features. Relative to other prophage identification tools, PHAST is up to 40 times faster and up to 15% more sensitive. It is also able to process and annotate both raw DNA sequence data and Genbank files, provide richly annotated tables on prophage features and prophage quality and distinguish between intact and incomplete prophage. PHAST also generates downloadable, high quality, interactive graphics that display all identified prophage components in both circular and linear genomic views. Databases available for download include Virus DB, Prophage and virus DB, Bacteria DB, and PHAST result DB. Pre-calculated genomes for viewing are also available.

Proper citation: PHAge Search Tool (RRID:SCR_005184) Copy   

•   Source: SciCrunch Registry

http://skatebase.org/

Portal supporting the North East Bioinformatics Collaborative''s project to sequence the genome of the Little Skate. Provided is a clearinghouse for Little Skate Genome Project and other publicly available Skate and Ray (Batoidea) genome data, and tools for data visualization and analysis. Little Skate Genome Project The little skate (Leucoraja erinacea) is a chondrichthyan (cartilaginous) fish native to the east coast of North America. Elasmobranchs (Skates, Rays, and Sharks) exhibit many fundamental vertebrate characteristics, including a neural crest, jaws and teeth, an adaptive immune system, and a pressurized circulatory system. These characteristics have been exploited to promote understanding about human physiology, immunology, stem cell biology, toxicology, neurobiology and regeneration. The development of standardized experimental protocols in elasmobranchs such as L. erinacea and the spiny dogfish shark (Squalus acanthias) has further positioned these organisms as important biomedical and developmental models. Despite this distinction, the only reported chondrichthyan genome is the low coverage (1.4x) draft genome of the elephant shark (Callorhinchus milii). To close the evolutionary gaps in available elasmobranch genome sequence data, and generate critical genomic resources for future biomedical study, the genome of L. erinacea is being sequenced by the North East Bioinformatics Collaborative (NEBC). As close evolutionary relatives, the little skate sequence will facilitate studies that employ dogfish shark and other elasmobranchs as model organisms. Skate tools include the SkateBLAST and the Skate Genome Browsers: Little Skate Mitochondrion, Thorny Skate Mitochondrion, and Ocellate Spot Skate Mitochondrion.

Proper citation: SkateBase (RRID:SCR_005302) Copy   

•   Source: SciCrunch Registry

http://www.glycosciences.de/modeling/sweet2/

Program that rapidly converts the primary sequence of a complex carbohydrate, as defined by standard nomenclature, directly into a reliable 3D molecular model by linking together preconstructed 3D molecular templates of monosaccharides in the manner specified by the sequence and then optimizing the 3D structure using the MM3 force field. The user interaction is supported by an input spreadsheet consisting of a grid of sugar symbol and connection type cells. Several ways to visualize and to output the generated structures and related information are implemented.

Proper citation: SWEET-DB (RRID:SCR_005324) Copy   

•   Source: SciCrunch Registry

http://edwardslab.bmcb.georgetown.edu/ws/peptideMapper/

The PeptideMapper Web-Service provides alignments of peptide sequence alignments to proteins, mRNA, EST, and HTC sequences from Genbank, RefSeq, UniProt, IPI, VEGA, EMBL, and HInvDb. This mapping infrastructure is supported, in part, by the compressed peptide sequence database infrastructure (Edwards, 2007) which enables a fast, suffix-tree based mapping of peptide sequences to gene identifiers and a gene-focused detailed mapping of peptide sequences to source sequence evidence. The PeptideMapper Web-Service can be used interactively or as a web-service using either HTTP or SOAP requests. Results of HTTP requests can be returned in a variety of formats, including XML, JSON, CSV, TSV, or XLS, and in some cases, GFF or BED; results of SOAP requests are returned as SOAP responses. The PeptideMapper Web-Service maps at most 20 peptides with length between 5 and 30 amino-acids in each request. The number of alignments returned, per peptide, gene, and sequence type, is set to 10 by default. The default can be changed on the interactive alignments search form or by using the max web-service parameter.

Proper citation: PeptideMapper (RRID:SCR_005763) Copy   

•   Source: SciCrunch Registry

http://www.jstacs.de/index.php/GeMoMa

Software tool as homology based gene prediction program that predicts gene models in target species based on gene models in evolutionary related reference species. Utilizes amino acid sequence conservation, intron position conservation, and RNA-seq data to accurately predict protein-coding transcripts. Supports combination of predictions based on several reference species allowing to transfer high quality annotation of different reference species to target species.

Proper citation: GeMoMa (RRID:SCR_017646) Copy   

•   Source: SciCrunch Registry

http://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastx&BLAST_PROGRAMS=blastx&PAGE_TYPE=BlastSearch&SHOW_DEFAULTS=on&LINK_LOC=blasthome

Web application to search protein databases using a translated nucleotide query. Translated BLAST services are useful when trying to find homologous proteins to a nucleotide coding region. Blastx compares translational products of the nucleotide query sequence to a protein database. Because blastx translates the query sequence in all six reading frames and provides combined significance statistics for hits to different frames, it is particularly useful when the reading frame of the query sequence is unknown or it contains errors that may lead to frame shifts or other coding errors. Thus blastx is often the first analysis performed with a newly determined nucleotide sequence and is used extensively in analyzing EST sequences. This search is more sensitive than nucleotide blast since the comparison is performed at the protein level.

Proper citation: BLASTX (RRID:SCR_001653) Copy   

•   Source: SciCrunch Registry

http://csg.sph.umich.edu//abecasis/MACH/index.html

A Markov Chain based software tool for haplotyping, genotype imputation and disease association analysis that can resolve long haplotypes or infer missing genotypes in samples of unrelated individuals.

Proper citation: MACH 1.0 (RRID:SCR_001759) Copy   

•   Source: SciCrunch Registry

http://www.aspergillus-genomes.org.uk/

A resource for viewing annotated genes arising from various Aspergillus sequencing and annotation projects, resulting from the merging of Central Aspergillus Data REpository (CADRE) and The Aspergillus Website, which took place in June 2008. The principal role of CADRE is to aid the Aspergillus research community by managing Aspergillus genome data and by providing visualization tools, ranging from relatively simple annotation displays to more complex data integration displays. In contrast, The Aspergillus Website provides a range of information to the medical community (i.e., clinicians, patients and scientists) regarding the genus Aspergillus and the diseases, such as Aspergillosis, that it can cause. CADRE has been implemented using the Ensembl v22 suite. This suite comprises: * a database schema, which has been devised for storing annotated eukaryotic genomes. The schema is implemented with the MySQL relational database management system. * several specialized programming modules for building interfaces (i.e., BioPerl and Ensembl API modules). * a series of programs (i.e., Perl CGI scripts using the API modules) for viewing genomic data within a web browser., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Aspergillus Genomes (RRID:SCR_001880) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.ensembl.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://camera.calit2.net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016; however, the URL provides links to associated projects and data. A suite of data query, download, upload, analysis and sharing tools serving the needs of the microbial ecology research community, and other scientists using metagenomics data.

Proper citation: Community Cyberinfrastructure for Advanced Marine Microbial Ecology Research and Analysis (RRID:SCR_002676) Copy   

•   Source: SciCrunch Registry

http://technelysium.com.au/?page_id=27

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31,2023. Software which is able to assemble data from 454 and Illumina next-generation sequencers, with up to 100,000 sequences if 2 Gb RAM is available.

Proper citation: ChromasPro (RRID:SCR_000229) Copy   

•   Source: SciCrunch Registry