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Software Python package to automate building of ML pipelines by combining flexible expression tree representation of pipelines with stochastic search algorithms such as genetic programming.
Proper citation: Tree-Based Pipeline Optimization Tool (RRID:SCR_017531) Copy
http://celeganskoconsortium.omrf.org
THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The mission of the C. elegans Gene Knockout Consortium is to facilitate genetic research of this important model system through the production of deletion alleles at specified gene targets. We choose targets based on investigator requests. Strains produced by the consortium are freely available with no restrictions to any investigator. At one time, our capacity dictated that we restrict requests to five per lab. This restriction no longer holds. Investigators are encouraged especially to register requests for functionally related groups of genes. Consortium strains are distributed by the C. elegans Genetic Center (CGC). In most cases, when you use the Consortium web site to request an existing allele, your request is forwarded automatically to the CGC. However, if you indicate that an existing allele is not satisfactory for your research, (for whatever reason), you may request that we generate another allele for the same target. Any information generated by the Consortium is entered into the official C. elegans data repository, WormBase.
Proper citation: C. elegans Gene Knockout Consortium (RRID:SCR_003000) Copy
http://www.anim.med.kyoto-u.ac.jp/nbr/default.aspx
NBRP-Rat was established to overcome limitations associated with properly utilizing existing rat resources. The collection of existing strains and genetic sub strains, phenotypic and genotypic characterization, cryopreservation of embryos, distribution of the collected rat strains, and a publicly accessible database of all assembled data are the major goals of this project. Once achieved, this unique database including the unique rat strains will become a powerful tool for biomedical research. A catalog of comparable, standardized and well characterized rat strains will lead to new and more precise research topics as well as it will facilitate biomedical sciences, drug discovery, advanced chemical research, and contributes to life sciences worldwide. As mentioned before, the major goals of NBRP-Rat are the collection, preservation and supply of rat strains. The repository includes strains from Japan and abroad, spontaneous mutants, congenic and recombinant strains as well as transgenic and mutagenized rats. Deposited rat strains are not only conserved as cryopreserved embryos and sperm. Many reference and frequently used rat strains are also maintained as living animals under SPF conditions. Furthermore, NBRP-rat provides a unique database on various rat strain phenotypes accompanied with basic genetic information. This allows scientists the selection of standardized and research specific strains. The animals themselves are provided free of charge to the research community (except for shipping costs). Sponsors: This project is one part of the National BioResource Projects (NBRP) in Japan for more than 20 species including animals, plants, microbes, tissues and DNAs. It is founded by the Japanese Ministry of Education, Culture, Sports, Science and Technology (Monkasho) and started in 2002.
Proper citation: National Bio Resource Project for the Rat. (RRID:SCR_012774) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. Knowledge base of genetic associations and human genome epidemiology including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions, and evaluation of genetic tests. This tool explores HuGENet, the Human Genome Epidemiology Network, which is a global collaboration of individuals and organizations committed to the assessment of the impact of human genome variation on population health and how genetic information can be used to improve health and prevent disease. What does HuGE Navigator offer? *HuGEpedia - an encyclopedia of human genetic variation in health and disease, includes, Phenopedia and Genopedia. Phenopedia allows you to look up gene-disease association summaries by disease, and Genopedia allows you to look up gene-disease association summaries by gene. In general, HuGEpedia is a searchable database that summarizes published articles about human disease and genetic variation, including primary studies, reviews, and meta-analyses. It provides links to Pubmed abstracts, researcher contact info, trends, and more. *HuGEtools - searching and mining the literature in human genome epidemiology, includes, HuGE Literature Finder, HuGE Investigator Browser, Gene Prospector, HuGE Watch, Variant Name Mapper, and HuGE Risk Translator. *HuGE Literature Finder finds published articles in human genome epidemiology since 2001. The search query can include genes, disease, outcome, environmental factors, author, etc. Results can be filtered by these categories. It is also possible to see all articles in the database for a particular topic, such as genotype prevalence, pharmacogenomics, or clinical trial. *HuGE Investigator Browser finds investigators in a particular field of human genome epidemiology. This info is obtained using a behind-the-scenes tool that automatically parses PubMed affiliation data. *Gene Prospector is a gateway for evaluating genes in relation to disease and risk factors. This tool allows you to enter a disease or risk factor and then supplies you with a table of genes associated w/your query that are ranked based on strength of evidence from the literature. This evidence is culled from the HuGE Literature Finder and NCBI Entrez Gene - And you're given the scoring formula. The Gene Prospector results table provides access to the Genopedia entry for each gene in the list, general info including links to other resources, SNP info, and associated literature from HuGE, PubMed, GWAS, and more. It is a great place to locate a lot of info about your disease/gene of interest very quickly. *HuGE Watch tracks the evolution of published literature, HuGE investigators, genes studied, or diseases studied in human genome epidemiology. For example, if you search Trend/Pattern for Diseases Studied you'll initially get a graph and chart of the number of diseases studied per year since 1997. You can refine these results by limiting the temporal trend to a category or study type such as Gene-gene Interaction or HuGE Review. *Variant Name Mapper maps common names and rs numbers of genetic variants using information from SNP500Cancer, SNPedia, pharmGKB, ALFRED, AlzGene, PDGene, SZgene, HuGE Navigator, LSDBs, and user submissions. *HuGE Risk Translator calculates the predictive value of genetic markers for disease risk. To do so, users must enter the frequency of risk variant, the population disease risk, and the odds ratio between the gene and disease. This information is necessary in order to yield a useful predictive result. *HuGEmix - a series of HuGE related informatics utilities and projects, includes, GAPscreener, HuGE Track, Open Source. GAPscreener is a screening tool for published literature on human genetic associations; HuGE Track is a custom track built for HuGE data in the UCSC Genome Browser; and Open Source is infrastructure for managing knowledge and information from PubMed.
Proper citation: HuGE Navigator - Human Genome Epidemiology Navigator (RRID:SCR_003172) Copy
A free, open-source, computationally efficient Java program for comparative analyses of QTL mapping data and population simulation that runs on any computer operating system. (entry from Genetic Analysis Software) It is written with a plug-in architecture for ready extensibility. The software accommodates line-cross mating designs consisting of any arbitrary sequence of selfing, backcrossing, intercrossing and haploid-doubling steps that includes map, population, and trait simulators; and is scriptable. Source code is available on request.
Proper citation: QGene (RRID:SCR_003209) Copy
http://www.alz.org/research/funding/alzheimers_research_roundtable.asp
A consortium aiming to facilitate the development and implementation of new treatments for Alzheimer's disease by collectively addressing obstacles to research and development, clinical care and public health education. The Roundtable convenes twice each year for a two-day presentation and discussion of specific topics within Alzheimer's research. Topics are selected from a list proposed and voted on by members. Roundtable members explore a broad range of Alzheimer's science topics, including: * New data and technologies that may improve the diagnosis of Alzheimer's disease, especially in its earliest and mildest stages. * Neuropsychological testing, genetic factors, and biochemical and neuroimaging biomarkers that could contribute to an earlier and more accurate Alzheimer's diagnosis. * Lessons learned about clinical trial design that may help shape future clinical trials of drugs aimed at slowing or stopping the progression of Alzheimer's. * The pros and cons of various scales as outcomes measures of clinical trials. The outputs of Roundtable meetings are published as articles in the Alzheimer's Association's journal, Alzheimer's & Dementia. The Research Roundtable also sponsors Alzheimer's Association grants. The chosen project is named Research Roundtable Sponsored Grant and the principal investigator of the project is invited to give a progress report at a Roundtable meeting.
Proper citation: Alzheimers Association Research Roundtable (RRID:SCR_004007) 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
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.broadinstitute.org/rat/public/index_main.html
Data set of pictures representing genetic linkage maps of the rat resulting from the integration of two F2 intercrosses (SHRSP x BN and FHH x ACI). Markers in common between the two crosses are connected by a line to define integration points. There are a total of 4,786 markers on these maps; 4375 WIBR/MIT CGR markers; 223 markers from the previously released Mit/Mgh rat maps and 188 markers from the National Institute of Arthritis and Musculoskeletal and Skin Diseases Arb rat maps. Pictures are drawn to a scale of 5cm (Kosombi) per inch. The changes in color of the backbone of the chromosome for each cross represents the space between any two framework loci. Markers in blue type are framework loci. Markers in green type are unique placement loci. Markers in black type are bouncy placement loci.
Proper citation: Genetic Maps of the Rat Genome (RRID:SCR_002266) 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
http://www.yandell-lab.org/software/vaast.html
A probabilistic search tool for identifying damaged genes and their disease-causing variants in personal genome sequences. VAAST combines elements of phylogenetic conservation, amino acid substitution, and aggregative approaches to variant prioritization into a single unified likelihood-framework that allows users to accurately identify damaged genes and deleterious variants. The software can score both coding (SNV, indel and splice site) and non-coding variants (SNV), evaluating the cumulative impact of both types of variants simultaneously. It can identify rare variants causing rare genetic diseases and can also use both rare and common variants to identify genes responsible for common diseases.
Proper citation: VAAST (RRID:SCR_002179) Copy
http://www.humgen.rwth-aachen.de/
Catalog of all changes detected in PKHD1 (Polycystic Kidney and Hepatic Disease 1) in a locus specific database. Investigators are invited to submit their novel data to this database. These data should be meaningful for clinical practice as well as of relevance for the reader interested in molecular aspects of polycystic kidney disease (PKD). There are also some links and information for ARPKD patients and their parents. Autosomal recessive polycystic kidney disease (ARPKD/PKHD1) is an important cause of renal-related and liver-related morbidity and mortality in childhood. This study reports mutation screening in 90 ARPKD patients and identifies mutations in 110 alleles making up a detection rate of 61%. Thirty-four of the detected mutations have not been reported previously. Two underlying mutations in 40 patients and one mutation in 30 cases are disclosed, and no mutation was detected on the remaining chromosomes. Mutations were found to be scattered throughout the gene without evidence of clustering at specific sites. PKHD1 mutation analysis is a powerful tool to establish the molecular cause of ARPKD in a given family. Direct identification of mutations allows an unequivocal diagnosis and accurate genetic counseling even in families displaying diagnostic challenges.
Proper citation: Autosomal Recessive Polycystic Kidney Disease Mutation Database (RRID:SCR_002290) Copy
https://www.genevestigator.com/gv/
A high performance search engine for gene expression that integrates thousands of manually curated public microarray and RNAseq experiments and nicely visualizes gene expression across different biological contexts (diseases, drugs, tissues, cancers, genotypes, etc.). There are two basic analysis approaches: # for a gene of interest, identify which conditions affect its expression. # for condition(s) of interest, identify which genes are specifically expressed in this/these conditions. Genevestigator builds on the deep integration of data, both at the level of data normalization and on the level of sample annotations. This deep integration allows scientists to ask new types of questions that cannot be addressed using conventional tools.
Proper citation: Genevestigator (RRID:SCR_002358) Copy
Curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species to facilitate the study of cross-species comparisons using information generated from projects supported by public funds. It currently hosts annotated whole genomes in over two dozen plant species and partial assemblies for almost a dozen wild rice species in the Ensembl browser, genetic and physical maps with genes, ESTs and QTLs locations, genetic diversity data sets, structure-function analysis of proteins, plant pathways databases (BioCyc and Plant Reactome platforms), and descriptions of phenotypic traits and mutations. The web-based displays for phenotypes include the Genes and Quantitative Trait Loci (QTL) modules. Sequence based relationships are displayed in the Genomes module using the genome browser adapted from Ensembl, in the Maps module using the comparative map viewer (CMap) from GMOD, and in the Proteins module displays. BLAST is used to search for similar sequences. Literature supporting all the above data is organized in the Literature database. In addition, Gramene now hosts a variety of web services including a Distributed Annotation Server (DAS), BLAST and a public MySQL database. Twice a year, Gramene releases a major build of the database and makes interim releases to correct errors or to make important updates to software and/or data. Additionally you can access Gramene through an FTP site.
Proper citation: Gramene (RRID:SCR_002829) Copy
http://www.hgsc.bcm.tmc.edu/content/red-flour-beetle-genome-project
This portal provides information about the Tribolium castabeum Genome Project. The Tribolium castaneum genome sequence and its analysis has been published in Nature, two companion journal issues (IBMB and DGE) and numerous other publications listed below. The red flour beetle, Tribolium castaneum, a common pest that is also a genetic model for the Coleoptera. The genome has been sequenced to 7-fold coverage using a whole genome shotgun approach and assembled using the HGSC's assembly engine, Atlas, with methods employed for the Drosophila pseudoobscura genome assembly. Approximately 90% of the genome sequence has been mapped to chromosomes in collaboration with Dick Beeman (USDA ARS) and Sue Brown (Kansas State University). Access to the Data :- Genome Assembly: The long term home of the Tribolium genome is Beetlebase. Tcas 3.0 is now available in GenBank and on our FTP site. Note there are no restrictions of any kind on the Tribolium data as it has been published. Version 2 of the assembly, Tcas_2.0 is available for download using the FTP Data link in the sidebar. The assembly is described in detail in the README in that directory. T.cas_1.0 was a preliminary genome assembly that did not include large insert paired end information and has been moved to a previous assemblies folder. A genboree browser of the Tcas2.0 sequence is available here: There are also links to the genboree browser from the blast results (at the bottom of each reported HSP) if you use the blast server on this page. The original linear scaffold file, Tcas2.0/linearScaffolds/Tcas20050914-genome, posted on the ftp site did not include singleton contigs from the assembly and thus did not fully reflect the tribolium genome sequence, missing ~4.4Mb of sequence in 1860 contigs and reptigs or approximately 2.5% of the assembled sequence. A corrected Tcas20051011-genome file containing these missing sequences is now available on the ftp site. The blast databases have also been updated to reflect this change. All other data is correct, and not affected by this change. :- BLAST Searches: The BLAST link is located in the sidebar. :* Linearized chromosome and unplaced scaffold sequences :* Assembled contigs :* Bin0 unassembled reads and Repeat reads Traces are available from the NCBI Trace Archive by using the link in the sidebar, or by using NCBI MegaBLAST with a same species or cross species query. Sponsors: Funding for this project has been provided by the National Human Genome Research Institute (NHGRI U54 HG003273), which is part of the National Institutes of Health (NIH), and the U.S. Department of Agriculture's Agricultural Research Service (USDA ARS Agreement No. 58-5430-3-338).
Proper citation: Tribolium castaneum Genome Project (RRID:SCR_002848) Copy
A Java based software tool designed to simplify and expedite the process of haplotype analysis by providing a common interface to several tasks relating to such analyses. Haploview currently allows users to examine block structures, generate haplotypes in these blocks, run association tests, and save the data in a number of formats. All functionalities are highly customizable. (entry from Genetic Analysis Software) * LD & haplotype block analysis * haplotype population frequency estimation * single SNP and haplotype association tests * permutation testing for association significance * implementation of Paul de Bakker's Tagger tag SNP selection algorithm. * automatic download of phased genotype data from HapMap * visualization and plotting of PLINK whole genome association results including advanced filtering options Haploview is fully compatible with data dumps from the HapMap project and the Perlegen Genotype Browser. It can analyze thousands of SNPs (tens of thousands in command line mode) in thousands of individuals. Note: Haploview is currently on a development and support freeze. The team is currently looking at a variety of options in order to provide support for the software. Haploview is an open source project hosted by SourceForge. The source can be downloaded at the SourceForge project site.
Proper citation: Haploview (RRID:SCR_003076) Copy
https://www.sfari.org/funding-opportunities/
The mission of SFARI is to improve the diagnosis, treatment, and prevention of autism and related developmental disorders. SFARI explores neuroscience from multiple directions, including molecular, cellular, systems, immunological, cognitive, behavioral, genetic, theoretical and computational perspectives. Funding for innovative scientific research is available through a peer-reviewed proposal process at regular intervals. Research projects are reviewed by a scientific advisory board and managed by the scientific director and a highly qualified staff. Proposals in multiple research areas are sought, to reflect the complex nature of autism. The Foundation supports innovative scientific projects where our involvement will play an essential role. In the course of this support, The Foundation is interested in partnering with other entities, or providing matching support where appropriate. The Simons Foundation has historically accepted only solicited grant proposals. These grant decisions are made by the Trustees of The Simons Foundation, who review applications on an ongoing basis. In the area of autism research, requests for proposals are issued on an annual basis. The Simons Foundation does not give grants to individuals, except through their institutions.
Proper citation: Simons Foundation Autism Research Initiative: Grant Resource (RRID:SCR_001862) Copy
http://courses.jax.org/2012/addiction.html
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. This course emphasizes genetic applications and approaches to drug addiction research through methodological instruction based on literature, data sets and informatics resources drawn from studies of addiction related phenotypes. The course includes plenary sessions on major progress in addiction genetics, and discussion sessions in which students present their work for discussion on applications of genetic methods. Students will leave the course able to design and interpret genetic and genomic studies of addiction as they relate to their specific research question, and will be able to make use of current bioinformatics resources to identify research resources and make use of public data sources in their own research.
Proper citation: Short Course on the Genetics of Addiction (RRID:SCR_005560) Copy
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
Database of genetic and molecular biology data for the model higher plant Arabidopsis thaliana. Data available includes the complete genome sequence along with gene structure, gene product information, metabolism, gene expression, DNA and seed stocks, genome maps, genetic and physical markers, publications, and information about the Arabidopsis research community. Gene product function data is updated every two weeks from the latest published research literature and community data submissions. Gene structures are updated 1-2 times per year using computational and manual methods as well as community submissions of new and updated genes. TAIR also provides extensive linkouts from data pages to other Arabidopsis resources. The data can be searched, viewed and analyzed. Datasets can also be downloaded. Pages on news, job postings, conference announcements, Arabidopsis lab protocols, and useful links are provided.
Proper citation: TAIR (RRID:SCR_004618) Copy
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