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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
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
https://scicrunch.org/resolver/SCR_002250
THIS RESOURCE IS NO LONGER IN SERVICE. Documented Jul 19, 2024. Metadatabase manually curated that provides web accessible tools related to genomics, transcriptomics, proteomics and metabolomics. Used as informative directory for multi-omic data analysis.
Proper citation: OMICtools (RRID:SCR_002250) Copy
http://proteininformationresource.org/
Integrated public bioinformatics resource to support genomic, proteomic and systems biology research and scientific studies. Provides databases and protein sequence analysis tools to scientific community, including Protein Sequence Database which grew out from the Atlas of Protein Sequence and Structure. Conducts research in biomedical text mining and ontology, computational systems biology, and bioinformatics cyberinfrastructure. In 2002 PIR, along with its international partners, EBI (European Bioinformatics Institute) and SIB (Swiss Institute of Bioinformatics), were awarded a grant from NIH to create UniProt, a single worldwide database of protein sequence and function, by unifying the PIR-PSD, Swiss-Prot, and TrEMBL databases. Currently, PIR major activities include: i) UniProt (Universal Protein Resource) development, ii) iProClass protein data integration and ID mapping, iii) PRO protein ontology, and iv) iProLINK protein literature mining and ontology development. The FTP site provides free download for iProClass, PIRSF, and PRO.
Proper citation: Protein Information Resource (RRID:SCR_002837) Copy
Only worldwide authority that provides standardized nomenclature, i.e. gene names and symbols (short form abbreviations), for all known human genes, and stores all approved symbols in the HGNC database. Approved human gene nomenclature. Database of gene symbols and names. Manually curated genes into groups based on shared characteristics such as homology, function or phenotype. Data for protein-coding genes, pseudogenes and non-coding RNAs.
Proper citation: HGNC (RRID:SCR_002827) Copy
Open source database of curated, non-redundant set of profiles derived from published collections of experimentally defined transcription factor binding sites for multicellular eukaryotes. Consists of open data access, non-redundancy and quality. JASPAR CORE is smaller set that is non-redundant and curated. Collection of transcription factor DNA-binding preferences, modeled as matrices. These can be converted into Position Weight Matrices (PWMs or PSSMs), used for scanning genomic sequences. Web interface for browsing, searching and subset selection, online sequence analysis utility and suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. New functions include clustering of matrix models by similarity, generation of random matrices by sampling from selected sets of existing models and a language-independent Web Service applications programming interface for matrix retrieval.
Proper citation: JASPAR (RRID:SCR_003030) Copy
http://r3cseq.genereg.net/Site/index.html
An R/Bioconductor package to identify chromosomal interaction regions generated by chromosome conformation capture (3C) coupled to next-generation sequencing (NGS), a technique termed 3C-seq. It performs data analysis for a number of different experimental designs, as it can analyze 3C-seq data with or without a control experiment and it can be used to facilitate data analysis for experiments with multiple replicates. The r3Cseq package provides functions to perform data normalization, statistical analysis for cis/trans interactions and visualization in order to help scientists identify genomic regions that physically interact with the given viewpoints of interest. This tool greatly facilitates hypothesis generation and the interpretation of experimental results.
Proper citation: r3Cseq (RRID:SCR_003198) 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
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.humanconnectomeproject.org/
A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.
Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy
http://thea.unice.fr/index-en.html
THIS RESOURCE IS NO LONGER IN SERVICE, on documented July 16, 2012. An integrated information processing system dedicated to the analysis of post-genomic data. It allows automatic annotation of data issued from classification systems with selected biological information (including the Gene Ontology). Users can either manually search and browse through these annotations, or automatically generate meaningful generalizations according to statistical criteria (data mining). Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: THEA - Tools for High-throughput Experiments Analysis (RRID:SCR_005802) Copy
Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.
Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy
Company provides medical laboratory services, specializing in genetic and genomic testing.
Proper citation: PacGenomics (RRID:SCR_027700) Copy
The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. Research data repository for data sharing and collaboration among investigators. Used to accelerate scientific discovery through data sharing across all of mental health and other research communities, data harmonization and reporting of research results. Infrastructure created by National Database for Autism Research (NDAR), Research Domain Criteria Database (RDoCdb), National Database for Clinical Trials related to Mental Illness (NDCT), and NIH Pediatric MRI Repository (PedsMRI).
Proper citation: NIMH Data Archive (RRID:SCR_004434) Copy
An independent, privately-held online and print publisher based in New York that serves the global community of scientists, technology professionals, and executives who use and develop the latest advanced tools in molecular biology research and molecular diagnostics. GenomeWeb's editorial mission is to serve readers with exclusive, in-depth coverage of the technology, institutions, and scientists that make up the worldwide research enterprise of molecular biology. We operate the largest online news organization focused on advanced research tools in genomics, proteomics, and bioinformatics. Our expert editors report and write with precision and clarity. GenomeWeb users can be found in major scientific organizations around the world, including biopharmaceutical companies, important research universities, biomedical institutes, and government laboratories. Our advertisers include leading suppliers of research tools, analytical instruments, and information technology. Getting started is easy - just register, and use your workplace e-mail address to maximize your access to content. Once you're logged in, you'll have complete free access to GenomeWeb Daily News, The Daily Scan, all of Genome Technology magazine, every GenomeWeb blog, and much more. GenomeWeb Free Content * GenomeWeb Daily News offers breaking news as well as feature articles on genomics, proteomics, bioinformatics, and more. Daily News covers not only the science and business news, but also regulatory and policy updates. Published online and twice daily by e-mail bulletin. * The Daily Scan is a roundup of the most interesting mainstream media articles, blog posts, and peer-reviewed literature relevant to genomic and proteomic scientists. Published daily online and by e-mail bulletin. * Genome Technology: GenomeWeb's magazine covers news, trends, people, and technologies in the systems biology field. It also includes Tech Guides, which feature expert troubleshooting advice on specific lab challenges, and Research Trend Digests. Published 10 times per year. Subscriptions to the print edition are free to active researchers in the US and $29 per year for non-scientists or anyone outside the US. Non-US researchers are eligible for a free subscription to the digital edition of Genome Technology. We may contact subscribers from time to time to requalify for the magazine, in compliance with our third-party readership audit. * Careers: Our Careers page includes content to help scientists in their jobs, with links to relevant external blog posts, profiles of alternative job paths, and more. Careers also includes our Job Listings board, where anyone can post job ads for free. * Cancer Minute: Updated daily and published by e-mail bulletin weekly, Cancer Minute rounds up the latest oncology peer-reviewed literature as well as news and blog posts. * Informatics Iron: This blog covers high-performance computing and the hardware side of bioinformatics, from GPUs to compute clusters and more. * The Sample: This blog focuses on a range of topics of interest to clinical labs, including the adoption of molecular tools, issues related to lab management, in-depth coverage of the major reference labs, and more. GenomeWeb Premium Content All GenomeWeb premium content provides readers with in-depth, exclusive coverage in key technology or application areas. These publications include business, technology, and research news; patent and IP information; product launches and upgrades; and hirings, promotions, and other people news.
Proper citation: GenomeWeb (RRID:SCR_000650) Copy
https://monarchinitiative.org/
Repository of information about model organisms, in vitro models, genes, pathways, gene expression, protein and genetic interactions, orthology, disease, phenotypes, publications, and authors, and ability to navigate multi-scale spatial and temporal phenotypes across in vivo and in vitro model systems in context of genetic and genomic data, using semantics and statistics. Discovery system provides basic and clinical science researchers, informaticists, and medical professionals with integrated interface and set of discovery tools to reveal genetic basis of disease, facilitate hypothesis generation, and identify novel candidate drug targets. Database that indexes authoritative information on experimental models of disease from MGI, RGD and ZFIN.
Proper citation: MONARCH Initiative (RRID:SCR_000824) Copy
http://mlemire.freeshell.org/SimM.README
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 6th,2023. Gene dropping simulation software. The program is a gzip'ed tar archive and is designed to run under UNIX/Linux operating system.
Proper citation: SIMM (RRID:SCR_000849) Copy
Software package that provides full solution to next generation sequencing data analysis consisting of an alignment tool (SOAPaligner/soap2), a re-sequencing consensus sequence builder (SOAPsnp), an indel finder ( SOAPindel ), a structural variation scanner ( SOAPsv ), a de novo short reads assembler ( SOAPdenovo ), and a GPU-accelerated alignment tool for aligning short reads with a reference sequence. (SOAP3/GPU)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: SOAP (RRID:SCR_000689) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. An integrated packages of tools for microarray data analysis. GEPAS provides a web-based interface that offers diverse analysis options from the early step of preprocessing (normalization of Affymetrix and two-color microarray experiments and other preprocessing options), to the final step of the functional profiling of the experiment (using Gene Ontology, pathways, PubMed abstracts etc.), which include different possibilities for clustering, gene selection, class prediction and array-comparative genomic hybridization management.
Proper citation: Gene Expression Profile Analysis Suite (RRID:SCR_008341) Copy
http://www.mknt.hu/sites/default/files/NEPSYBANK_0.doc
The Hungarian Society of Clinical Neurgenetics established a nationwide collaboration for prospective collection of human biological materials and databases from patient with neurological and psychiatric diseases. The basic triangle of the NEPSYBANK is the sample, the information and the study management. The present participants of the NEPSYBANK are the Department of Neurology and Psychiatry of the four Medical Universities (in Budapest, Debrecen, Pecs, Szeged) and the National Institute of Psychiatry and Neurology in Budapest. The NEPSYBANK is a disease based biobank collecting both phenotypical and environmental data and biological materials such as DNA/RNA, whole blood, plasma, cerebral spinal fluid, muscle / nerve / skin biopsy, brain, and fibroblast. The target of the diseases is presently (Phase I): stroke syndromes, dementias, movement disorders, motoneuron diseases, epilepsy, multiple sclerosis, schizophrenia, alcohol addiction. In the near future (Phase II.) it is planned to enlarge the scale with headaches, disorders of the peripheral nerves, disorders of neuromuscular transmission, disorders of skeletal muscle, depression, anxiety. DNA/RNA is usually extracted from whole blood, but occasionally different tissues such as muscle, brain etc. can be used as well. The extracting procedures differ among the institutes, but in all cases the concentration and the quality of the DNA/RNA must be registered in the database. Participating institutional biobanks have committed themselves to follow common quality standards, which provide access to samples after prioritization on scientific grounds only. In every case the following data are registered. 1. General data: main bank categories, age, sex, ethnicity, body height, body weight, economic stats, education, type of place of living, marital status, birth complications, alcohol, drugs, smoking. 2. Sample properties (sample ID, type of sample, date of extraction, concentration, and level of purity). General patient data as blood pressure, heart rate, internal medical status, ECG, additional diseases. Disease specific question e.g. in schizophrenia the diagnosis after DSMIV and ICD 10, detailed diagnostic questions after both classification, detailed psychiatric and neurological status, laboratory findings, rating scales, data of neuroimaging, genetic tests, applied medication (with generic name, dose, duration), adverse drug effects and other treatments. The Biobank Information Management System (BIMS) is responsible for linkage of databases containing information on the individual sample donors. If you want to have samples from the NEPSYBANK an application must be submitted containing the following information: short research plan including aims and study design, ethic application with a positive decision, specific demands regarding the right of disposition, agreements with grant organizations which regulate immaterial property, information about financing (academic grants, support from industry). All participants have the right to withdraw their samples through a simple order.
Proper citation: Hungarian Neurological-Psychiatric Biobank (RRID:SCR_003715) Copy
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