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http://www.cbioc.com/en/

Commercial organization that discovers, validates & analyzes genomic biomarkers with a focus on body fluid samples. Take advantage of their proven expertise in biomarker signature development and speed up your biomarker studies.

Proper citation: Comprehensive Biomarker Center (RRID:SCR_003901) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov

A portal to biomedical and genomic information. NCBI creates public databases, conducts research in computational biology, develops software tools for analyzing genome data, and disseminates biomedical information for the better understanding of molecular processes affecting human health and disease.

Proper citation: NCBI (RRID:SCR_006472) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/

Biomedical and genomic research center located in Cambridge, Massachusetts, United States. Nonprofit research organization under the name Broad Institute Inc., and is partners with Massachusetts Institute of Technology, Harvard University, and the five Harvard teaching hospitals. Dedicated to advance understanding of biology and treatment of human disease to improve human health.

Proper citation: Broad Institute (RRID:SCR_007073) Copy   

•   Source: SciCrunch Registry

http://www.jax.org/index.html

An independent, nonprofit organization focused on mammalian genetics research to advance human health. Their mission is to discover the genetic basis for preventing, treating, and curing human disease, and to enable research for the global biomedical community. Jackson Laboratory breeds and manages colonies of mice as resources for other research institutions and laboratories, along with providing software and techniques. Jackson Lab also conducts genetic research and provides educational material for various educational levels.

Proper citation: Jackson Laboratory (RRID:SCR_004633) Copy   

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https://github.com/cwhelan/cloudbreak

Software providing a Hadoop-based genomic structural variation (SV) caller for Illumina paired-end DNA sequencing data. It contains a full pipeline for aligning data in the form of FASTQ files using alignment pipelines that generate many possible mappings for every read, in the Hadoop framework. It then contains Hadoop jobs for computing genomic features from the alignments, and for calling insertion and deletion variants from those features.

Proper citation: Cloudbreak (RRID:SCR_005097) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/molbiolib/

A compact, portable, and extensively tested C++11 software framework and set of applications tailored to the demands of next-generation sequencing data and applicable to many other applications. It is designed to work with common file formats and data types used both in genomic analysis and general data analysis. A central relational-database-like Table class is a flexible and powerful object to intuitively represent and work with a wide variety of tabular datasets, ranging from alignment data to annotations. MolBioLib includes programs to perform a wide variety of analysis tasks such as computing read coverage, annotating genomic intervals, and novel peak calling with a wavelet algorithm. This package assumes fluency in both UNIX and C++.

Proper citation: MolBioLib (RRID:SCR_005372) Copy   

•   Source: SciCrunch Registry

http://statgenpro.psychiatry.hku.hk/limx/kggseq/

A biological Knowledge-based mining platform for Genomic and Genetic studies using Sequence data. The software platform, constituted of bioinformatics and statistical genetics functions, makes use of valuable biologic resources and knowledge for sequencing-based genetic mapping of variants / genes responsible for human diseases / traits. It facilitates geneticists to fish for the genetic determinants of human diseases / traits in the big sea of DNA sequences. KGGSeq has paid attention to downstream analysis of genetic mapping. The framework was implemented to filter and prioritize genetic variants from whole exome sequencing data.

Proper citation: KGGSeq (RRID:SCR_005311) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/hydra-sv/

Software that detects structural variation (SV) breakpoints by clustering discordant paired-end alignments whose signatures corroborate the same putative breakpoint. Hydra can detect breakpoints caused by all classes of structural variation. Moreover, it was designed to detect variation in both unique and duplicated genomic regions; therefore, it will examine paired-end reads having multiple discordant alignments. Hydra does not attempt to classify SV breakpoints based on the mapping distances and orientations of each breakpoint cluster, it merely detects and reports breakpoints. This is an intentional decision, as it was observed that in loci affected by complex rearrangements, the type of variant suggested by the breakpoint signature is not always correct. Hydra does report the orientations, distances, number of supporting read-pairs, etc., for each breakpoint. It is suggested that downstream methods be used to classify variants based on the genomic features that they overlap and the co-occurrence of other breakpoints. For example, they developed BEDTools for exactly this purpose and the breakpoints reported by Hydra are in the BEDPE format used by BEDTools. Future releases of Hydra will include scripts that assist in the classification process.

Proper citation: Hydra (RRID:SCR_005260) Copy   

•   Source: SciCrunch Registry

https://www.wtccc.org.uk/

Consortium of 50 research groups across the UK to harness the power of newly-available genotyping technologies to improve our understanding of the aetiological basis of several major causes of global disease. The consortium has gathered genotype data for up to 500,000 sites of genome sequence variation (single nucleotide polymorphisms or SNPs) in samples ascertained for the disease phenotypes. Analysis of the genome-wide association data generated has lead to the identification of many SNPs and genes showing evidence of association with disease susceptibility, some of which will be followed up in future studies. In addition, the Consortium has gained important insights into the technical, analytical, methodological and biological aspects of genome-wide association analysis. The core of the study comprised an analysis of 2,000 samples from each of seven diseases (type 1 diabetes, type 2 diabetes, coronary heart disease, hypertension, bipolar disorder, rheumatoid arthritis and Crohn's disease). For each disease, the case samples have been ascertained from sites widely distributed across Great Britain, allowing us to obtain considerable efficiencies by comparing each of these case populations to a common set of 3,000 nationally-ascertained controls also from England, Scotland and Wales. These controls come from two sources: 1,500 are representative samples from the 1958 British Birth Cohort and 1,500 are blood donors recruited by the three national UK Blood Services. One of the questions that the WTCCC study has addressed relates to the relative merits of these alternative strategies for the generation of representative population cohorts. Genotyping for this main Case Control study was conducted by Affymetrix using the (commercial) Affymetrix 500K chip. As part of this study a total of 17,000 samples were typed for 500,000 SNPs. There are two additional components to the study. First, the WTCCC award is part-funding a study of host resistance to infectious diseases in African populations. The same approach has been used to type 2,000 cases of tuberculosis (TB) and 2,000 cases of malaria, as well as 2,000 shared controls. As well as addressing diseases of major global significance, and extending WTCCC coverage into the area of infectious disease, the inclusion of samples of African origin has obvious benefits with respect to methodological aspects of genome-wide association analysis. Second, the WTCCC has, for four additional diseases (autoimmune thyroid disease, breast cancer, ankylosing spondylitis, multiple sclerosis), completed an analysis of 15,000 SNPs designed to represent a large proportion of the known non-synonymous coding SNPs across the genome. This analysis has been performed at the WTSI using a custom Infinium chip (Illumina). Data release The genotypic data of the control samples (1958 British Birth Cohort and UK Blood Service) and from seven diseases analyzed in the main study are now available to qualified researchers. Summary genotype statistics for these collections are available directly from the website. Access to the individual-level genotype data and summary genotype statistics is by application to the Consortium Data Access Committee (CDAC) and approval subject to a Data Access Agreement. WTCCC2: A further round of GWA studies were funded in April 2008. These include 15 WTCCC-collaborative studies and 12 independent studies be supported totaling approximately 120,000 samples. Many of the studies represent major international collaborative networks that have together assembled large sample collections. WTCCC2 will perform genome-wide association studies in 13 disease conditions: Ankylosing spondylitis, Barrett's oesophagus and oesophageal adenocarcinoma, glaucoma, ischaemic stroke, multiple sclerosis, pre-eclampsia, Parkinson's disease, psychosis endophenotypes, psoriasis, schizophrenia, ulcerative colitis and visceral leishmaniasis. WTCCC2 will also investigate the genetics of reading and mathematics abilities in children and the pharmacogenomics of statin response. Over 60,000 samples will be analyzed using either the Affymetrix v6.0 chip or the Illumina 660K chip. The WTCCC2 will also genotype 3,000 controls each from the 1958 British Birth cohort and the UK Blood Service control group, and the 6,000 controls will be genotyped on both the Affymetrix v6.0 and Illumina 1.2M chips. WTCCC3: The Wellcome Trust has provided support for a further round of GWA studies in January 2009. These include 5 WTCCC-collaborative studies to be carried out in WTCCC3 and 5 independent studies, across a range of diseases. Many of the studies represent major international collaborative networks that have together assembled large sample collections. WTCCC3 will perform genome-wide association studies in the following 4 disease conditions: primary biliary cirrhosis, anorexia nervosa, pre-eclampsia in UK subjects, and the interactions between donor and recipient DNA related to early and late renal transplant dysfunction. The WTCCC3 will also carry out a pilot in a study of the genetics of host control of HIV-1 infection. Over 40,000 samples will be analyzed using the Illumina 660K chip. The WTCCC3 will utilize the 6,000 control genotypes generated by the WTCCC2.

Proper citation: Wellcome Trust Case Control Consortium (RRID:SCR_001973) Copy   

•   Source: SciCrunch Registry

http://icbi.at/software/gpviz/gpviz.shtml

A versatile Java-based software used for dynamic gene-centered visualization of genomic regions and/or variants.

Proper citation: GPViz (RRID:SCR_000346) Copy   

•   Source: SciCrunch Registry

https://arvados.org/

Bioinformatics platform for storing, organizing, processing, and sharing genomic and other biomedical big data. Designed to make it easier for bioinformaticians to develop analyses, developers to create genomic web applications and IT administers to manage large-scale compute and storage genomic resources. Designed to run on top of cloud operating systems such as Amazon Web Services and OpenStack. Currently, there are implementations that work on AWS and Xen+Debian/Ubuntu. Functionally, Arvados has two major sets of capabilities: (a) data management and (b) compute management.

Proper citation: Arvados (RRID:SCR_002223) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/genes.shtml

Searchable database of mouse genes, DNA segments, cytogenetic markers and QTLs. MGI provides access to integrated data on mouse genes and genome features, from sequences and genomic maps to gene expression and disease models.

Proper citation: Genes, Genome Features and Maps (RRID:SCR_017524) Copy   

•   Source: SciCrunch Registry

http://www.vetmed.wisc.edu/ms-phd/

The Comparative Biomedical Sciences Graduate Degree program provides exceptional graduate research training in core areas of animal and human health including genomics, immunology, molecular and cellular biology, physiology, infectious disease, neuroscience, pharmacology and toxicology, and oncology. Seventy-five faculty members in a diverse number of UW departments including Bacteriology, Biochemistry, Medical Microbiology and Immunology, Medicine, Oncology, Pathology, Radiology in addition to the 4 departments of the School of Veterinary Medicine are trainers in the program. These internationally recognized professors, as well as the integrative nature of our program, provide outstanding and unique research opportunities for our students. Because the University of Wisconsin is consistently ranked as one of the best 10 graduate institutions in the nation, the strength of our program is not only due to the superb research and teaching of our faculty but also due to the University as a whole. Approximately 55 students, most of whom are Ph.D. candidates, are currently enrolled in the program. Research strategies and academic curricula are tailored to the specific needs of each individual student. Graduates from our program are highly successful in the biotechnology industry and at top-ranked research institutions in the U.S. and abroad. The Comparative Biomedical Sciences Graduate Program offers a diverse number of research opportunities in multiple fields of study. A brief description of some of the major areas of research being performed by faculty affiliated with the Comparative Biomedical Sciences Graduate Program is provided below. Use the pull down menu above or click on the heading to find faculty members doing research in these areas. Sponsors: CBMS is supported by the University of Wisconsin

Proper citation: Comparative Biomedical Sciences Graduate Program (RRID:SCR_008304) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/

Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.

Proper citation: Bioconductor (RRID:SCR_006442) Copy   

•   Source: SciCrunch Registry

http://toxodb.org/toxo/

A genome and functional genomic database for the protozoan parasite Toxoplasma gondii. It incorporates the sequence and annotation of the T. gondii ME49 strain, as well as genome sequences for the GT1, VEG and RH (Chr Ia, Chr Ib) strains. Sequence information is integrated with various other genomic-scale data, including community annotation, ESTs, gene expression and proteomics data. Organisms * Toxoplasma gondii (ME49, RH, GT1, Veg strains) * Neospora caninum * environmental isolate sequences from numerous species Tools * BLAST: Identify Sequence Similarities * Sequence Retrieval: Retrieve Specific Sequences using IDs and coordinates * PubMed and Entrez: View the Latest Toxoplasma, Neospora Pubmed and Entrez Results * Genome Browser: View Sequences and Features in the genome browser * Ancillary Genome Browse: Access Additional info like Probeset data and Toxoplasma Array info

Proper citation: ApiDB ToxoDB (RRID:SCR_013453) Copy   

•   Source: SciCrunch Registry

http://microbialgenomics.energy.gov/index.shtml

Through its Microbial Genome Program (MGP) and its Genomics:GTL (GTL) program, DOEs Office of Biological and Environmental Research (BER) has sequenced more than 485 microbial genomes and 30 microbial communities having specialized biological capabilities. Identifying these genes will help investigators discern how gene activities in whole living systems are orchestrated to solve myriad life challenges. The MGP was begun in 1994 as a spinoff from the Human Genome Program. The goal of the program was to sequence the genomes of a number of nonpathogenic microbes that would be useful in solving DOE''s mission challenges in environmental-waste cleanup, energy production, carbon cycling, and biotechnology. Past projects include microbial genome program, microbial cell project, and the Laboratory Science Program at the DOE Joint Genome Institute. The two ongoing projects are Genomics: GTL program and Community Sequencing Program at the DOE Joint Genome Institute. Sponsors: Site sponsored by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Microbial Genomics Program (RRID:SCR_008140) Copy   

•   Source: SciCrunch Registry

http://skonops.imbb.forth.gr/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on November 22, 2023. A database containing genomic/biological information on anopheline mosquitoes, with an emphasis on Anopheles gambiae, the world''''s most important malaria vector. AnoBase is an integrated, relational database of basic biological and genetic data on anopheline species, with a particular emphasis on Anopheles gambiae. It has been designed as an information source and research support tool for the broad vector biology community. Although AnoBase is not a primary genomic database that develops and provides tools to access the genome of the malaria mosquito, it nevertheless contains several sections that offer data of genomic interest such as in situ hybridization images, an integrated gene tool and direct online access to AnoXcel, the proteomic database of An. gambiae. Moreover, AnoBase also contains information on non-gambiae mosquito species and a novel section on studies related to insecticide resistance.

Proper citation: AnoBase: An Anopheles database (RRID:SCR_008166) Copy   

•   Source: SciCrunch Registry

http://locustdb.genomics.org.cn/

The migratory locust (Locusta migratoria) is an orthopteran pest and a representative member of hemimetabolous insects. Its transcriptomic data provide invaluable information for molecular entomology study of the insect and pave a way for comparative studies of other medically, agronomically, and ecologically relevant insects. This first transcriptomic database of the locust (LocustDB) has been developed, building necessary infrastructures to integrate, organize, and retrieve data that are either currently available or to be acquired in the future. It currently hosts 45,474 high quality EST sequences from the locust, which were assembled into 12,161 unigenes. This database contains original sequence data, including homologous/orthologous sequences, functional annotations, pathway analysis, and codon usage, based on conserved orthologous groups (COG), gene ontology (GO), protein domain (InterPro), and functional pathways (KEGG). It also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. LocustDB also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. It starts with the first transcriptome information for an orthopteran and hemimetabolous insect and will be extended to provide a framework for incorporation of in-coming genomic data of relevant insect groups and a workbench for cross-species comparative studies.

Proper citation: Migratory Locust EST Database (RRID:SCR_008201) Copy   

•   Source: SciCrunch Registry

http://mrna.otago.ac.nz/

Database that provides access to mRNA sequences and associated regulatory elements that were processed from Genbank. These mRNA sequences include complete genomes, which are divided into 5-prime UTRs, 3-prime UTRs, initiation sequences, termination regions and full CDS sequences. This data can be searched for a range of properties including specific mRNA sequences, mRNA motifs, codon usage, RSCU values, information content, etc.

Proper citation: Transterm (RRID:SCR_008244) Copy   

•   Source: SciCrunch Registry

http://www.primervfx.com/#welcome

PrimerParadise is an online PCR primer database for genomics studies. The database contains predesigned PCR primers for amplification of exons, genes and SNPs of almost all sequenced genomes. Primers can be used for genome-wide projects (resequencing, mutation analysis, SNP detection etc). The primers for eukaryotic genomes have been tested with e-PCR to make sure that no alternative products will be generated. Also, all eukaryotic primers have been filtered to exclude primers that bind excessively throughout the genome. Genes are amplified as amplicons. Amplicons are defined as only one genes exons containing maximaly 3000 bp long dna segments. If gene is longer than 3000 bp then it is split into the segments at length 3000 bp. So for example gene at length 5000 bp is split into two segment and for both segments there were designed a separate primerpair. If genes exons length is over 3000 bp then it is split into amplicons as well. Every SNP has one primerpair. In addition of considering repetitive sequences and mono-dinucleotide repeats, we avoid designing primers to genome regions which contain other SNPs. -There are two ways to search for primers: you can use features IDs ( for SNP primers Reference ID, for gene/exon primers different IDs (Ensembl gene IDs, HUGO IDs for human genes, LocusLink IDs, RefSeq IDs, MIM IDs, NCBI gene names, SWISSPROT IDs for bacterial genes, VEGA gene IDs for human and mouse, Sanger S.pombe systematic gene names and common gene names, S.cerevisiae GeneBanks Locus, AccNo, GI IDs and common gene names) -you can use genome regions (chromosome coordinates, chromosome bands if exists) -Currently we provide 3 primers collections: proPCR for prokaryotic organisms genes primers -euPCR for eukaryotic organisms genes/exons primers -snpPCR for eukaryotic organisms SNP primers Sponsors: PrimerStudio is funded by the University of Tartu.

Proper citation: PrimerStudio (RRID:SCR_008232) Copy   

•   Source: SciCrunch Registry