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http://knhi.de/en/network/

Association of physicians, scientists, academics, research institutes and self-help groups that provides and nurtures interdisciplinary cooperation between research and primary, secondary and tertiary health care. Many internationally renowned heart failure researchers and working groups live and work in Germany. Nevertheless, there is insufficient cooperation of the respective working groups and research projects in this area. In order to remain internationally competitive in the heart failure research community, excellent implementation of large scale clinical and genetic trials is indispensable. Further, deficits in the effective presentation and transfer of research findings into clinical practice need to be addressed. An adequate translation of guidelines into practical, tangible instructions can facilitate clinical practice both in primary and tertiary care fundamentally. The need for action to address the research-practice-gap is obvious.

Proper citation: Competence Network Heart Failure (RRID:SCR_004979) Copy   

•   Source: SciCrunch Registry

http://hyphy.org/

Open source software package for comparative sequence analysis using stochastic evolutionary models. Used for analysis of genetic sequence data in particular the inference of natural selection using techniques in phylogenetics, molecular evolution, and machine learning.

Proper citation: HyPhy (RRID:SCR_016162) Copy   

•   Source: SciCrunch Registry

http://gentle.magnusmanske.de

Software for DNA and amino acid editing, database management, plasmid maps, It can also be used for restriction and ligation, alignments, sequencer data import, calculators, gel image display, PCR, and more.

Proper citation: Gentle (RRID:SCR_016127) Copy   

•   Source: SciCrunch Registry

http://biopp.univ-montp2.fr/wiki/index.php/Main_Page

Software providing a set of ready-to-use C++ libraries as re-usable tools to visualize, edit, print and output data for bioinformatics. It uses sequence analysis, phylogenetics, molecular evolution and population genetics to help to write programs., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Bio++ (RRID:SCR_016055) Copy   

•   Source: SciCrunch Registry

http://www.broadcvdi.org/

Platform for analysis of the genetics of cardiovascular disease.Used for searching and analysis of human genetic information linked to myocardial infarction, atrial fibrillation and related traits while protecting the integrity and confidentiality of the data.

Proper citation: Cardiovascular Disease Knowledge Portal (RRID:SCR_016536) Copy   

•   Source: SciCrunch Registry

https://www.mc.vanderbilt.edu/victr/dcc/projects/acc/index.php/Main_Page

A national consortium formed to develop, disseminate, and apply approaches to research that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research. The consortium is composed of seven member sites exploring the ability and feasibility of using EMR systems to investigate gene-disease relationships. Themes of bioinformatics, genomic medicine, privacy and community engagement are of particular relevance to eMERGE. The consortium uses data from the EMR clinical systems that represent actual health care events and focuses on ethical issues such as privacy, confidentiality, and interactions with the broader community.

Proper citation: eMERGE Network: electronic Medical Records and Genomics (RRID:SCR_007428) Copy   

•   Source: SciCrunch Registry

http://www.aneurist.org/

Project focused on cerebral aneurysms and provides integrated decision support system to assess risk of aneurysm rupture in patients and to optimize their treatments. IT infrastructure has been developeded for management and processing of vast amount of heterogeneous data acquired during diagnosis.

Proper citation: aneurIST (RRID:SCR_007427) Copy   

•   Source: SciCrunch Registry

http://wwwmgs.bionet.nsc.ru/mgs/gnw/about.shtml

GeneNetWorks is designed for accumulation of experimental data, data navigation, data analysis, and analysis of dependencies in the field of gene expression regulation. It integrates the databases and programs for processing the data about structure and function of DNA, RNA, and proteins, together with the other information resources important for gene expression description. The unique property of above described system is that all the resources within the system GeneNetWorks are divided according to the natural hierarchy of molecular genetic systems and has the following levels: (1) DNA; (2) RNA; (3) proteins; and (4) gene networks. Each module contains: 1) experimental data represented as a database or some sample; 2) program for data analysis; 3) results of an automated data processing; 4) tools for the graphical representation of these data and the results of the data analyses.

Proper citation: GeneNetWorks (RRID:SCR_008034) Copy   

•   Source: SciCrunch Registry

http://ncv.unl.edu/Angelettilab/HPV/Database.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented August 23, 2016. The Human Papillomaviruses Database collects, curates, analyzes, and publishes genetic sequences of papillomaviruses and related cellular proteins. It includes molecular biologists, sequence analysts, computer technicians, post-docs and graduate research assistants. This Web site has two main branches. The first contains our four annual data books of papillomavirus information, called Human Papillomaviruses: A Compilation and Analysis of Nucleic Acid and Amino Acid Sequences. and the second contains papillomavirus genetic sequence data. There is also a New Items location where we store the latest changes to the database or any other current news of interest. Besides the compendium, we also provide genetic sequence information for papilloma viruses and related cellular proteins. Each year they publish a compendium of papillomavirus information called Human Papillomaviruses: A Compilation and Analysis of Nucleic Acid and Amino Acid Sequences. which can now be downloaded from this Web site.

Proper citation: HPV Sequence Database (RRID:SCR_008154) Copy   

•   Source: SciCrunch Registry

http://www.animalgenome.org/pigs/nagrp.html

Database and resources on the pig genome.

Proper citation: U.S. Pig Genome Project (RRID:SCR_008151) Copy   

•   Source: SciCrunch Registry

http://csgr.pgml.uga.edu/

The objective of this project is to develop physical maps of the sorghum and rice genomes, based on BAC contigs that are cross-linked to each other and also to genetic maps and BAC islands for other large-genome crops and a library of ca. 50,000 expressed-sequence tags (EST''s) and corresponding cDNA clones, from diverse sorghum organs and developmental states. It also aims to improve understanding of genetic diversity and allelic richness that might be harbored ex situ (in gene banks) or in situ (in nature), and refine techniques for assesing allelic richness and Expedite data acquisition and utilization by a sound parnership between laboratory scientists and computational biologists. Specific goals of developing physical maps of sorghum and rice genomes include: -Enrich cross-links between sorghum and rice by mapping additional rice probes on sorghum. -Apply mapped DNA probes to macroarrays of sorghum, sugarcane, rice, and maize BACs. -Fingerprint 10x BAC libraries of Sorghum bicolor and S. propinquum. Libraries presently 3x and 6x respectively, to be expanded to 10x each. -Use fragment-matching (BAC-RF) method to determine locus-specificity in polyploids. - Contig assembly based on 1-3, plus rice BAC fingerprints generated under a separate Novartis project. -Evaluate methodology for rapid high-throughput assignment of new ESTs to BACs. -Conduct genomic sequencing in a region duplicated in both sorghum and arabidopsis. Selected BACs from sorghum(2), sugarcane, maize, rice, wheat. By improving the understanding of genetic diversity and allelic richness, the goal is to: -Sequence previously mapped sorghum DNA probes. -Discover & characterize 100 single nucleotide polymorphisms (SNPs) from cDNA markers. -Develop colorimetric high-throughput genotyping assays, and utilize to assess genetic diversity in geographically- and phenotypically-diverse sorghums. -Develop colorimetric high-throughput asssays for identifying phytochrome allelic variation, and apply these assays to a core collection representing a large set of genetic resources. -Support informatics group to streamline cataloging of DNA-level information relevant to large genetic resources collections. Lastly, the goals of expediting data acquisition and utilization include: -A new web-based resource for 3D-integration and visualization of structural and functional genomic data will be developed. -New sequence assembly and alignment software SABER (Sequence AssemBly in the presence of ERror), and PRIMAL(Practical RIgorous Multiple ALignment), will be evaluated with reference to existing standards (PHRED, PHRAP). -Specialized image processing and image analysis tools will be developed for acquistion and interpretation of qualitative and quantitative hybridization signals. To deal expeditiously with large volumes of data, parallel processing approaches will be investigated. Sponsors: * National Science Foundation (NSF) * National Sorghum Producers * University of Georgia Research Foundation (UGARF) * Georgia Research Alliance (GRA)

Proper citation: Comparative Saccharinae Genomics Resource (RRID:SCR_008153) Copy   

•   Source: SciCrunch Registry

http://www.oege.org/software/hwe-mr-calc.shtml

This portal leads to the Chi-sq Hardy-Weinberg equilibrium test calculator for biallelic markers (SNPs, indels etc), including analysis for ascertainment bias for dominant/recessive models (due to biological or technical causes.) The purpose of this web program is for estimating possible missingness and an approach to evaluating missingness under different genetic models. Mendelian randomization (MR) permits causal inference between exposures and a disease. It can be compared with randomized controlled trials. Whereas in a randomized controlled trial the randomization occurs at entry into the trial, in MR the randomization occurs during gamete formation and conception. Several factors, including time since conception and sampling variation, are relevant to the interpretation of an MR test. Particularly important is consideration of the missingness of genotypes that can be originated by chance, genotyping errors, or clinical ascertainment. Testing for Hardy-Weinberg equilibrium (HWE) is a genetic approach that permits evaluation of missingness. Through this tool, the authors demonstrate evidence of nonconformity with HWE in real data. They also perform simulations to characterize the sensitivity of HWE tests to missingness. Unresolved missingness could lead to a false rejection of causality in an MR investigation of trait-disease association. These results indicate that large-scale studies, very high quality genotyping data, and detailed knowledge of the life-course genetics of the alleles/genotypes studied will largely mitigate this risk. Sponsors: This resource is supported by an Intermediate Fellowship (grant FS/05/065/19497) from the British Heart Foundation.

Proper citation: Hardy-Weinberg Equilibrium Calculator (RRID:SCR_008371) Copy   

•   Source: SciCrunch Registry

http://cgems.cancer.gov

The project began as a pilot study to identify inherited genetic susceptibility to prostate and breast cancer. CGEMS has developed into a robust research program involving genome-wide association studies (GWASs) for a number of cancers to identify common genetic variants that affect a person''s risk of developing cancer. In collaboration with extramural scientists, NCI''s Division of Cancer Epidemiology and Genetics (DCEG) has carried out genome-wide scans for breast, prostate, pancreatic, and lung cancers, while a GWAS of bladder cancer is currently underway. By making the data available to both intramural and extramural research scientists, as well as those in the private sector through rapid posting, NIH can leverage its resources to ensure that the dramatic advances in genomics are incorporated into rigorous population-based studies. Ultimately, findings from these studies may yield new preventive, diagnostic, and therapeutic interventions for cancer. Sponsors: This resource is supported by the U.S. National Institues Of Health.

Proper citation: CGEMS (RRID:SCR_008445) Copy   

•   Source: SciCrunch Registry

http://www.snprc.org/

Center that supports studies of nonhuman primate models of human diseases, including common chronic diseases and infectious diseases and the effects that genetics and the environment have on physiological processes and disease susceptibility. SNPRC encourages the use of its resources by investigators from the national and international biomedical research communities.

Proper citation: Southwest National Primate Research Center (RRID:SCR_008292) Copy   

•   Source: SciCrunch Registry

https://beast.community/tempest

Software tool for investigating temporal signal and clocklikeness of molecular phylogenies. Used for visualization and analysis of temporally sampled sequence data to assess whether there is sufficient temporal signal in data to proceed with phylogenetic molecular clock analysis, and to identify sequences whose genetic divergence and sampling date are incongruent. Not available for downloading as of August 8, 2019.

Proper citation: TempEst (RRID:SCR_017304) Copy   

•   Source: SciCrunch Registry

https://www.ebi.ac.uk/eva/

Open access database of all types of genetic variation data from all species. Users can download data from any study, or submit their own data to archive. You can also query all variants by study, gene, chromosomal location or dbSNP identifier using our Variant Browser.

Proper citation: European Variation Archive (EVA) (RRID:SCR_017425) Copy   

•   Source: SciCrunch Registry

http://geneatlas.roslin.ed.ac.uk

Database of associations between traits and variants using UK Biobank cohort. Searchable atlas of genetic associations. Assists researchers to query UK Biobank. Provides unbiased view of phenotype and genotype associations across of traits.

Proper citation: GeneATLAS (RRID:SCR_017577) Copy   

•   Source: SciCrunch Registry

http://knightadrc.wustl.edu/

The Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) supports researchers and our surrounding community in their pursuit of answers that will lead to improved diagnosis and care for persons with Alzheimer disease (AD). The Center is committed to the long-term goal of finding a way to effectively treat and prevent AD. The Knight ADRC facilitates advanced research on the clinical, genetic, neuropathological, neuroanatomical, biomedical, psychosocial, and neuropsychological aspects of Alzheimer disease, as well as other related brain disorders.

Proper citation: Washington University School of Medicine Knight Alzheimers Disease Research Center (RRID:SCR_000210) Copy   

•   Source: SciCrunch Registry

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

Central location for voluntary submission of genetic test information by providers including the test''s purpose, methodology, validity, evidence of the test''s usefulness, and laboratory contacts and credentials. GTR aims to advance the public health and research into the genetic basis of health and disease. GTR is accepting registration of clinical tests for Mendelian disorders, complex tests and arrays, and pharmacogenetic tests. These tests may include multiple methods and may include multiple major method categories such as biochemical, cytogenetic, and molecular tests. GTR is not currently accepting registration of tests for somatic disorders, research tests or direct-to-consumer tests.

Proper citation: Genetic Testing Registry (RRID:SCR_005565) Copy   

•   Source: SciCrunch Registry

http://www.biomedbridges.eu/

Consortium of 12 Biomedical sciences research infrastructure (BMS RI) partners to develop a shared e-infrastructure to allow interoperability between data and services in the biological, medical, translational and clinical domains (providing a complex knowledge environment comprising standards, ontologies, data and services) and thus strengthen biomedical resources in Europe. The BMS RIs are on the roadmap of the European Strategy Forum on Research Infrastructures (ESFRI). Connecting several European research infrastructures brings a diversity of ethical, legal and security concerns including data security requirements for participating e-Infrastructures that are storing or processing patient-related data (or biosamples): EATRIS, ECRIN, BBMRI, EuroBioImaging and EMBL-EBI. In addition, INSTRUCT is interested in secure sample transport and in intellectual property rights; Infrafrontier stores high-throughput data from mice. BBMRI with its focus on the availability of biomaterials is currently emphasizing aspects like k-anonymity and metadata management for its data. Sharing of imaging data by Euro-BioImaging poses challenges with respect to anonymisation and intellectual property. Therefore, an ethical, regulatory and security framework for international data sharing that covers these diverse areas and different types of data (e.g. clinical trials data, mouse data, and human genotype and DNA sequence data) is of crucial importance. The outcomes will lead to real and sustained improvement in the services the biomedical sciences research infrastructures offer to the research community. Data curation and sample description will be improved by the adoption of best practices and agreed standards. Many improvements will emerge from new interactions between RIs created by data linkage and networking. Ensuring access to relevant information for all life science researchers across all BMS RIs will enable scientists to conduct and share cutting-edge research.

Proper citation: BioMedBridges (RRID:SCR_006179) Copy   

•   Source: SciCrunch Registry