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http://healthybrain.umn.edu/

Research forum portal to address brain status by acquiring comprehensive, multimodal data from healthy humans across the lifespan to characterize brain status, assess its change over time, and associate composite descriptors of brain status. Specifically, the measurements are acquired noninvasively by existing neuroimaging technologies (structural MRI, functional MRI, magnetic resonance spectroscopy, diffusion MRI, and magnetoencephalography); in addition, genetic, cognitive, language, and lifestyle data are acquired. Goals: * Derive the Brain Health Index- An integrative assessment of brain status derived from multimodal measurements of brain structure, function, and chemistry. * Continue acquiring data to construct the first-ever databank on brain, cognitive, language and genetic measurements for healthy people across the lifespan. * Provide a novel and unique dataset by which to: characterize brain status, assess its change over time, and associate it with genetic makeup, cognitive function, and language abilities. * Forecast future brain health and disease based on current measurements and guide physicians towards new interventions and evaluate interventions as they develop. * Extend to siblings and other family members to further assess the genetic influences and inheritability.

Proper citation: HBP: Healthy Brain Project (RRID:SCR_013137) Copy   

•   Source: SciCrunch Registry

http://rarediseases.info.nih.gov/GARD/Default.aspx

Genetic and Rare Diseases Information Center (GARD) is a collaborative effort of two agencies of the National Institutes of Health, The Office of Rare Diseases Research (ORDR) and the National Human Genome Research Institute (NHGRI) to help people find useful information about genetic conditions and rare diseases. GARD provides timely access to experienced information specialists who can furnish current and accurate information about genetic and rare diseases. So far, GARD has responded to 27,635 inquiries on about 7,147 rare and genetic diseases. Requests come not only from patients and their families, but also from physicians, nurses and other health-care professionals. GARD also has proved useful to genetic counselors, occupational and physical therapists, social workers, and teachers who work with people with a genetic or rare disease. Even scientists who are studying a genetic or rare disease and who need information for their research have contacted GARD, as have people who are taking part in a clinical study. Community leaders looking to help people find resources for those with genetic or rare diseases and advocacy groups who want up-to-date disease information for their members have contacted GARD. And members of the media who are writing stories about genetic or rare diseases have found the information GARD has on hand useful, accurate and complete. GARD has information on: :- What is known about a genetic or rare disease. :- What research studies are being conducted. :- What genetic testing and genetic services are available. :- Which advocacy groups to contact for a specific genetic or rare disease. :- What has been written recently about a genetic or rare disease in medical journals. GARD information specialists get their information from: :- NIH resources. :- Medical textbooks. :- Journal articles. :- Web sites. :- Advocacy groups, and their literature and services. :- Medical databases.

Proper citation: Genetic and Rare Diseases Information Center (RRID:SCR_008695) Copy   

•   Source: SciCrunch Registry

https://atgu.mgh.harvard.edu/plinkseq/

An open-source C/C++ library for working with human genetic variation data. The specific focus is to provide a platform for analytic tool development for variation data from large-scale resequencing projects, particularly whole-exome and whole-genome studies. However, the library could in principle be applied to other types of genetic studies, including whole-genome association studies of common SNPs. (entry from Genetic Analysis Software)

Proper citation: PLINK/SEQ (RRID:SCR_013193) Copy   

•   Source: SciCrunch Registry

http://eyegene.ophthy.med.umich.edu/madeline/

Software tool designed for preparing, visualizing, and exploring human pedigree data used in genetic linkage studies. It converts pedigree and marker data into formats required by popular linkage analysis packages, provides powerful ways to query pedigree data sets, and produces Postscript pedigree drawings that are useful for rapid data review.

Proper citation: MADELINE (RRID:SCR_001979) Copy   

•   Source: SciCrunch Registry

http://www.depressiontools.org/

Online instrument that estimates whether a biomarker predicting outcome of depression treatment is likely to be clinically significant.

Proper citation: DepressionTools.org Clinical Significance Calculator (RRID:SCR_003873) Copy   

•   Source: SciCrunch Registry

http://analysis2.bio-x.cn/myAnalysis.php

A powerful web-based platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci.

Proper citation: SHEsis: Analysis Tools For Random Samples (RRID:SCR_002958) Copy   

•   Source: SciCrunch Registry

http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

•   Source: SciCrunch Registry

https://www.facebase.org/node/252

THIS RESOURCE IS NO LONGER IN SERVICE,documented on January,18, 2022. FaceBase Biorepository is now collecting biological samples from people with cleft lip/palate and their family members. Information for Prospective Cases: Clefts of the lip and/or palate can be caused by a wide range of genetic, environmental and other factors. The FaceBase Biorepository will serve as a common source of both biological samples and information that can be made available to investigators trying to determine the underlying cause of these common birth defects. Genetic studies, in particular, will benefit from both family history information and having samples from affected individuals as well as their family members. DNA is the information containing molecules found in all the cells of our body and can be easily obtained from material such as blood or saliva samples. As part of the FaceBase Biorepository, we are requesting families to submit biological samples from specific family members as well as information from other family members that might be affected with either the same condition or a similar condition. The medical and family history information that is collected includes other relevant information such as exposure to possible environmental causes during pregnancy. The biorepository is managed by Nichole Nidey, a research study coordinator, and Jeff Murray, a pediatric clinical geneticist and researcher. They are available to speak with family members regarding questions they may have, including providing information about the biorepository and making arrangements for the collection of samples for those who wish to participate. All participation is voluntary. Your name or other personally identifiable information (name, address, etc) will be removed before information is placed in the biorepository. Summary data to show how the database itself has been used overall as well as updates on whether specific findings might have been made using this database will be available on the FaceBase website at www.facebase.org. A newsletter containing this information will also be given to families and referring clinicians so that they may discuss the specifics with the families if there appears to be information that might be relevant in a particular case. Families will also need to sign a consent form that has been approved by the Institutional Review Board at the University of Iowa. Also, any submitted samples or data can also be removed from the database at any time should the family no longer wish to participate. Investigators interested in requesting DNA samples or for more information, please contact cleftresearch (at) uiowa.edu, Nichole Nidey, nichole-nidey (at) uiowa.edu or (319) 353-4365, or Jeff Murray, jeff-murray (at) uiowa.edu.

Proper citation: FaceBase Biorepository (RRID:SCR_006001) Copy   

•   Source: SciCrunch Registry

http://www.oncotrack.eu/

An international consortium to develop and assess novel approaches to identify and characterize biological markers for colon cancer that will deepen the understanding of the variable make-up of tumors and how this affects the way patients respond to treatment. They will use cutting edge laboratory-based genome sequencing techniques coupled to novel computer modelling approaches to study both the biological heterogeneity of colon cancers (i.e. patient to patient variability) as well as tumor variation within the patient for example, by comparing primary tumors with metastases. This five year project brings together top scientists from European academic institutions offering a wide range of expertise, and partners them with pharmaceutical companies. The project is based on the premise that this genetic and epigenetic information, combined with a description of the molecular pathology of the tumor, will allow OncoTrack to generate a more accurate in-silico model of the cancer cell. This will facilitate the identification of predictive markers that can be used to guide the optimal therapy strategy at the level of the individual patient - and will also provide on-going prognostic guidance for the clinician. This project will not only advance understanding of the fundamental biology of colon cancers but will provide the means and approach for the identification of previously undetected biomarkers not only in the cancer under study, but potentially also in other solid cancers and, in doing so, open the door for personalized management of the oncology patient.

Proper citation: OncoTrack (RRID:SCR_003767) Copy   

•   Source: SciCrunch Registry

http://www.europeanlung.org/en/projects-and-research/projects/airprom/

Consortium focused on developing computer and physical models of the airway system for patients with asthma and chronic obstructive pulmonary disease (COPD). Developing accurate models will better predict how asthma and COPD develop, since current methods can only assess the severity of disease. They aim to bridge the gaps in clinical management of airways-based disease by providing reliable models that predict disease progression and the response to treatment for each person with asthma or COPD. A data management platform provides a secure and sustainable infrastructure that semantically integrates the clinical, physiological, genetic, and experimental data produced with existing biomedical knowledge from allied consortia and public databases. This resource will be available for analysis and modeling, and will facilitate sharing, collaboration and publication within AirPROM and with the broader community. Currently the AirPROM knowledge portal is only accessible by AirPROM partners.

Proper citation: AirPROM (RRID:SCR_003827) Copy   

•   Source: SciCrunch Registry

http://www.themmrf.org/research-programs/commpass-study/

A personalized medicine initiative to discover biomarkers that can better define the biological basis of multiple myeloma to help stratify patients. This effort hopes to obtain samples from approximately 1,000 multiple myeloma patients and follow them over time to identify how a patient's genetic profile is related to clinical progression and treatment response. As a partnership between 17 academic centers, 5 pharmaceuticals and the Department of Veterans Affairs, the goal of this eight year study is to create a database that can accelerate future clinical trials and personalized treatment strategies. MMRF's CoMMpass Study has the following goals: * Create a guide to which treatments work best for specific patient subgroups. * Share data with researchers to accelerate drug development for specific subtypes of multiple myeloma patients. In order to facilitate discoveries and development related to targeted therapies, the comprehensive data from CoMMpass is placed in an open-access research portal. The data will be part of the Multiple Myeloma Research Foundation's (MMRF) Personalized Medicine Platform combines CoMMpass data with those collected from MMRF's Genomics Initiative. It is hoped that the longitudinal data, combined with the annotated bio-specimens will help provide insights that can accelerate personalized therapies.

Proper citation: MMRF CoMMpass Study (RRID:SCR_003721) Copy   

•   Source: SciCrunch Registry

http://www.transformproject.eu/portfolio-item/d6-2-clinical-research-information-model/

A clinical research information model for the integration of clinical research covering randomized clinical trials (RCT), case-control studies and database searches into the TRANSFoRm application development. TRANSFoRm clinical research is based on primary care data, clinical data and genetic data stored in databases and electronic health records and employs the principle of reusing primary care data, adapting data collection by patient reported outcomes (PRO) and eSource based Case Report Forms. CRIM was developed using the TRANSFoRm clinical use cases of GORD and Diabetes. Their use case driven approach consisted of three levels of modelling drawing heavily on the clinical research workflow of the use cases. Different available information models were evaluated for their usefulness to represent TRANSFoRm clinical research, including for example CTOM of caBIG, Primary Care Research Object Model (PRCOM) of ePCRN and BRIDG of CDISC. The PCROM model turned out to be the most suitable and it was possible to extend and modify this model with only 12 new information objects, 3 episode of care related objects and 2 areas to satisfy all requirements of the TRANSFoRm research use cases. Now the information model covers Good Clinical Practice (GCP) compliant research, as well as case control studies and database search studies, including the interaction between patient and GP (family doctor) during patient consultation, appointment, screening, patient recruitment and adverse event reporting.

Proper citation: TRANSFoRm Clinical Research Information Model (RRID:SCR_003889) Copy   

•   Source: SciCrunch Registry

http://betabat.ulb.ac.be/

Project that aims to develop new treatment strategies based on knowledge of cellular dysfunction in diabetes. They will perform a detailed organelle diagnosis based on both focused and systems biology approaches, which will provide the scientific rationale for the design of specific interventions to boost the capacity of beta cells and brown adipocytes to regain homeostatic control. They propose that only by understanding the complex molecular mechanisms triggering cellular dysfunction in diabetes, and by integrating this knowledge at the systems level, will it be possible to develop interventional therapies that protect and restore beta cell and (Brown adipose tissue) BAT function. The ultimate goal is to offer individual therapeutic choices based on both genetic information and organelle diagnosis.

Proper citation: BetaBat (RRID:SCR_003834) 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

https://ihg.helmholtz-muenchen.de/cgi-bin/hw/hwa1.pl

Software tool for performing tests for deviation from Hardy-Weinberg equilibrium and tests for association. Used in population-based genetic association studies to identify susceptibility genes for complex diseases.

Proper citation: Tests for deviation from Hardy-Weinberg equilibrium (RRID:SCR_016496) 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.ncbi.nlm.nih.gov/projects/mutagene/

Software tool to explore and analyze mutagenic factors leading to tumors to decipher cancer genetic heterogeneity.

Proper citation: MutaGene (RRID:SCR_016574) Copy   

•   Source: SciCrunch Registry

http://cerebrovascularportal.org

Portal enables browsing, searching, and analysis of human genetic information linked to cerebrovascular disease and related traits, while protecting the integrity and confidentiality of the underlying data.

Proper citation: Cerebrovascular Disease Knowledge Portal (RRID:SCR_015628) Copy   

•   Source: SciCrunch Registry

http://www.aevol.fr/

Simulation software for experimental evolution of microorganisms. Aevol is a digital genetics model for the study of structural variations of the genome (e.g. number of genes, synteny, proportion of coding sequences).

Proper citation: Aevol (RRID:SCR_015966) Copy   

•   Source: SciCrunch Registry