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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   

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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   

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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   

•   Source: SciCrunch Registry

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   

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http://www.geuvadis.org/web/geuvadis/home

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 6,2023. A European Medical Sequencing Consortium committed to gaining insights into the human genome and its role in health and medicine by sharing data, experience and expertise in high-throughput sequencing., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GEUVADIS (RRID:SCR_000684) Copy   

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http://www.genet.sickkids.on.ca/cftr/

Collection of mutations in CFTR gene for international cystic fibrosis genetics research community. Provides up to date information about individual mutations in CFTR gene. All known CFTR mutations and sequence variants have been converted to standard nomenclature recommended by Human Genome Variation Society. On line process for submission of new mutations has been added.While they continue to ensure quality of data, they urge international community to give them feedback and suggestions. Clinical information in this database relates only to details of discovery of specific mutations. As part of 2010 upgrade, CFTR1 joined new project called CFTR2 - Clinical and Functional TRanslation of CFTR. Links to CFTR2 for many mutations in CFTR1 will provide up-to-date summaries of genotype-phenotype information from patient registries around the world.

Proper citation: Cystic Fibrosis Mutation Database (RRID:SCR_000685) Copy   

•   Source: SciCrunch Registry

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   

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http://www.scienceexchange.com/facilities/model-system-genomics-duke

Portal to the Duke University Model Systems Genomics facility equipped to perform molecular genetic research in Drosophilia. Equipment includes stereo microscopes for fly pushing and microdissection, a compound microscope and a microscope equipped to view GFP and RFP as well as two inverted microscopes for embryo injections.

Proper citation: Duke Model System Genomics (RRID:SCR_001051) Copy   

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https://www.benaroyaresearch.org/our-research/biorepositories/biorepository-neurologic-disease

BRI investigators study the molecular and genetic mechanisms which underlie some of the most devastating chronic neurological disorders, and conduct clinical trials for new innovative therapies. Neurological studies that are currently studied include Amyotrophic lateral sclerosis (ALS) or Lou Gehrig's Disease, Multiple Sclerosis, and Parkinson's Disease.

Proper citation: Benaroya Research Institute: Neurological Diseases (RRID:SCR_001576) Copy   

•   Source: SciCrunch Registry

https://pmsf.org/

The Phelan-McDermid Syndrome Foundation, established in 2002, is a 501(c)3 nonprofit group that provides support services for those who have family members affected by 22q13 Deletion Syndrome / Phelan-McDermid Syndrome. It also raises money to further awareness of the syndrome through research and sponsoring an international conference every two years that brings together families, researchers and therapists. The Foundation facilitates connections between families through networking, communications and support services. We also build alliances with other rare diseases groups to expand our reach and exposure. The syndrome, which affects families worldwide, is a rare genetic occurrence and is the result of a damaged or missing protein on the 22nd chromosome. Our Foundation works with researchers who are looking into the cause and possible cure for the syndrome. PMSF's grants and fellowships program is intended to encourage research projects that will advance the development of treatments and cures for PMS. Our mission is to bring together everyone affected by 22q13 Deletion Syndrome/Phelan-McDermid Syndrome to help them through the challenges they face every day and to raise awareness in the medical and research communities.

Proper citation: Phelan-McDermid Syndrome Foundation (RRID:SCR_001707) Copy   

•   Source: SciCrunch Registry

http://www.stats.ox.ac.uk/%7Emarchini/software.html

An R package that specifically focuses on statistical and population genetics methods. The motivation behind the package is to produce an easy to use interface to many of the commonly used methods and models used in statistical and population genetics and an alternative interface for some of the methodology produced by our group. (entry from Genetic Analysis Software)

Proper citation: POPGEN (RRID:SCR_007315) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/hapassoc/index.html

Software application using a likelihood approach to inference of haplotype and nongenetic effects and their interactions in generalized linear models of disease penetrance, when haplotype phase is unknown for some subjects. Parameter estimates are obtained by use of an expectation-maximization (EM) algorithm and standard errors are calculated using Louis'' formula. (entry from Genetic Analysis Software)

Proper citation: R/HAPASSOC (RRID:SCR_009365) Copy   

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http://www.cs.cmu.edu/~genome/FAST-MAP.html

Fluorescent allele-calling software toolkit: a computer software for fully automated microsatellite genotyping. (entry from Genetic Analysis Software)

Proper citation: FASTMAP (1) (RRID:SCR_008346) Copy   

•   Source: SciCrunch Registry

http://automl.info/tpot/

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   

•   Source: SciCrunch Registry

http://centreforstrokerecovery.ca/our-research/research-structure/stroke-patient-recovery-research-database-spred

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 28,2025. The Stroke Patient Recovery Research Database (SPReD) initiative creates the infrastructure needed for the collection of a wide range of data related to stroke risk factors and to stroke recovery. It also promotes the analysis and management of large brain and vessel images. A major goal is to create a comprehensive electronic database Stroke Patient Recovery Research Database or SPReD and populate it with patient data, including demographic, biomarker, genetic and proteomic data and imaging data. SPReD will enable us to combine descriptions of our stroke patients from multiple projects that are geographically distributed. We will do this in a uniform fashion in order to enhance our ability to document rates of recovery; to study the effects of vascular risk factors and inflammatory biomarkers; and to use these data to improve their physical and cognitive recovery through innovative intervention programs. This comprehensive database will provide an integrated repository of data with which our researchers will investigate and test original ideas, ultimately leading to knowledge that can be applied clinically to benefit stroke survivors.

Proper citation: Stroke Patient Recovery Research Database (SPReD) (RRID:SCR_005508) Copy   

•   Source: SciCrunch Registry

http://www.semel.ucla.edu/creativity/

The purpose of this center is to study the molecular, cellular, systems and cognitive mechanisms that result in cognitive enhancements and explain unusual levels of performance in gifted individuals, including extraordinary creativity. Additionally, by understating the mechanisms responsible for enhancements in performance we may be better suited to intervene and reverse disease states that result in cognitive deficits. One of the key topics addressed by the Center is the biological basis of cognitive enhancements, a topic that can be studied in human subjects and animal models. In the past much of the focus in the brain sciences has been on the study of brain mechanisms that degrade cognitive performance (for example, on mutations or other lesions that cause cognitive deficits). The Tennenbaum Center for the Biology of Creativity at UCLA enables an interdisciplinary team of leading scientists to advance knowledge about the biological bases of creativity. Starting with a pilot project program, a series of investigations was launched, spanning disciplines from basic molecular biology to cognitive neuroscience. Because the concept of creativity is multifaceted, initial efforts targeted refinement of the component processes necessary to generate novel, useful cognitive products. The identified core cognitive processes: 1.) Novelty Generation the ability to flexibly and adaptively generate products that are unique; 2.) Working Memory and Declarative Memory the ability to maintain, and then use relevant information to guide goal-directed performance, along with the capacity to store and retrieve this information; and 3.) Response Inhibition the ability to suppress habitual plans and substitute alternate actions in line with changing problem-solving demands. To study the basic mechanisms underlying these complex brain functions we use translational strategies. Starting from foundational studies in basic neuroscience, we forged an interdisciplinary strategy that permits the most advanced techniques for genetic manipulation and basic neurobiological research to be applied in close collaboration with human studies that converge on the same core cognitive processes. Our integrated research program aims to reveal the genetic architecture and fundamental brain mechanisms underlying creative cognition. The work holds enormous promise for both enhancing healthy cognitive performance and designing new treatments for diverse cognitive disorders. Sponsors: The Tennenbaum Center for the Biology of Creativity was inspired by the vision and generosity of Michael Tennenbaum.

Proper citation: Tennenbaum Center for the Biology of Creativity (RRID:SCR_000668) Copy   

•   Source: SciCrunch Registry

http://ccb.loni.usc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31, 2022. Center focused on the development of computational biological atlases of different populations, subjects, modalities, and spatio-temporal scales with 3 types of resources: (1) Stand-alone computational software tools (image and volume processing, analysis, visualization, graphical workflow environments). (2) Infrastructure Resources (Databases, computational Grid, services). (3) Web-services (web-accessible resources for processing, validation and exploration of multimodal/multichannel data including clinical data, imaging data, genetics data and phenotypic data). The CCB develops novel mathematical, computational, and engineering approaches to map biological form and function in health and disease. CCB computational tools integrate neuroimaging, genetic, clinical, and other relevant data to enable the detailed exploration of distinct spatial and temporal biological characteristics. Generalizable mathematical approaches are developed and deployed using Grid computing to create practical biological atlases that describe spatiotemporal change in biological systems. The efforts of CCB make possible discovery-oriented science and the accumulation of new biological knowledge. The Center has been divided into cores organized as follows: - Core 1 is focused on mathematical and computational research. Core 2 is involved in the development of tools to be used by Core 3. Core 3 is composed of the driving biological projects; Mapping Genomic Function, Mapping Biological Structure, and Mapping Brain Phenotype. - Cores 4 - 7 provide the infrastructure for joint structure within the Center as well as the development of new approaches and procedures to augment the research and development of Cores 1-3. These cores are: (4)Infrastructure and Resources, (5) Education and Training, (6) Dissemination, and (7) Administration and Management. The main focus of the CCB is on the brain, and specifically on neuroimaging. This area has a long tradition of sophisticated mathematical and computational techniques. Nevertheless, new developments in related areas of mathematics and computational science have emerged in recent years, some from related application areas such as Computer Graphics, Computer Vision, and Image Processing, as well as from Computational Mathematics and the Computational Sciences. We are confident that many of these ideas can be applied beneficially to neuroimaging.

Proper citation: Center for Computational Biology at UCLA (RRID:SCR_000334) Copy   

•   Source: SciCrunch Registry

http://soap.genomics.org.cn/

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   

•   Source: SciCrunch Registry

http://www.zfatlas.psu.edu/

Atlas containing 2- and 3-dimensional, anatomical reference slides of the lifespan of the zebrafish to support research and education worldwide. Hematoxylin and eosin histological slides, at various points in the lifespan of the zebrafish, have been scanned at 40x resolution and are available through a virtual slide viewer. 3D models of the organs are reconstructed from plastic tissue sections of embryo and larvae. The size of the zebrafish, which allows sections to fall conveniently within the dimensions of the common 1 x 3 glass slide, makes it possible for this anatomical atlas to become as high resolution as for any vertebrate. That resolution, together with the integration of histology and organ anatomy, will create unique opportunities for comparisons with both smaller and larger model systems that each have their own strengths in research and educational value. The atlas team is working to allow the site to function as a scaffold for collaborative research and educational activity across disciplines and model organisms. The Zebrafish Atlas was created to answer a community call for a comprehensive, web-based, anatomical and pathological atlas of the zebrafish, which has become one of the most widely used vertebrate animal models globally. The experimental strengths of zebrafish as a model system have made it useful for a wide range of investigations addressing the missions of the NIH and NSF. The Zebrafish Atlas provides reference slides for virtual microscopic viewing of the zebrafish using an Internet browser. Virtual slide technology allows the user to choose their own field of view and magnification, and to consult labeled histological sections of zebrafish. We are planning to include a complete set of embryos, larvae, juveniles, and adults from approximately 25 different ages. Future work will also include a variety of comparisons (e.g. normal vs. mutant, normal vs. diseased, multiple stages of development, zebrafish with other organisms, and different types of cancer)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Zebrafish Atlas (RRID:SCR_006722) Copy   

•   Source: SciCrunch Registry