Curator Dashboard

Software application that constructs feasible haplotype configurations and the corresponding segregation types on pedigrees. the haplotype configuration minimizes recombinations on the pedigree. (entry from Genetic Analysis Software)

• Resource
• SciCrunch
• 14 years ago - by Anonymous

Software programs for pedigree analysis, including segregation analysis, gene extinction, and pedigree graphics. (entry from Genetic Analysis Software)

• Resource
• SciCrunch
• 14 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software program that performs estimation of power and sample sizes required to detect genetic and environmental main, as well as gene-environment interaction (GxE) effects in indirect matched case-control studies (1:1 matching). When the hypothesis of GxE is tested, power/sample size will be estimated for the detection of GxE, as well as for the detection of genetic and environmental marginal effects. Furthermore, power estimation is implemented for the joint test of genetic marginal and GxE effects (Kraft P et al., 2007). Power and sample size estimations are based on Gauderman''s (2002) asymptotic approach for power and sample size estimations in direct studies of GxE. Hardy-Weinberg equilibrium and independence of genotypes and environmental exposures in the population are assumed. The estimates are based on genotypic codes (G=1 (G=0) for individuals who carry a (non-) risk genotype), which depend on the mode of inheritance (dominant, recessive, or multiplicative). A conditional logistic regression approach is used, which employs a likelihood-ratio test with respect to a biallelic candidate SNP, a binary environmental factor (E=1 (E=0) in (un)exposed individuals), and the interaction between these components. (entry from Genetic Analysis Software)

• Resource
• SciCrunch
• 14 years ago - by Anonymous

Software application designed to simulate a wide range of genetic architectures and population structures in livestock. Large scale genotyping data and complex pedigrees can be efficiently simulated. QMSim is a family based simulator, which can also take into account predefined evolutionary features, such as LD, mutation, bottlenecks and expansions. The simulation is basically carried out in two steps: In the first step, a historical population is simulated to establish mutation-drift equilibrium and, in the second step, recent population structures are generated, which can be complex. QMSim allows for a wide range of parameters to be incorporated in the simulation models in order to produce appropriate simulated data. (entry from Genetic Analysis Software)

• Resource
• SciCrunch
• 14 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. SAS software program to estimate genetic effects and heritabilities of quantitative traits in breeding populations consisting of six related generations (entry from Genetic Analysis Software)

• Resource
• SciCrunch
• 14 years ago - by Anonymous

A command-line program for detecting disease associations with rare variants in sequencing studies. The mutation information is aggregated across multiple variant sites of a gene through a weighted linear combination and then related to disease phenotypes through appropriate regression models. The weights can be constant or dependent on allele frequencies and phenotypes. The association testing is based on score-type statistics. The allele-frequency threshold can be fixed or variable. Statistical significance can be assessed by using asymptotic normal approximation or resampling. The current release covers binary and continuous traits with arbitrary covariates under case-control and cross-sectional sampling. (entry from Genetic Analysis Software)

• Resource
• SciCrunch
• 14 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May24,2023. Software program that implements the Mantel statistics as proposed by Beckmann et al. (2005) to test for association between genetic markers and phenotypes in case-control studies using haplotype information. The potential value of haplotypes has attracted widespread interest in the mapping of complex traits. Haplotype sharing methods take into account linkage disequilibrium information between multiple markers, and may have good power to detect predisposing genes. We present a new approach based on Mantel statistics for space time clustering, which we developed in order to improve the power of haplotype sharing analysis for gene mapping in complex disease. The new statistic correlates genetic similarity and phenotypic similarity across pairs of haplotypes for case-only and case-control studies. The genetic similarity is measured as the shared length between haplotypes around a putative disease locus. Alternative measures for the phenotypic similarity were implemented. (entry from Genetic Analysis Software)

• Resource
• SciCrunch
• 14 years ago - by Anonymous

Collection of nine software packages for genetic analysis: BOREL, HARDY, MORGAN (now 2 and 3), Pedpack, InSegT, Loki, MCLEEPS, Pedfiddler, and Eclipse.

• Resource
• SciCrunch
• 14 years ago - by Anonymous

The overall mission of the College of Pharmacy is to advance pharmaceutical care for the people of Ohio and the global community through our teaching, through our research, and through our service. The College will provide high quality education in the pharmaceutical sciences and pharmacy practice to professional, undergraduate, graduate, and postgraduate students through teaching, research, practice, and related service activities including outreach and engagement.

• Organization
• SciCrunch
• 16 years ago - submitted by Andrea Stagg

Human Genome Epidemiology Network, or HuGENet, is a global collaboration of individuals and organizations committed to the assessment of the impact of human genome variation on population health and how genetic information can be used to improve health and prevent disease. Its goals include: establishing an information exchange that promotes global collaboration in developing peer-reviewed information on the relationship between human genomic variation and health and on the quality of genetic tests for screening and prevention; providing training and technical assistance to researchers and practitioners interested in assessing the role of human genomic variation on population health and how such information can be used in practice; developing an updated and accessible knowledge base on the World Wide Web; and promoting the use of this knowledge base by health care providers, researchers, industry, government, and the public for making decisions involving the use of genetic information for disease prevention and health promotion. HuGENet collaborators come from multiple disciplines such as epidemiology, genetics, clinical medicine, policy, public health, education, and biomedical sciences. Currently, there are 4 HuGENet Coordinating Centers for the implementation of HuGENet activities: CDC''s Office of Public Health Genomics, Atlanta, Georgia; HuGENet UK Coordinating Center, Cambridge, UK; University of Ioannina, Greece; University of Ottawa , Ottawa, Canada. HuGENet includes: HuGE e-Journal Club: The HuGE e-Journal Club is an electronic discussion forum where new human genome epidemiologic (HuGE) findings, published in the scientific literature in the CDC''s Office of Public Health Genomics Weekly Update, will be abstracted, summarized, presented, and discussed via a newly created HuGENet listserv. HuGE Reviews: A HuGE Review identifies human genetic variations at one or more loci, and describes what is known about the frequency of these variants in different populations, identifies diseases that these variants are associated with and summarizes the magnitude of risks and associated risk factors, and evaluates associated genetic tests. Reviews point to gaps in existing epidemiologic and clinical knowledge, thus stimulating further research in these areas. HuGE Fact Sheets: HuGE Fact Sheets summarize information about a particular gene, its variants, and associated diseases. HuGE Case Studies: An on-line presentation designed to sharpen your epidemiological skills and enhance your knowledge on genomic variation and human diseases. Its purpose is to train health professionals in the practical application of human genome epidemiology (HuGE), which translates gene discoveries to disease prevention by integrating population-based data on gene-disease relationships and interventions. Students will acquire conceptual and practical tools for critically evaluating the growing scientific literature in specific disease areas. HUGENet Publications: Articles related to the HuGENet movement written by our HuGENet collaborators. HuGE Navigator: An integrated, searchable knowledge base of genetic associations and human genome epidemiology, including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions, and evaluation of genetic tests. HuGE Workshops: HuGENet has sponsored meetings and workshops with national and international partners since 2001. Available are detailed summaries, agendas or the ability to download speaker slides. HuGE Book: Human Genome Epidemiology: A Scientific Foundation for Using Genetic Information to Improve Health and Prevent Disease. (The findings and conclusions in this book are those of the author(s) and do not necessarily represent the views of the funding agency.) HuGENet Collaborators: HuGENet is interested in establishing collaborations with individuals and organizations working on population based research involving genetic information. HuGE Funding: Funding opportunities for specific population-based genetic epidemiology research projects are available. Research initiatives whose aims include assessing the prevalence of human genetic variation, the association between genetic variants and human diseases, the measurement of gene-gene or gene-environment interaction, and the evaluation of genetic tests for screening and prevention are compiled to create a posted listing. Additional information and application details can be found by clicking on the respective links.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

National institute whose mission is to reduce the burden of neurological disease - a burden borne by every age group, by every segment of society, by people all over the world. To accomplish this goal the NINDS supports and conducts basic, translational, and clinical research on the normal and diseased nervous system. The Institute also fosters the training of investigators in the basic and clinical neurosciences, and seeks better understanding, diagnosis, treatment, and prevention of neurological disorders. NINDS: * Conducts, fosters, coordinates, and guides research on the causes, prevention, diagnosis, and treatment of neurological disorders and stroke, and supports basic research in related scientific areas. * Provides grants-in-aid to public and private institutions and individuals in fields related to its areas of interest, including research project, program project, and research center grants. * Operates a program of contracts for the funding of research and research support efforts in selected areas of institute need. * Provides individual and institutional fellowships to increase scientific expertise in neurological fields. * Conducts a diversified program of intramural and collaborative research in its own laboratories, branches, and clinics. * Collects and disseminates research information related to neurological disorders.

• Resource
• SciCrunch
• 15 years ago - submitted by Stephen Larson

The University of Wisconsin - Madison School of Pharmacy is a world-class leader in pharmacy education, research, and service in the pharmaceutical, social, and clinical sciences. We educate future pharmacists and scientists and provide professional development opportunities globally to practicing pharmacists and the pharmaceutical industry. All of our programs are driven by our mission to enhance the quality of life for the people of Wisconsin and the global community through improved health.

• Organization
• SciCrunch
• 17 years ago - submitted by Eddy Kim

Pipeline for small genome assembly using SOLiD sequencing technology.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

The Graduate Program in Neuroscience at the University of Maryland, Baltimore is one of eight programs in the Graduate Program in Life Sciences (GPILS). The Program in Neuroscience offers research and training opportunities with internationally-renowned faculty. Our Neuroscience Graduate Program is an interdisciplinary program of study leading to a Ph.D. degree in Neuroscience. This graduate program in neuroscience offers research training in a wide range of brain sciences and a flexible program of study.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

This tool creates an Atlas image as an average of several DTI images that will be registered. The registration will be done in two steps : - Affine Registration with BRAINSFit - Non Linear Registration with GreedyAtlas A final step will apply the transformations to the original DTI images so that the final average can be computed. The main function writes a python script that will be executed to compute the Atlas. By running DTIAtlasBuilder, you will need to fill in informations in a Graphical User Interface, and then compute the Atlas. You can also run the tool in command line without using the GUI. Using the GUI, you will be able to save or load a dataset file or a parameter file. The tool needs these other tools to work, so be sure to have these installed on your computer: - ImageMath - ResampleDTIlogEuclidean - CropDTI - dtiprocess - BRAINSFit - GreedyAtlas - dtiaverage - DTI-Reg - unu - MriWatcher If you download the package, be sure to have the glut library installed.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

The pursuit of the Department of Physiology & Pharmacology at Wake Forest University School of Medicine is excellence in research and education. Graduate education and training includes quality introductory and advanced courses in physiology, pharmacology and neuroscience, as well as seminars and journal clubs in several major research areas. Laboratory rotations encourage the graduate student to explore various experimental approaches and provide a diverse training experience. The department and Medical Center are frequented by distinguished visitors from other universities who further enrich the stimulating academic environment. Departmental faculty are active in the medical education as well as in residency training programs in Neurology, Psychiatry, Urology, and Surgery.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

General-purpose unsupervised data-analysis tool, most often used for brain imaging data.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A tool for the gene-set (or pathway) analysis of a genome-wide association study result. It accepts a genome-wide list of SNPs and their association P-values. It summarizes the SNP P-values into nearby genes. The gene-by-gene summary results are then further summarized by gene-sets such as Gene Ontology, KEGG pathways, or user-created gene-sets. Various standardization and statistical tests can be performed and the resulting gene-sets that pass a significance level after multiple-testing correction are reported. The tool is written in Java and is available as a standalone version.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software tools for the processing of liver images. These tools consist of a level set based variational approach that incorporates shape priors and appearance models. It uses ITK-SNAP 1.4 as interface. The tools are capable of automatic liver segmentation and semi-automatic injury segmentation.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Database that contains the complete entries of human ARE-containing full-length mRNAs.<BR/> ARED is further clustered into five groups depending on the number of motifs in the ARE stretch. Groups 1-4 contain five, four, three and two pentameric (AUUUA) repeats, respectively, while Group 5 contains only one repeat within the 13-bp pattern. Clustering was performed in such a way that, for example, Group 1 included not only exact five or more continuous ARE pentamers but also those with 10% ambiguity, so that a stretch of NUUUAUUUAUUUAUUUAUUUN would fall in this category. This process was verified by a phylogenic tree relationship using Clustal-W alignment of ARE stretches and their variations. As could be expected, this analysis showed that the lower the number of ARE motifs in a group, the higher the number of sequences that were included, and apparently the more functionally diverse the corresponding ARE-genes.<BR/>

• Resource
• SciCrunch
• 17 years ago - by Anonymous