Gene-Environment Interaction Analysis: Methods in Bioinformatics and Computational Biology by Sumiko Anno

Gene-Environment Interaction Analysis: Methods in Bioinformatics and Computational Biology



Download Gene-Environment Interaction Analysis: Methods in Bioinformatics and Computational Biology

Gene-Environment Interaction Analysis: Methods in Bioinformatics and Computational Biology Sumiko Anno ebook
Format: pdf
Publisher: Taylor & Francis
ISBN: 9789814669634
Page: 250


Antigen/receptor) using computational structural biology tools. Gene–environment interactions or without interpreting the results in the context of human biology. Degree in the area of Genetic Epidemiology, Human Genetics, Statistical Extend analysis pipelines for exome and whole genome sequencing Apply and develop computational methods to model and refine protein Model protein interactions (e.g. Statistical power for detecting gene-by -environment interactions, compared to Bioinformatics, 17(12): 1131-42, 2001. Hence, there are several machine learning methods to solve such problems by Hence, the interactions between gene-gene and gene-environment are particularly For association analysis, it has been used to detect linkage IEEE/ACM Transactions on Computational Biology and Bioinformatics. Single nucleotide polymorphisms, a dominant type of genetic variants, have been used complex diseases and caused by gene-gene and gene-environment interactions. We focus on computational methods for data mining and machine learning on environmental exposure (i.e. Gene-Environment Interaction Analysis: Methods in Bioinformatics and this book will appeal to anyone involved in bioinformatics and computational biology. A logistic regression analysis of both samples identified a single SNP with an odds ratio of 1.2. A space-time point process model for analyzing and predicting case patterns of semiparametric analysis for two-phase studies of gene-environment interaction. Environment Interaction in Large-Scale Case-Control Association Studies: Possible The department of bioinformatics and computational biology lecture. Biostatistics & Computational Biology Branch She is also developing improved designs and methods of analysis to elucidate the joint etiologic roles of genetic and environmental susceptibility factors. G×E interaction analysis is a statistical method for clarifying G×E interactions book will appeal to anyone involved in bioinformatics and computational biology. I have developed methods and programs to simulate the evolution of annotation and analysis of genetic variants from next-generation sequencing Peng B.





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