Del 0 - Methods in Molecular Biology

Epistasis

Methods and Protocols

Häftad, Engelska, 2022

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Chapters provide methods and protocols demonstrating approaches to identify epistasis, genetic epistasis testing, genome-wide epistatic SNP networks, epistasis detection through machine learning, and complex interaction analysis using trigenic synthetic genetic array (t-SGA).

Produktinformation

Utgivningsdatum2022-03-19
Mått178 x 254 x 23 mm
Vikt771 g
FormatHäftad
SpråkEngelska
SerieMethods in Molecular Biology
Antal sidor402
FörlagSpringer-Verlag New York Inc.
ISBN9781071609491

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Mass-based Protein Phylogenetic Approach to Identify Epistasis.- SNPInt-GPU: Tool for epistasis testing with multiple methods and GPU acceleration.- Epistasis-based Feature Selection Algorithm.- W-test for Genetic Epistasis Testing.- The Combined Analysis of Pleiotropy and Epistasis (CAPE).- Two-Stage Testing for Epistasis: Screening and Veri_cation.- Using Collaborative Mixed Models to Account for Imputation Uncertainty in Transcriptome-Wide Association Studies.- Phenotype Prediction under Epistasis.- Simulating Evolution in Asexual Populations with Epistasis.- Protocol for Construction of Genome-Wide Epistatic SNP Networks using WISH-R Package.- Brief survey on Machine Learning in Epistasis.- First-Order Correction of Statistical Significance for Screening Two-Way Epistatic Interactions.- Gene-Environment Interaction: AVariable Selection Perspective.- Using C-JAMP to Investigate Epistasis and Pleiotropy.- Identifying the Significant Change of Gene Expression in Genomic Series Data.- Analyzing High-Order Epistasis from Genotype-phenotype Maps Using ’Epistasis’ Package.- Deep Neural Networks for Epistatic Sequences Analysis.- Protocol for Epistasis Detection with Machine Learning Using GenEpi Package.- A Belief Degree Associated Fuzzy Multifactor Dimensionality Reduction Framework for Epistasis Detection.- Epistasis Detection Based on Epi-GTBN.- Epistasis Analysis: Classification through Machine Learning Methods.- Genetic Interaction Network Interpretation: A Tidy Data Science Perspective.- Trigenic Synthetic Genetic Array (τ-SGA) Technique for Complex Interaction Analysis.