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Genome-wide association (GWA) constitutes a prominent portion of studies which have been conducted on personalized medicine and pharmacogenomics. Recently, very few methods have been developed for extracting mutation-diseases associations.…

Computation and Language · Computer Science 2020-12-03 Behrouz Bokharaeian , Alberto Diaz

Discovery gene-disease links is important in biology and medicine areas, enabling disease identification and drug repurposing. Machine learning approaches accelerate this process by leveraging biological knowledge represented in ontologies…

Machine Learning · Computer Science 2025-04-14 Catarina Canastra , Cátia Pesquita

The objective of a genome-wide association study (GWAS) is to associate subsequences of individuals' genomes to the observable characteristics called phenotypes (e.g., high blood pressure). Motivated by the GWAS problem, in this paper we…

Information Theory · Computer Science 2020-10-15 Behrooz Tahmasebi , Mohammad Ali Maddah-Ali , Seyed Abolfazl Motahari

Using brain imaging quantitative traits (QTs) to identify the genetic risk factors is an important research topic in imaging genetics. Many efforts have been made via building linear models, e.g. linear regression (LR), to extract the…

In genome-wide association studies (GWAS), hundreds of thousands of genetic markers (SNPs) are tested for association with a trait or phenotype. Reported effects tend to be larger in magnitude than the true effects of these markers, the…

Methodology · Statistics 2010-10-25 Michael E. Goddard , Naomi R. Wray , Klara Verbyla , Peter M. Visscher

Genome-wide association studies (GWAS) involving increasing sample sizes have identified hundreds of genetic variants associated with complex diseases, such as type 2 diabetes (T2D); however, it is unclear how GWAS hits form unique…

Molecular Networks · Quantitative Biology 2023-09-20 Euijun Song

Where causal SNPs (single nucleotide polymorphisms) tend to accumulate within biological pathways, the incorporation of prior pathways information into a statistical model is expected to increase the power to detect true associations in a…

Methodology · Statistics 2012-01-30 Matt Silver , Giovanni Montana

Genetic Network Programming (GNP) is an evolutionary algorithm that extends Genetic Programming (GP). It is typically used in agent control problems. In contrast to GP, which employs a tree structure, GNP utilizes a directed graph…

Multiagent Systems · Computer Science 2024-12-17 Ali Kohan , Mohamad Roshanzamir , Roohallah Alizadehsani

A large number of recent genome-wide association studies (GWASs) for complex phenotypes confirm the early conjecture for polygenicity, suggesting the presence of large number of variants with only tiny or moderate effects. However, due to…

Genomics · Quantitative Biology 2018-05-01 Mingwei Dai , Xiang Wan , Hao Peng , Yao Wang , Yue Liu , Jin Liu , Zongben Xu , Can Yang

We consider the problem in precision health of grouping people into subpopulations based on their degree of vulnerability to a risk factor. These subpopulations cannot be discovered with traditional clustering techniques because their…

Machine Learning · Statistics 2018-12-11 Alexander New , Kristin P. Bennett

Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. In this paper, we leverage recent advances in…

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed…

Populations and Evolution · Quantitative Biology 2014-08-19 Jeremy J. Berg , Graham Coop

With advancements in next generation sequencing technology, a massive amount of sequencing data are generated, offering a great opportunity to comprehensively investigate the role of rare variants in the genetic etiology of complex…

Methodology · Statistics 2025-08-18 Changshuai Wei , Ming Li , Zihuai He , Olga Vsevolozhskaya , Daniel J. Schaid , Qing Lu

The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The information accumulated time-by-time and included in the…

Molecular Networks · Quantitative Biology 2021-08-25 Salvatore Miccichè

The standard paradigm for the analysis of genome-wide association studies involves carrying out association tests at both typed and imputed SNPs. These methods will not be optimal for detecting the signal of association at SNPs that are not…

Genome-wide association studies (GWAS) suggests that a complex disease is typically affected by many genetic variants with small or moderate effects. Identification of these risk variants remains to be a very challenging problem.…

Methodology · Statistics 2014-01-21 Dongjun Chung , Can Yang , Cong Li , Joel Gelernter , Hongyu Zhao

An important task of human genetics studies is to accurately predict disease risks in individuals based on genetic markers, which allows for identifying individuals at high disease risks, and facilitating their disease treatment and…

Genomics · Quantitative Biology 2013-08-20 Cong Li , Can Yang , Joel Gelernter , Hongyu Zhao

Although displaying genetic correlations, psychiatric disorders are clinically defined as categorical entities as they each have distinguishing clinical features and may involve different treatments. Identifying differential genetic…

Genomics · Quantitative Biology 2021-05-24 Shitao Rao , Liangying Yin , Yong Xiang , Hon-Cheong So

In this paper we develop a theory describing how the extended Burrows-Wheeler Transform (eBWT) of a collection of DNA fragments tends to cluster together the copies of nucleotides sequenced from a genome G. Our theory accurately predicts…

Data Structures and Algorithms · Computer Science 2018-05-11 Nicola Prezza , Nadia Pisanti , Marinella Sciortino , Giovanna Rosone

Identifying phenotypes plays an important role in furthering our understanding of disease biology through practical applications within healthcare and the life sciences. The challenge of dealing with the complexities and noise within…

Applications · Statistics 2023-04-28 Andre Vauvelle , Hamish Tomlinson , Aaron Sim , Spiros Denaxas
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