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It is widely recognized nowadays that complex diseases are caused by, amongst the others, multiple genetic factors. The recent advent of genome-wide association study (GWA) has triggered a wave of research aimed at discovering genetic…

Applications · Statistics 2011-09-30 Nguyen Xuan Vinh

Much of the natural variation for a complex trait can be explained by variation in DNA sequence levels. As part of sequence variation, gene-gene interaction has been ubiquitously observed in nature, where its role in shaping the development…

Applications · Statistics 2012-10-01 Shaoyu Li , Yuehua Cui

For complex diseases, the interactions between genetic and environmental risk factors can have important implications beyond the main effects. Many of the existing interaction analyses conduct marginal analysis and cannot accommodate the…

Methodology · Statistics 2016-05-31 Yangguang Zang , Yinjun Zhao , Qingzhao Zhang , Hao Chai , Sanguo Zhang , Shuangge Ma

Cognizance of gene-environment interactions may help prevent or detain the onset of complex diseases like cardiovascular disease, cancer, type2 diabetes, autism or asthma by adjustments to lifestyle. In this regard, we extend the Bayesian…

Applications · Statistics 2017-07-25 Durba Bhattacharya , Sourabh Bhattacharya

Gene-gene and gene-environment interactions are widely believed to play significant roles in explaining the variability of complex traits. While substantial research exists in this area, a comprehensive statistical framework that addresses…

Methodology · Statistics 2026-02-18 Durba Bhattacharya , Sourabh Bhattacharya

Identifying genes associated with complex human diseases is one of the main challenges of human genetics and computational medicine. To answer this question, millions of genetic variants get screened to identify a few of importance. To…

Genomics · Quantitative Biology 2015-09-01 Aziz M. Mezlini , Fabio Fuligni , Adam Shlien , Anna Goldenberg

Genome-wide association studies, in which as many as a million single nucleotide polymorphisms (SNP) are measured on several thousand samples, are quickly becoming a common type of study for identifying genetic factors associated with many…

Methodology · Statistics 2010-10-25 Charles Kooperberg , Michael LeBlanc , James Y. Dai , Indika Rajapakse

Gene-environment interactions have important implications to elucidate the genetic basis of complex diseases beyond the joint function of multiple genetic factors and their interactions (or epistasis). In the past, G$\times$E interactions…

Applications · Statistics 2020-03-09 Fei Zhou , Jie Ren , Xi Lu , Shuangge Ma , Cen Wu

Nature (one's genes) and nurture (one's environment) jointly contribute to the formation and evolution of health and human capital over the life cycle. This complex interplay between genes and environment can be estimated and quantified…

A system level view of cellular processes for human and several organisms can be cap- tured by analyzing molecular interaction networks. A molecular interaction network formed of differentially expressed genes and their interactions helps…

Molecular Networks · Quantitative Biology 2016-11-09 Jeethu V. Devasia , Priya Chandran

Most disorders are caused by a combination of multiple genetic and/or environmental factors. If two diseases are caused by the same molecular mechanism, they tend to co-occur in patients. Here we provide a quantitative method to disentangle…

Molecular Networks · Quantitative Biology 2016-06-01 Peter Klimek , Silke Aichberger , Stefan Thurner

A biological pathway represents a set of genes that serves a particular cellular or a physiological function. The genes within the same pathway are expected to function together and hence may interact with each other. It is also known that…

Methodology · Statistics 2012-06-14 Zaili Fang , Inyoung Kim , Jeesun Jung

The majority of common diseases are influenced by multiple genetic and environmental factors such as Cancer. Even though uncovering the main causes of disease is deemed difficult due to the complexity of gene-gene and gene-environment…

Other Computer Science · Computer Science 2017-05-10 Layan Nahlawi

Many diseases and traits involve a complex interplay between genes and environment, generating significant interest in studying gene-environment interaction through observational data. However, for lifestyle and environmental risk factors,…

Methodology · Statistics 2023-09-22 Malka Gorfine , Conghui Qu , Ulrike Peters , Li Hsu

One component of precision medicine is to construct prediction models with their predictive ability as high as possible, e.g. to enable individual risk prediction. In genetic epidemiology, complex diseases have a polygenic basis and a…

Machine Learning · Statistics 2019-01-28 Damian Gola , Inke R. König

Gene-gene interactions are often regarded as playing significant roles in influencing variabilities of complex traits. Although much research has been devoted to this area, to date a comprehensive statistical model that addresses the…

Applications · Statistics 2018-04-18 Durba Bhattacharya , Sourabh Bhattacharya

Substantial progress has been made in identifying single genetic variants predisposing to common complex diseases. Nonetheless, the genetic etiology of human diseases remains largely unknown. Human complex diseases are likely influenced by…

Methodology · Statistics 2014-05-27 Zihuai He , Min Zhang , Xiaowei Zhan , Qing Lu

Variations in complex traits are influenced by multiple genetic variants, environmental risk factors, and their interactions. Though substantial progress has been made in identifying single genetic variants associated with complex traits,…

Genomics · Quantitative Biology 2025-08-22 Ming Li , Ruo-Sin Peng , Changshuai Wei , Qing Lu

It is becoming increasingly clear that complex interactions among genes and environmental factors play crucial roles in triggering complex diseases. Thus, understanding such interactions is vital, which is possible only through statistical…

Applications · Statistics 2020-05-04 Durba Bhattacharya , Sourabh Bhattacharya

Polygenic risk scores (PRSs) can significantly enhance breast cancer risk prediction when combined with clinical risk factor data. While many studies have explored the value-add of PRSs, little is known about the potential impact of…

Genomics · Quantitative Biology 2024-07-31 Monica Isgut , Andrew Hornback , Yunan Luo , Asma Khimani , Neha Jain , May D. Wang
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