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Identifying disease genes from human genome is an important and fundamental problem in biomedical research. Despite many publications of machine learning methods applied to discover new disease genes, it still remains a challenge because of…

Quantitative Methods · Quantitative Biology 2017-05-23 Peng Yang

Gene/pathway-based methods are drawing significant attention due to their usefulness in detecting rare and common variants that affect disease susceptibility. The biological mechanism of drug responses indicates that a gene-based analysis…

Applications · Statistics 2014-08-04 Jung-Ying Tzeng , Wenbin Lu , Fang-Chi Hsu

Network-based computational approaches to predict unknown genes associated with certain diseases are of considerable significance for uncovering the molecular basis of human diseases. In this paper, we proposed a kind of new…

Molecular Networks · Quantitative Biology 2018-11-14 Ke Hu , Jing-Bo Hu , Ju Xiang , Hui-Jia Li , Yan Zhang , Shi Chen , Chen-He Yi

The past decade has seen a rapid growth in omics technologies. Genome-wide association studies (GWAS) have uncovered susceptibility variants for a variety of complex traits. However, the functional significance of most discovered variants…

Genomics · Quantitative Biology 2017-02-22 Hon-Cheong So

Discovering disease pathways, which can be defined as sets of proteins associated with a given disease, is an important problem that has the potential to provide clinically actionable insights for disease diagnosis, prognosis, and…

Molecular Networks · Quantitative Biology 2017-12-05 Monica Agrawal , Marinka Zitnik , Jure Leskovec

Modeling disease progression through multiple stages is critical for clinical decision-making for chronic diseases, e.g., cancer, diabetes, chronic kidney diseases, and so on. Existing approaches often model the disease progression as a…

Machine Learning · Computer Science 2025-03-04 Haoyu Yang , Sanjoy Dey , Pablo Meyer

Presented here is a simple method for cross-validated genome-wide association studies (cvGWAS). Focusing on phenotype prediction, the method is able to reveal a significant amount of missing heritability by properly selecting a small number…

Quantitative Methods · Quantitative Biology 2013-08-08 Xia Shen

Understanding how genetic variants influence cellular-level processes is an important step towards understanding how they influence important organismal-level traits, or "phenotypes", including human disease susceptibility. To this end…

Methodology · Statistics 2013-07-30 Heejung Shim , Matthew Stephens

We consider the problem of detecting and estimating the strength of association between a trait of interest and alleles or haplotypes in a small genomic region (e.g. a gene or a gene complex), when no direct information on that region is…

Applications · Statistics 2008-04-11 Rodrigo Labouriau , Poul Sørensen , Helle R. Juul-Madsen

Background: Many genome-wide association studies have detected genomic regions associated with traits, yet understanding the functional causes of association often remains elusive. Utilizing systems approaches and focusing on intermediate…

Genomics · Quantitative Biology 2019-04-30 Azam Yazdani , Akram Yazdani , Sarah H. Elsea , Daniel J. Schaid , Michael R. Kosorok , Gita Dangol , Ahmad Samiei

Motivation: Predicting gene-disease associations (GDAs) is the problem to determine which gene is associated with a disease. GDA prediction can be framed as a ranking problem where genes are ranked for a query disease, based on features…

Quantitative Methods · Quantitative Biology 2026-02-03 Fernando Zhapa-Camacho , Robert Hoehndorf

The analysis of cancer genomic data has long suffered "the curse of dimensionality". Sample sizes for most cancer genomic studies are a few hundreds at most while there are tens of thousands of genomic features studied. Various methods have…

Machine Learning · Statistics 2018-03-14 Li Zeng , Zhaolong Yu , Hongyu Zhao

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

The identification of disease-associated genes has recently gathered much attention for uncovering disease complex mechanisms that could lead to new insights into the treatment of diseases. For exploring disease-susceptible genes, not only…

Computational Engineering, Finance, and Science · Computer Science 2016-04-27 Zahra Razaghi-Moghadam , Razieh Abdollahi , Sama Goliaei , Morteza Ebrahimi

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

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

Understanding the genetic basis of complex traits is a longstanding challenge in the field of genomics. Genome-wide association studies (GWAS) have identified thousands of variant-trait associations, but most of these variants are located…

Molecular Networks · Quantitative Biology 2024-11-01 Marc Subirana-Granés , Jill Hoffman , Haoyu Zhang , Christina Akirtava , Sutanu Nandi , Kevin Fotso , Milton Pividori

In genetic studies of complex diseases, the underlying mode of inheritance is often not known. Thus, the most powerful test or other optimal procedure for one model, e.g. recessive, may be quite inefficient if another model, e.g. dominant,…

Statistics Theory · Mathematics 2007-06-13 Gang Zheng , Boris Freidlin , Joseph L. Gastwirth

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

Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), the signals identified by association analysis may not have specific pathological relevance to diseases so…

Genomics · Quantitative Biology 2019-07-19 Rong Jiao , Xiangning Chen , Eric Boerwinkle , Momiao Xiong