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Identifying a patient's key problems over time is a common task for providers at the point care, yet a complex and time-consuming activity given current electric health records. To enable a problem-oriented summarizer to identify a…

Applications · Statistics 2020-03-26 Gal Levy-Fix , Jason Zucker , Konstantin Stojanovic , Noémie Elhadad

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

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

We show how field- and information theory can be used to quantify the relationship between genotype and phenotype in cases where phenotype is a continuous variable. Given a sample population of phenotype measurements, from various known…

Quantitative Methods · Quantitative Biology 2022-06-10 Jonathan Wattis , Sian Bray , Panagiota Kyratzi , Cyril Rauch

Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the most part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.).…

Quantitative Methods · Quantitative Biology 2009-05-08 Roberto Amato , Michele Pinelli , Daniel D'Andrea , Gennaro Miele , Mario Nicodemi , Giancarlo Raiconi , Sergio Cocozza

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

The paper presents a systematic review of state-of-the-art approaches to identify patient cohorts using electronic health records. It gives a comprehensive overview of the most commonly de-tected phenotypes and its underlying data sets.…

Machine Learning · Statistics 2017-07-25 Norman Hiob , Stefan Lessmann

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

The identification of disease-gene associations is instrumental in understanding the mechanisms of diseases and developing novel treatments. Besides identifying genes from RNA-Seq datasets, it is often necessary to identify gene clusters…

Genomics · Quantitative Biology 2025-11-14 Jake R. Patock , Rinki Ratnapriya , Arko Barman

Studying phenotype-gene association can uncover mechanism of diseases and develop efficient treatments. In complex disease where multiple phenotypes are available and correlated, analyzing and interpreting associated genes for each…

Methodology · Statistics 2021-12-14 Yujia Li , Yusi Fang , Peng Liu , George C. Tseng

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

Rare diseases affecting 350 million individuals are commonly associated with delay in diagnosis or misdiagnosis. To improve those patients' outcome, rare disease detection is an important task for identifying patients with rare conditions…

Machine Learning · Computer Science 2019-07-03 Kezi Yu , Yunlong Wang , Yong Cai , Cao Xiao , Emily Zhao , Lucas Glass , Jimeng Sun

The vast majority of connections between complex disease and common genetic variants were identified through meta-analysis, a powerful approach that enables large samples sizes while protecting against common artifacts due to population…

High-dimensional phenotypes hold promise for richer findings in association studies, but testing of several phenotype traits aggravates the grand challenge of association studies, that of multiple testing. Several methods have recently been…

Methodology · Statistics 2013-05-14 Pekka Marttinen , Jussi Gillberg , Aki Havulinna , Jukka Corander , Samuel Kaski

The relationship between microscopic observations and macroscopic behavior is a fundamental open question in biophysical systems. Here, we develop a unified approach that---in contrast with existing methods---predicts cell type from…

Genomics · Quantitative Biology 2020-03-31 Thomas P. Wytock , Adilson E. Motter

Statistically resolving the underlying haplotype pair for a genotype measurement is an important intermediate step in gene mapping studies, and has received much attention recently. Consequently, a variety of methods for this problem have…

Machine Learning · Computer Science 2007-10-29 Matti Kääriäinen , Niels Landwehr , Sampsa Lappalainen , Taneli Mielikäinen

The study of human genes and diseases is very rewarding and can lead to improvements in healthcare, disease diagnostics and drug discovery. In this paper, we further our previous study on gene disease relationship specifically with the…

Genomics · Quantitative Biology 2019-01-16 Hisham Al-Mubaid , Sasikanth Potu , M. Shenify

Many common diseases are highly polygenic, modulated by a large number genetic factors with small effects on susceptibility to disease. These small effects are difficult to map reliably in genetic association studies. To address this…

Quantitative Methods · Quantitative Biology 2012-08-23 Peter Carbonetto , Matthew Stephens

We consider a problem of data integration. Consider determining which genes affect a disease. The genes, which we call predictor objects, can be measured in different experiments on the same individual. We address the question of finding…

Machine Learning · Statistics 2016-10-04 Xin Gao , Raymond J. Carroll

The widely used genetic pleiotropic analysis of multiple phenotypes are often designed for examining the relationship between common variants and a few phenotypes. They are not suited for both high dimensional phenotypes and high…

Machine Learning · Statistics 2015-12-04 Panpan Wang , Mohammad Rahman , Li Jin , Momiao Xiong