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Detailed phenotype information is fundamental to accurate diagnosis and risk estimation of diseases. As a rich source of phenotype information, electronic health records (EHRs) promise to empower diagnostic variant interpretation. However,…

Machine Learning · Computer Science 2023-04-28 Shenghan Zhang , Haoxuan Li , Ruixiang Tang , Sirui Ding , Laila Rasmy , Degui Zhi , Na Zou , Xia Hu

DNA methylation (DNAme) is a critical component of the epigenetic regulatory machinery and aberrations in DNAme patterns occur in many diseases, such as cancer. Mapping and understanding DNAme profiles offers considerable promise for…

In recent times whole-genome gene expression analysis has turned out to be a highly important tool to study the coordinated function of a very large number of genes within their corresponding cellular environment, especially in relation to…

Genomics · Quantitative Biology 2009-09-21 Enrique Hernandez-Lemus

The ongoing explosion of genome sequence data is transforming how we reconstruct and understand the histories of biological systems. Across biological scales, from individual cells to populations and species, trees-based models provide a…

Populations and Evolution · Quantitative Biology 2025-12-08 Yun Deng , Shing H. Zhan , Yulin Zhang , Chao Zhang , Bingjie Chen

Transcriptomic data is a treasure-trove in modern molecular biology, as it offers a comprehensive viewpoint into the intricate nuances of gene expression dynamics underlying biological systems. This genetic information must be utilised to…

Molecular Networks · Quantitative Biology 2023-12-13 Vikram Singh , Vikram Singh

Gene expression-based heterogeneity analysis has been extensively conducted. In recent studies, it has been shown that network-based analysis, which takes a system perspective and accommodates the interconnections among genes, can be more…

Methodology · Statistics 2023-08-09 Rong Li , Qingzhao Zhang , Shuangge Ma

Models obtained by decision tree induction techniques excel in being interpretable.However, they can be prone to overfitting, which results in a low predictive performance. Ensemble techniques are able to achieve a higher accuracy. However,…

Machine Learning · Statistics 2016-11-18 Gilles Vandewiele , Olivier Janssens , Femke Ongenae , Filip De Turck , Sofie Van Hoecke

Clinical trials are critical for drug development but often suffer from expensive and inefficient patient recruitment. In recent years, machine learning models have been proposed for speeding up patient recruitment via automatically…

Machine Learning · Computer Science 2023-07-20 Brandon Theodorou , Cao Xiao , Jimeng Sun

With the wealth of high-throughput sequencing data generated by recent large-scale consortia, predictive gene expression modelling has become an important tool for integrative analysis of transcriptomic and epigenetic data. However,…

Quantitative Methods · Quantitative Biology 2017-02-14 David M. Budden , Edmund J. Crampin

Integration of transcriptomic and metabolomic data improves functional interpretation of disease-related metabolomic phenotypes, and facilitates discovery of putative metabolite biomarkers and gene targets. For this reason, these data are…

Motivation: Histone modifications are among the most important factors that control gene regulation. Computational methods that predict gene expression from histone modification signals are highly desirable for understanding their…

Machine Learning · Computer Science 2016-07-08 Ritambhara Singh , Jack Lanchantin , Gabriel Robins , Yanjun Qi

Foundation models for single-cell RNA sequencing (scRNA-seq) have shown promising capabilities in capturing gene expression patterns. However, current approaches face critical limitations: they ignore biological prior knowledge encoded in…

Machine Learning · Computer Science 2025-03-04 Mufan Qiu , Xinyu Hu , Fengwei Zhan , Sukwon Yun , Jie Peng , Ruichen Zhang , Bhavya Kailkhura , Jiekun Yang , Tianlong Chen

The linking genotype to phenotype is the fundamental aim of modern genetics. We focus on study of links between gene expression data and phenotype data through integrative analysis. We propose three approaches. 1) The inherent complexity of…

Quantitative Methods · Quantitative Biology 2015-06-30 Min Xu

We introduce a multiple testing procedure (TreeBH) which addresses the challenge of controlling error rates at multiple levels of resolution. Conceptually, we frame this problem as the selection of hypotheses which are organized…

Methodology · Statistics 2018-10-25 Marina Bogomolov , Christine B. Peterson , Yoav Benjamini , Chiara Sabatti

It is tempting to believe that we now own the genome. The ability to read and re-write it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles heel exposed by all of the genomic data that has…

One of the outstanding challenges in comparative genomics is to interpret the evolutionary importance of regulatory variation between species. Rigorous molecular evolution-based methods to infer evidence for natural selection from…

Populations and Evolution · Quantitative Biology 2013-10-16 Joshua G. Schraiber , Yulia Mostovoy , Tiffany Y. Hsu , Rachel B. Brem

High-throughput genetic and epigenetic data are often screened for associations with an observed phenotype. For example, one may wish to test hundreds of thousands of genetic variants, or DNA methylation sites, for an association with…

Methodology · Statistics 2017-10-20 Eric F. Lock , David B. Dunson

Gene regulation is an important fundamental biological process. The regulation of gene expression is managed through a variety of methods including epigenetic processes (e.g., DNA methylation). Understanding the role of epigenetic changes…

Molecular Networks · Quantitative Biology 2021-06-01 James Brunner , Jacob Kim , Timothy Downing , Eric Mjolsness , Kord M. Kober

Gene regulation is a complex process involving the role of several genomic elements which work in concert to drive spatio-temporal expression. The experimental characterization of gene regulatory elements is a very complex and…

Genomics · Quantitative Biology 2007-10-11 Arvind Rao , Alfred O. Hero , David J. States , James Douglas Engel

Understanding functional organization of genetic information is a major challenge in modern biology. Following the initial publication of the human genome sequence in 2001, advances in high-throughput measurement technologies and efficient…

Machine Learning · Statistics 2011-03-01 Leo Lahti
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