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We now need more than ever to make genome analysis more intelligent. We need to read, analyze, and interpret our genomes not only quickly, but also accurately and efficiently enough to scale the analysis to population level. There currently…

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-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

A major goal in genomics is to properly capture the complex dynamical behaviors of gene regulatory networks (GRNs). This includes inferring the complex interactions between genes, which can be used for a wide range of genomics analyses,…

Molecular Networks · Quantitative Biology 2023-01-18 Mohammad Alali , Mahdi Imani

Biomedical research increasingly relies on integrating diverse data modalities, including gene expression profiles, medical images, and clinical metadata. While medical images and clinical metadata are routinely collected in clinical…

Artificial Intelligence · Computer Science 2026-01-23 Francesca Pia Panaccione , Carlo Sgaravatti , Pietro Pinoli

Chronic Kidney Disease (CKD) is a major global health issue which is affecting million people around the world and with increasing rate of mortality. Mitigation of progression of CKD and better patient outcomes requires early detection.…

Artificial Intelligence · Computer Science 2025-04-08 Md. Ehsanul Haque , S. M. Jahidul Islam , Jeba Maliha , Md. Shakhauat Hossan Sumon , Rumana Sharmin , Sakib Rokoni

For the vast majority of genome wide association studies (GWAS) published so far, statistical analysis was performed by testing markers individually. In this article we present some elementary statistical considerations which clearly show…

Applications · Statistics 2010-10-04 Florian Frommlet , Felix Ruhaltinger , Piotr Twarog , Malgorzata Bogdan

Heterogeneous molecular entities and their interactions, commonly depicted as a network, are crucial for advancing our systems-level understanding of biology. With recent advancements in high-throughput data generation and a significant…

Quantitative Methods · Quantitative Biology 2026-03-18 Kishan KC , Rui Li , Paribesh Regmi , Anne R. Haake

Biomarker testing is a laboratory test in oncology that is used in the selection of targeted cancer treatments and helping to avoid ineffective treatments. There exist several types of biomarker tests that can be used to detect the presence…

Quantitative Methods · Quantitative Biology 2022-10-05 Marzieh Soltanolkottabi , Hadi A. Khorshidi , Maarten J. IJzerman

The choice of crossover and mutation strategies plays a crucial role in the searchability, convergence efficiency and precision of genetic algorithms. In this paper, a novel improved genetic algorithm is proposed by improving the crossover…

Neural and Evolutionary Computing · Computer Science 2022-10-12 Dingming Yang , Zeyu Yu , Hongqiang Yuan , Yanrong Cui

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

The aim of plant breeding trials is often to identify germplasms that are well adapt to target environments. These germplasms are identified through genomic prediction from the analysis of multi-environmental field trial (MET) using linear…

Quantitative Methods · Quantitative Biology 2018-07-20 Emi Tanaka

Genetic data are frequently categorical and have complex dependence structures that are not always well understood. For this reason, clustering and classification based on genetic data, while highly relevant, are challenging statistical…

Methodology · Statistics 2016-06-13 Gabriela Bettella Cybis , Marcio Valk , Silvia Regina Costa Lopes

For complex diseases, beyond the main effects of genetic (G) and environmental (E) factors, gene-environment (G-E) interactions also play an important role. Many of the existing G-E interaction methods conduct marginal analysis, which may…

Methodology · Statistics 2020-03-06 Qingzhao Zhang , Hao Chai , Shuangge Ma

Modern disease classification often overlooks molecular commonalities hidden beneath divergent clinical presentations. This study introduces a transcriptomics-driven framework for discovering disease relationships by analyzing over 1300…

Genomics · Quantitative Biology 2025-08-08 Ke Chen , Haohan Wang

In genomics, pattern matching against a sequence of nucleotides plays a pivotal role for DNA sequence alignment and comparing genomes. This helps tackling some diseases, such as cancer in humans. The complexity of searching biological…

Quantitative Methods · Quantitative Biology 2017-10-04 Fereshte Mozafari , Hossein Babashah , Somayyeh Koohi , Zahra Kavehvash

Genetic mutations can cause disease by disrupting normal gene function. Identifying the disease-causing mutations from millions of genetic variants within an individual patient is a challenging problem. Computational methods which can…

Machine Learning · Computer Science 2021-06-28 Jun Cheng , Carolin Lawrence , Mathias Niepert

Skin cancer is a highly dangerous type of cancer that requires an accurate diagnosis from experienced physicians. To help physicians diagnose skin cancer more efficiently, a computer-aided diagnosis (CAD) system can be very helpful. In this…

Image and Video Processing · Electrical Eng. & Systems 2024-06-24 Ayush Roy , Sujan Sarkar , Sohom Ghosal , Dmitrii Kaplun , Asya Lyanova , Ram Sarkar

Many common diseases have a complex genetic basis in which large numbers of genetic variations combine with environmental and lifestyle factors to determine risk. However, quantifying such polygenic effects and their relationship to disease…

Background: Heritability is a central measure in genetics quantifying how much of the variability observed in a trait is attributable to genetic differences. Existing methods for estimating heritability are most often based on random-effect…

Applications · Statistics 2022-08-26 The Tien Mai , Paul Turner , Jukka Corander