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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

The wealth of computerised medical information becoming readily available presents the opportunity to examine patterns of illnesses, therapies and responses. These patterns may be able to predict illnesses that a patient is likely to…

Machine Learning · Computer Science 2013-07-05 Jenna Reps , Jonathan M. Garibaldi , Uwe Aickelin , Daniele Soria , Jack E. Gibson , Richard B. Hubbard

In rare disease physician targeting, a major challenge is how to identify physicians who are treating diagnosed or underdiagnosed rare diseases patients. Rare diseases have extremely low incidence rate. For a specified rare disease, only a…

Machine Learning · Statistics 2017-01-23 Yong Cai , Yunlong Wang , Dong Dai

Methods to effectively detect multi-locus genetic association are becoming increasingly relevant in the genetic dissection of complex trait in humans. Current approaches typically consider a limited number of hypotheses, most of which are…

Genomics · Quantitative Biology 2007-05-23 Zhong Li , Aris Floratos , David Wang , Andrea Califano

In this contribution, we discuss the basic concepts of genotypes and phenotypes in tree-based GP (TGP), and then analyze their behavior using five benchmark datasets. We show that TGP exhibits the same behavior that we can observe in other…

Neural and Evolutionary Computing · Computer Science 2024-02-14 Wolfgang Banzhaf , Illya Bakurov

1) Micro-evolutionary predictions are complicated by ecological feedbacks like density dependence, while ecological predictions can be complicated by evolutionary change. A widely used approach in micro-evolution, quantitative genetics,…

Populations and Evolution · Quantitative Biology 2015-09-07 Tim Coulson , Floriane Plard , Susanne Schindler , Arpat Ozgul , Jean-Michel Gaillard

We propose a categorical matrix factorization method to infer latent diseases from electronic health records (EHR) data in an unsupervised manner. A latent disease is defined as an unknown biological aberration that causes a set of common…

Applications · Statistics 2019-02-15 Yang Ni , Peter Mueller , Yuan Ji

Life science is entering a new era of petabyte-level sequencing data. Converting such big data to biological insights represents a huge challenge for computational analysis. To this end, we developed DeepMetabolism, a biology-guided deep…

Genomics · Quantitative Biology 2017-05-10 Weihua Guo , You Xu , Xueyang Feng

Identifying measurable genetic indicators (or biomarkers) of a specific condition of a biological system is a key element of precision medicine. Indeed it allows to tailor diagnostic, prognostic and treatment choice to individual…

Machine Learning · Statistics 2016-12-16 Chloé-Agathe Azencott

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

We consider cross-sectional genetic association studies (common and rare variants) where non-genetic information is available, or feasible to obtain for $N$ individuals, but where it is infeasible to genotype all $N$ individuals. We…

Applications · Statistics 2020-02-06 Thea Bjørnland , Anja Bye , Einar Ryeng , Ulrik Wisløff , Mette Langaas

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

Diseases involve complex processes and modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, biological knowledge pertaining to a disease can…

Quantitative Methods · Quantitative Biology 2020-04-13 Thomas Gaudelet , Noel Malod-Dognin , Jon Sanchez-Valle , Vera Pancaldi , Alfonso Valencia , Natasa Przulj

Retrieving gene functional networks from knowledge databases presents a challenge due to the mismatch between disease networks and subtype-specific variations. Current solutions, including statistical and deep learning methods, often fail…

Machine Learning · Computer Science 2025-02-25 Ziwei Yang , Zheng Chen , Xin Liu , Rikuto Kotoge , Peng Chen , Yasuko Matsubara , Yasushi Sakurai , Jimeng Sun

Identifying phenotypes plays an important role in furthering our understanding of disease biology through practical applications within healthcare and the life sciences. The challenge of dealing with the complexities and noise within…

Applications · Statistics 2023-04-28 Andre Vauvelle , Hamish Tomlinson , Aaron Sim , Spiros Denaxas

The advent of artificial intelligence, especially the progress of deep neural networks, is expected to revolutionize genetic research and offer unprecedented potential to decode the complex relationships between genetic variants and disease…

Quantitative Methods · Quantitative Biology 2023-12-13 Tingting Hou , Chang Jiang , Qing Lu

The advent of plant phenomics, coupled with the wealth of genotypic data generated by next-generation sequencing technologies, provides exciting new resources for investigations into and improvement of complex traits. However, these new…

Genomics · Quantitative Biology 2019-04-30 Gota Morota , Diego Jarquin , Malachy T. Campbell , Hiroyoshi Iwata

We seek to identify genes involved in Parkinson's Disease (PD) by combining information across different experiment types. Each experiment, taken individually, may contain too little information to distinguish some important genes from…

In the field of health-care and bio-medical research, understanding the relationship between the symptoms of diseases is crucial for early diagnosis and determining hidden relationships between diseases. The study aimed to understand the…

Artificial Intelligence · Computer Science 2023-02-24 Zolzaya Dashdorj , Stanislav Grigorev , Munguntsatsral Dovdondash

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