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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

Accurate evaluation of human aesthetic preferences represents a major challenge for creative evolutionary and generative systems research. Prior work has tended to focus on feature measures of the artefact, such as symmetry, complexity and…

Neural and Evolutionary Computing · Computer Science 2020-09-28 Jon McCormack , Andy Lomas

Genomic surveillance of infectious diseases allows monitoring circulating and emerging variants and quantifying their epidemic potential. However, due to the high costs associated with genomic sequencing, only a limited number of samples…

Recent research in neuroimaging has focused on assessing associations between genetic variants that are measured on a genomewide scale and brain imaging phenotypes. A large number of works in the area apply massively univariate analyses on…

Mutational neighbourhoods in genotype-phenotype (GP) maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should, as John Maynard Smith famously pointed out,…

Populations and Evolution · Quantitative Biology 2016-03-08 Sam F. Greenbury , Steffen Schaper , Sebastian E. Ahnert , Ard A. Louis

The vast amount of sequencing data presently available allow the scientific community to explore a range of genetic variables that may drive and progress cancer. A myriad of predictive tools has been proposed, allowing researchers and…

Genomics · Quantitative Biology 2023-03-31 Mona Nourbakhsh , Kristine Degn , Astrid Saksager , Matteo Tiberti , Elena Papaleo

This manuscript delves into the intersection of genomics and phenotypic prediction, focusing on the statistical innovation required to navigate the complexities introduced by noisy covariates and confounders. The primary emphasis is on the…

Methodology · Statistics 2024-11-15 Upama Paul Chowdhury , Ronit Bhattacharjee , Susmita Das , Abhik Ghosh

Gene expression and phenotype association can be affected by potential unmeasured confounders from multiple sources, leading to biased estimates of the associations. Since genetic variants largely explain gene expression variations, they…

Methodology · Statistics 2019-10-23 Jiarui Lu , Hongzhe Li

Recent advances in large language model (LLM) embeddings have enabled powerful representations for biological data, but most applications to date focus on gene-level information. We present one of the first systematic frameworks to generate…

Applications · Statistics 2026-04-01 Hongqian Niu , Jordan Bryan , Jacob Williams , Hufeng Zhou , Haoyu Zhang , Xihao Li , Didong Li

Cells with the same genome can exist in different phenotypes. and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming…

Quantitative Methods · Quantitative Biology 2022-09-28 Jianhua Xing

The association of a given human phenotype to a genetic variant remains a critical challenge for biology. We present a novel system called PhenoLinker capable of associating a score to a phenotype-gene relationship by using heterogeneous…

Physical activity is crucial for human health. With the increasing availability of large-scale mobile health data, strong associations have been found between physical activity and various diseases. However, accurately capturing this…

Methodology · Statistics 2026-01-19 Xiaojing Sun , Bingxin Zhao , Fei Xue

It has been shown that differences in fecundity variance can influence the probability of invasion of a genotype in a population, i.e. a genotype with lower variance in offspring number can be favored in finite populations even if it has a…

Populations and Evolution · Quantitative Biology 2007-05-23 Max Shpak

Understanding gene perturbation effects across diverse cellular contexts is a central challenge in functional genomics, with important implications for therapeutic discovery and precision medicine. Single-cell technologies enable…

Genomics · Quantitative Biology 2025-11-25 Abrar Rahman Abir , Sajib Acharjee Dip , Liqing Zhang

We consider the problem of predicting perturbation effects via causal models. In many applications, it is a priori unknown which mechanisms of a system are modified by an external perturbation, even though the features of the perturbation…

Machine Learning · Computer Science 2025-07-02 Nora Schneider , Lars Lorch , Niki Kilbertus , Bernhard Schölkopf , Andreas Krause

Each human genome is a 3 billion base pair set of encoding instructions. Decoding the genome using deep learning fundamentally differs from most tasks, as we do not know the full structure of the data and therefore cannot design…

Machine Learning · Computer Science 2016-05-24 Laura Deming , Sasha Targ , Nate Sauder , Diogo Almeida , Chun Jimmie Ye

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

Motivation: Despite being often perceived as the main contributors to cell fate and physiology, genes alone cannot predict cellular phenotype. During the process of gene expression, 95% of human genes can code for multiple proteins due to…

Genomics · Quantitative Biology 2018-09-25 Claudio Angione

Since the completion of the human genome sequencing project in 2001, significant progress has been made in areas such as gene regulation editing and protein structure prediction. However, given the vast amount of genomic data, the segments…

Other Quantitative Biology · Quantitative Biology 2025-01-29 Wang Liang
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