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Neural networks achieve the state-of-the-art in image classification tasks. However, they can encode spurious variations or biases that may be present in the training data. For example, training an age predictor on a dataset that is not…

Computer Vision and Pattern Recognition · Computer Science 2018-09-28 Mohsan Alvi , Andrew Zisserman , Christoffer Nellaker

We investigate two approaches to increase the efficiency of phenotypic prediction from genome-wide markers, which is a key step for genomic selection (GS) in plant and animal breeding. The first approach is feature selection based on Markov…

Methodology · Statistics 2013-09-09 Marco Scutari , Ian Mackay , David J. Balding

Genome sequencing technology has improved significantly in few last years and resulted in abundance genetic data. Artificial intelligence has been employed to analyze genetic data in response to its sheer size and variability. Gene…

Genomics · Quantitative Biology 2023-03-17 Muhammad Anwari Leksono , Ayu Purwarianti

We propose a resampling-based fast variable selection technique for detecting relevant single nucleotide polymorphisms (SNP) in a multi-marker mixed effect model. Due to computational complexity, current practice primarily involves testing…

Applications · Statistics 2025-04-30 Subhabrata Majumdar , Saonli Basu , Matt McGue , Snigdhansu Chatterjee

When a beneficial mutation occurs in a population, the new, favored allele may spread to the entire population. This process is known as a selective sweep. Suppose we sample $n$ individuals at the end of a selective sweep. If we focus on a…

Probability · Mathematics 2007-05-23 Jason Schweinsberg , Rick Durrett

Non protein coding regions of the human genome contain many complex patterns which regulate the cellular activity. Studying the human genome is limited by the lack of understanding of its features and their complex interactions. However,…

Genomics · Quantitative Biology 2017-08-15 Kerim Arioglu , Umut Eser

Recent advancements in deep learning have been primarily driven by the use of large models trained on increasingly vast datasets. While neural scaling laws have emerged to predict network performance given a specific level of computational…

Computer Vision and Pattern Recognition · Computer Science 2023-11-13 Elior Benarous , Sotiris Anagnostidis , Luca Biggio , Thomas Hofmann

Variable selection has played a critical role in modern statistical learning and scientific discoveries. Numerous regularization and Bayesian variable selection methods have been developed in the past two decades for variable selection, but…

Methodology · Statistics 2024-03-04 Travis Canida , Hongjie Ke , Shuo Chen , Zhenayo Ye , Tianzhou Ma

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

Thousands of candidate human-specific regulatory sequences (HSRS) have been identified, supporting the hypothesis that unique to human phenotypes result from human-specific alterations of genomic regulatory networks. Here, conservation…

Genomics · Quantitative Biology 2025-12-30 Gennadi Glinsky

A selective sweep describes the reduction of diversity due to strong positive selection. If the mutation rate to a selectively beneficial allele is sufficiently high, Pennings and Hermisson (2006a) have shown, that it becomes likely, that a…

Populations and Evolution · Quantitative Biology 2010-09-17 Cornelia Borck

We construct genomic predictors for heritable and extremely complex human quantitative traits (height, heel bone density, and educational attainment) using modern methods in high dimensional statistics (i.e., machine learning). Replication…

Genomics · Quantitative Biology 2017-09-20 Louis Lello , Steven G. Avery , Laurent Tellier , Ana Vazquez , Gustavo de los Campos , Stephen D. H. Hsu

Species-sampling problems (SSPs) refer to a vast class of statistical problems calling for the estimation of (discrete) functionals of the unknown species composition of an unobservable population. A common feature of SSPs is their…

Methodology · Statistics 2024-02-13 Cecilia Balocchi , Federico Camerlenghi , Stefano Favaro

A common problem in bioinformatics is related to identifying gene regulatory regions marked by relatively high frequencies of motifs, or deoxyribonucleic acid sequences that often code for transcription and enhancer proteins. Predicting…

Genomics · Quantitative Biology 2021-01-22 Ethan Jacob Moyer , Anup Das

Coreset selection methods have shown promise in reducing the training data size while maintaining model performance for data-efficient machine learning. However, as many datasets suffer from biases that cause models to learn spurious…

Machine Learning · Computer Science 2025-10-22 Amaya Dharmasiri , William Yang , Polina Kirichenko , Lydia Liu , Olga Russakovsky

The standard paradigm for the analysis of genome-wide association studies involves carrying out association tests at both typed and imputed SNPs. These methods will not be optimal for detecting the signal of association at SNPs that are not…

We identify a set of 575 human genes that are expressed in all conditions tested in a publicly available database of microarray results. Based on this common occurrence, the set is expected to be rich in "housekeeping" genes, showing…

Genomics · Quantitative Biology 2007-05-23 Eli Eisenberg , Erez Y. Levanon

We apply genetic programming techniques to the `shepherding' problem, in which a group of one type of animal (sheep dogs) attempts to control the movements of a second group of animals (sheep) obeying flocking behavior. Our genetic…

Artificial Intelligence · Computer Science 2016-03-22 Joshua Brulé , Kevin Engel , Nick Fung , Isaac Julien

The first step toward Seed Phenotyping i.e. the comprehensive assessment of complex seed traits such as growth, development, tolerance, resistance, ecology, yield, and the measurement of pa-rameters that form more complex traits is the…

Computer Vision and Pattern Recognition · Computer Science 2021-03-30 Venkat Margapuri , Mitchell Neilsen

Cattle lameness is a prevalent health problem in livestock farming, often resulting from hoof injuries or infections, and severely impacts animal welfare and productivity. Early and accurate detection is critical for minimizing economic…

Computer Vision and Pattern Recognition · Computer Science 2025-09-19 Md Fahimuzzman Sohan , Raid Alzubi , Hadeel Alzoubi , Eid Albalawi , A. H. Abdul Hafez