Genetics

Bridging Ancestry Gaps in Genomic Risk Prediction with Tabular Foundation Models

Motivation: Models deployed for genomic prediction of diseases perform unevenly across populations, limiting clinical utility. Two factors drive this limitation: large imbalances in sample availability across ancestry groups and non-stationarity of genotype-phenotype effect sizes across the ancestry continuum. While tabular foundation models with in-context learning (ICL) have shown strong sample ...

Sensitive Glioma Detection and Recurrence Monitoring Using a Machine Learning Model Based on Circulating Monocytes

Background: Non-invasive diagnosis, reliable recurrence surveillance remain critical unmet needs in gliomas. Glioma induces profound systemic immune alterations despite its anatomical confinement to the central nervous system. Circulating immune cells, particularly monocytes, are key mediators of tumor-host crosstalk and may retain tumor-induced transcriptional imprints. However, their potential c...

Trustworthy ML/AI for Aging Clocks: Preventing Systematic Prediction Bias in Biological Age Estimation

Machine learning (ML)- and artificial intelligence (AI)-based aging clocks are increasingly used to quantify physiological and molecular aging from om...

Assessing and Optimizing Low-Frequency Somatic Mutation Detection: A Multi-Platform High-Throughput Sequencing Perspective

The availability of multiple commercial short-read sequencing platforms necessitates systematic cross-platform performance comparisons, particularly f...

A Foundation Model for the Cancer Genome

Cancer is a disease of the genome, in which somatic mutations and copy-number alterations determine tumour identity, clinical behaviour, and response ...

High-dimensional Characterization of Genome-Environment Fitness Landscapes in Klebsiella pneumoniae

Background Bacterial fitness is shaped by interactions between genome variation and environmental context, yet how these interactions determine its pr...

Explainable machine learning reveals an RBP regulatory logic of exon skipping

RNA binding proteins (RBPs) regulate the life cycle of an mRNA, often through RBP-RNA interactions. This life cycle includes splicing, whereby the int...

Entropy Fusion DNA: Alignment-Free Gene Fusion Detection through Entropy and Mutual Information Descriptors

Gene fusions are clinically relevant genomic alterations and key cancer biomarkers. Their computational detection remains dominated by alignment-based...

Cooperative FOXA1-HNF4A binding emerges from motif spacing and nucleosome architecture

The pioneer factor hypothesis posits that specialized transcription factors access nucleosomal DNA to enable binding of secondary factors, implying a ...

ModCRE-NN: Interpretable Deep Learning Harnesses Structural and Evolutionary Synergy to Predict Transcription Factor Binding Specificity

We present ModCRE-NN, a machine-learning framework and server for predicting transcription-factor (TF) DNA-binding motifs through the integration of s...

Bimodal masked language modeling for bulk RNA-seq and DNA methylation representation learning

Oncologists are increasingly relying on multiple modalities to model the complexity of diseases. Within this landscape, transcriptomic and epigenetic ...

Pansoma, a machine learning tool for identifying somatic variants using pangenome graphs

Somatic variant calling, the identification of mutations in non-germline cells acquired over an individual's lifetime, is critical for studying diseas...

gTranslate: rapid and accurate translation table prediction for prokaryotic genomes

Background: Bioinformatic tools often require the prediction of protein-coding genes to make inferences about prokaryotic genomes. Typically, the gene...

Sequence-Based Prioritization of Promoter Regulatory Variants in Colorectal Cancer Using a DNA Foundation Model

Noncoding regulatory variants contribute to colorectal cancer (CRC) susceptibility, yet their functional interpretation remains difficult.This is main...

Translational bioinformatics and machine learning framework for biomarker discovery, disease prediction, and patient profiling for precision medicine

Precision medicine aims to advance our ability from a "one-size-fits-all" approach to personalized and predictive healthcare across diverse population...

Comparing Pathway-Informed Polygenic Risk Score Strategies: A multi-cohort evaluation of Amyloid-β

Objective: To systematically evaluate pathway-informed polygenic risk score (PRS) strategies and determine which approaches most effectively leverage ...

Association of a polygenic risk score with coronary atherosclerotic burden in clinical CT angiograms

Background: Polygenic risk scores (PRS) for coronary artery disease (CAD) are associated with cardiovascular events, but the relationship between inhe...

Evolutionary transfer learning enables organism-wide inference of mammalian enhancer landscapes

Understanding and modeling how a single human genome concurrently encodes gene regulatory programs for thousands of cell types remains a central chall...

Molecular Characterization of T-Lineage Acute Lymphoblastic Leukemia by an Optimal-Transport Based Multi-Omics Integration Framework

T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive pediatric malignancy characterized by complex heterogeneity across multiple molecular ...

Multi-Algorithm Machine Learning Benchmarking for Pan-Cancer Classification from Tumour-Educated Platelet RNA Sequencing

Tumour-educated platelets (TEPs) carry cancer-type-specific RNA signatures accessible through whole-blood RNA sequencing, but systematic multi-algorit...