variant effect prediction

Determinants of missense pathogenicity in Usherin: Evaluating sequence and predicted-structure features

This paper develops UshEffect-3D, a variant effect predictor for USH2A missense variants using sequence and predicted structure features, reclassifying 37.2% of ClinVar VUS as likely pathogenic.

Predicting the Risk of Avian Influenza Zoonosis using Viral Genome Sequencing Data

This study uses machine learning to predict avian influenza zoonosis risk based on viral genome sequence features, finding that a multi-model approach outperforms individual models.

Spanning-Tree Thermostatistics of Protein Allostery: An Exact Kirchhoff Framework with Application to Oncogenic KRAS

Kirchhoff matrix-tree evaluation of residue-contact spanning-tree ensembles yields exact allosteric thermodynamics; KRAS G12D conserves global and channel heat capacity but reroutes paths via Q61 and F156.

Long-read transcriptome analysis using IsoRanker for identifying pathogenic variants in Mendelian conditions

IsoRanker uses long-read transcriptomics to prioritize non-coding variants in Mendelian conditions by detecting expression outliers, allelic imbalance, and NMD, leading to the identification of pathogenic variants in one individual.

Multiplexed Quantification of Variant Abundance in the Globin Gene Family: Integrating Saturation Mutagenesis with Cross-Paralog Prediction

The paper presents a hybrid experimental and computational framework to quantify variant abundance in globin genes, using saturation mutagenesis and deep learning for cross-paralog prediction.

Predicting Protein-RNA Binding Affinity Changes via Spatial Coupling-Aware State Space Modeling

iSCALE predicts mutation-induced changes in protein-RNA binding affinity using a spatial coupling-aware deep learning model, achieving superior performance on multiple binding affinity tasks.

Human panepigenome represents epigenomic diversity

The paper presents a human panepigenome map of DNA methylation, revealing epigenomic diversity across populations and highlighting the role of genetic variation in CpG presence and absence.

Ancestry-stratified variant classification in monogenic diabetes genes: annotation coverage and differential curation burden

The paper evaluates variant classification disparities in monogenic diabetes genes across ancestry groups using ClinVar and gnomAD, finding significant annotation gaps and curation biases in non-European populations.

Standing genetic variation buffers field populations of Zymoseptoria tritici against seasonal and fungicide selection

The paper analyzes whole-genome sequences from wheat fields to determine how seasonal changes and fungicide use affect genetic variation in Zymoseptoria tritici.

OncoGenRAG: Evidence-Grounded Retrieval and BioBERT Classification for Precision Oncology Variant Interpretation

OncoGenRAG improves variant interpretation in oncology by combining retrieval and classification with a curated knowledge base, achieving high accuracy and reducing hallucinations.

Dynamics-aware Evolutionary Profiling Uncouples Structural Rigidity from Functional Motion to Enable Enhanced Variant Interpretation

This paper introduces Dynamics-Aware Evolutionary Profiling to separate structural rigidity from functional motion in proteins, improving variant interpretation by identifying dynamic-conserved residues.

Mapping pathogenic patterns in membrane transporters from the GLUT transporter family

The paper maps pathogenicity patterns in GLUT transporters by analyzing missense mutations and their structural impact across the family.

No evidence of association between PGK1 variants and Parkinsons disease

This study examines the association between PGK1 variants and Parkinson's disease but finds no evidence of such a link in large cohorts.

Bacterial persistence emerges mainly from antibiotic-specific networks rather than slow growth

This study identifies antibiotic-specific pathways governing bacterial persistence in E. coli, showing persistence is largely independent of growth and depends on distinct physiological mechanisms for different antibiotics.

AlphaVaR: an R framework for the statistical interpretation of AlphaGenome variant-effect predictions

AlphaVaR structures AlphaGenome's per-track variant scores in R and adds multiple-testing-corrected enrichment and shift tests, a tissue-specificity index and transparent ranking; on rs1427407 it recovers BCL11A erythroid-enhancer biology.

Mitigating the Effects of Population Stratification in Gene-Gene Interaction Studies

This study identifies scenarios where population stratification inflates gene-gene interaction test statistics and proposes a method to control false positives by adding a SNP-population structure interaction term to regression models.

Estimating uncertainty in family-based GWAS

This study investigates uncertainty in sibling-based GWAS allelic effect estimates and proposes a resampling-based method that is more accurate than existing approaches.

SVlog: a logic programming framework for understanding structural variation in genomic disease

SVlog provides a logic programming framework for analyzing structural variants in genomic disease by applying deterministic rules to genomic data and annotations.

PG-LLM: Benchmarking General-Purpose Language Models for Protein Variant Ranking

PG-LLM benchmarks language models for protein variant ranking, showing they outperform many sequence-based predictors but fall short of specialized models.

Pathogenic Epilepsy Gene Variant Prevalence and Penetrance Among U.S. Military Veterans in the Million Veteran Program Cohort

The paper examines the prevalence and penetrance of pathogenic variants in epilepsy genes among U.S. military Veterans, finding increased epilepsy risk for carriers of certain variants.

A survey of multi-targeting and off-targeting sgRNAs across five genome-wide CRISPR-Cas9 knockout sgRNA libraries with GuideRefine

The paper develops GuideRefine to identify and remove multi-targeting and off-targeting sgRNAs from CRISPR-KO libraries, improving the accuracy of gene hit lists.

mV2G: a multiomic atlas for tissue-specific variant-to-gene prioritization

A web atlas counts evidence from 24 types for 188,634,118 variant-gene pairs across 50 human tissues; 1,530,420 pairs pass a high-confidence cutoff, 87% of them tissue-specific.

Context-dependent variant interpretation from Mendelian disease to genetic predisposition: a proof-of-concept using LPL

This paper proposes a context-dependent framework for variant interpretation by analyzing LPL loss-of-function variants, showing how residual activity levels influence clinical outcomes.

INDELVAR: structure-informed prediction of in-frame indel pathogenicity with calibrated PP3/BP4 thresholds

INDELVAR predicts pathogenicity of in-frame indels using structural and evolutionary features, achieving high AUROC scores and calibrated thresholds for both deletion and insertion types.

A Semantic + Neuronal Approach to Predict Pathogenic Variants in DNA Sequences

The paper presents a machine learning model that predicts pathogenic DNA variants using a semantic approach combined with CRF and BiLSTM, achieving state-of-the-art performance.

In-silico functional prediction of novel tuberculosis pharmacogenetic variants and NAT2 phenotype prediction in African populations

The paper predicts NAT2 genotypes and phenotypes in African populations using bioinformatic tools and next-generation sequencing data to inform pharmacogenetic treatment strategies for tuberculosis.

Correction of the cytosine deamination artifacts in FFPE-based sequencing experiments

This study evaluates methods to correct cytosine deamination artifacts in FFPE sequencing, finding enzymatic repair is most effective and FFPErase is the best computational method.

EpiBinder: A Multimodal Framework for Cell-Type-Specific Prediction and Interpretation of Transcription Factor Binding

EpiBinder predicts cell-type-specific TF binding by integrating DNA sequence and epigenetic data, improving prediction accuracy and providing interpretability.

Benchmark Averages Hide the Failures That Matter: Quantizing ESM-2 for Protein Variant-Effect Prediction

The paper benchmarks ESM-2 model precision configurations for variant-effect prediction, finding that average performance metrics hide critical failures and that asymmetric activation quantization improves accuracy.

β-lactoglobulin a new whey: Computational redesign improves stability and nutritional composition

The paper uses computational methods to redesign β-lactoglobulin, improving its stability and BCAA content, with experimental validation of the results.