Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Gene-Modulated Network Diffusion for Improved Modeling of Amyloid-β Spread in Alzheimer's Disease

Understanding the pathogenesis of amyloid-{beta} pathology in Alzheimer's Disease (AD) proves to be ...

Evaluating Reference-Independent Pipelines for the Detection of Spreading Organisms in Metagenomic Datasets

The emergence of unidentified pathogens, or "Disease X," poses a significant threat to global health...

Tumor cell specific total mRNA expression informed neural networks predicts cancer progression

Inferring tumor molecular phenotypes from high-dimensional multi-omic data is a fundamental challeng...

PEPR-GNN: Perturbation-Enhancer-Promoter-RNA Graph Neural Networks for Multiome Perturb-Seq modeling of regulomes

Cellular reprogramming is a complex interplay between perturbations and regulatory elements, culmina...

A Pilot Evaluation of Open-Weight Large Language Models for Screening RNA-seq Metadata in Public Databases

Although the Gene Expression Omnibus and other public repositories are expanding rapidly, curation a...

EffectorGeneP: accurate gene annotation in pathogen genomes from infection transcriptomes

Accurate gene annotation is crucial for inference of biological knowledge from genomes. However, non...

Comparative single-cell transcriptomic roadmap of mammalian fetal ovarian development

Early ovarian development establishes the cellular basis of female reproduction, yet its cellular co...

Machine learning approaches for the identification and analysis of enterotoxin genes in Staphylococcus aureus genomes

Staphylococcus aureus produces a broad range of enterotoxins that act as superantigens, disrupting h...

Combinatorial epigenomic patterns define regulatory programs underlying disease heterogeneity

Disease is a heterogeneous process that involves multiple organs and cell types. Understanding how g...

Clonal embeddings allow exploratory analysis of lineage-resolved single-cell data

Assays coupling high-throughput lineage tracing with single-cell transcriptomics are transforming st...

Functional Profiling of Thousands of Sequence-Diverse Protease Homologs with GROQ-seq

High-quality datasets that span broad sequence diversity are essential for understanding protein seq...

MolGene-E: Inverse Molecular Design to Modulate Single Cell Transcriptomics

Designing drugs that can restore a diseased cell to its healthy state is an emerging approach in sys...

Linearizing Vision Transformer with Test-Time Training

While linear-complexity attention mechanisms offer a promising alternative to Softmax attention for ...

DoFormer: Causal Transformer for Gene Perturbation

Learning causal gene regulatory mechanisms from single-cell data, and thereby predicting the effects...

Mitigating Family Effects in RNA Secondary-Structure Prediction with Latent-Space Continual Learning

Accurate RNA secondary-structure prediction remains difficult despite decades of thermodynamics-base...

Deep learning cell type classification using nuclear DNA patterns

Multicellular organisms comprise various types of cells, which are characterized by gene expression ...

Species-specific transformer models of bacterial gene order and content for genomic surveillance tasks

Transformer models enable functionally meaningful representation of complex biological data, such as...

Systems Pharmacology Reveals Type I Interferon and Myeloid-Like B Cell Reprogramming as Druggable Axes in Antiphospholipid Syndrome

Antiphospholipid syndrome (APS) lacks targeted therapies beyond anticoagulation, and its molecular h...

Overcoming systematic data biases enables accurate prediction of enzyme kcat fold-changes for computational protein design

Machine learning is increasingly used to guide protein engineering by predicting how mutations affec...

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