Genetics

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

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Capturing the Mutational Dynamics of SARS-CoV-2 with Graphs

The rapid evolution of SARS-CoV-2 presents significant challenges for modeling viral dynamics, drive...

Machine learning–driven decoding of maternal immune signatures in repeated pregnancy loss

Repeated pregnancy loss (RPL) is a multifactorial condition in which the underlying immunological me...

DLRNA-BERTa: A transformer approach for RNA-drug binding affinity prediction

RNA-based therapies are a rapidly expanding field, offering treatments for a wide range of diseases,...

vcfsim: flexible simulation of all-sites VCFs with missing data

VCFs are the most widely used data format for encoding genetic variation. By design, standard VCFs d...

OmicsFUSION: A Pretrained Hyena-Based Framework for Encoding, Reconstruction, and Representation of the Omics and DNA Data

Recent advances in Natural Language Processing (NLP) have spurred the application of Large Language ...

TransStop, a genomic language model for the pan-drug prediction of translational readthrough efficacy

Premature termination codons (PTCs) are a major cause of genetic diseases, but the efficacy of thera...

Discovery of RdRp Thumb-1 as a novel broad-spectrum antiviral family of targets and MDL-001 as a potent broad-spectrum inhibitor thereof

Multiple positive-sense, single-stranded RNA (+ssRNA) viruses cause human diseases, ranging from mil...

PhyloAug: An Evolutionary and Structure-Aware Data Augmentation Tool *

Genomic Language Models (GLMs) suffer from the inherent problem of data scarcity, due to the cost, t...

Predicting functional constraints across evolutionary timescales with phylogeny-informed genomic language models

Genomic language models (gLMs) have emerged as a powerful approach for learning genome-wide function...

Generative design of synthetic gene circuits for functional and evolutionary properties

In the past decades, a wide suite of design tools for biological systems have been developed, but us...

Leveraging learned representations and multitask learning for lysine methylation site discovery

Lysine methylation is a dynamic and reversible post-translational modification of proteins carried o...

Predicting the unseen: a diffusion-based debiasing framework for transcriptional response prediction at single-cell resolution

Predicting cellular responses to genetic perturbations is critical for advancing our understanding o...

Structured Multimodal Deep Learning improves Genomic Prediction in Future Environments

The development of prediction models for phenotypes as functions of genetics and environmental input...

Non-Invasive Diagnostic Evaluation of Urinary Exosomal Let-7c Cluster Expression in Bladder Cancer Using Machine Learning Approaches

Bladder cancer (BCa) diagnosis typically relies on invasive cystoscopy, which is effective but costl...

DELPHAI, AI Agent for Predicting Drug Response and Resistance

Patient-derived organoids preserve critical tumor features and drug sensitivity patterns that mirror...

Learning the native-like codons with a 5’UTR and RNA secondary structure aided species-informed transformer model

Efficient protein expression across heterologous hosts remains a major challenge in synthetic biolog...

A Benchmark of Evo2 Genomic AI Models for Efficient and Practical Deployment

The rapid advancement of DNA foundation language models has brought about a transformative shift in ...

Illuminating the Virosphere’s Dark Matter using Hierarchical Deep Learning

Systematic discovery of novel viruses is essential for pandemic preparedness, understanding tumor-as...

CNN-based learning of single-cell transcriptomes reveals a blood-detectable multi-cancer signature of brain metastasis

Brain metastasis (BrM) is a serious complication of advanced cancers and remains difficult to predic...

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