Genetics

OligoGraph: A novel geometric graph-based approach for siRNA efficacy prediction

RNA interference (RNAi) is a biological process in which a small interfering RNA (siRNA) prevents the translation of a messenger RNA (mRNA) into a protein by cleaving the mRNA before translation. We exploit this process to prevent the formation of harmful proteins by using an effective siRNA on the target mRNA. The current rapidly emerging RNAi-based drugs show immense potential for therapeutic ap...

BOTANIC-0: a series of foundation models for plant genomic data

Genomic language models (gLMs) have emerged as a powerful paradigm for learning regulatory biology directly from DNA sequence. Here, we introduce Botanic0, a family of plant genomic foundation models spanning 100M to 1B parameters and pretrained on 43 phylogenetically diverse plant genomes. The Botanic0-S, Botanic0-M, and Botanic0-L models form the first generation of a long-term research initiati...

EnhancerDetector: Enhancer Discovery from Human to Fly via Interpretable Deep Learning

Deciphering how enhancers encode regulatory information in DNA remains a central genomics challenge, as sequencing outpaces functional annotation. A k...

Genomic Evolution of SARS-CoV-2 Delta Variants Pre- and Post-Omicron Emergence using Alignment-free Machine Learning models

The SARS-CoV-2 Delta variant (B.1.617.2), initially classified as a variant of concern due to its enhanced transmissibility and vaccine-escape mutatio...

Inference of cancer driver mutations from tumor microenvironmentcomposition: a pan-cancer study with cross-platform external validation

Cancer driver mutations shape the tumor microenvironment (TME), yet whether TME composition alone can predict genotype has not been systematically eva...

An snRNA-seq aging clock for the fruit fly head sheds light on sex-biased aging

Although multiple high-performing epigenetic aging clocks exist, few are based directly on gene expression. Such transcriptomic aging clocks allow us ...

SHAP-Guided CpG Selection with Ensemble Learning for Epigenetic Age Prediction

Abstract Epigenetic biomarkers offer critical insight into biological aging and disease risk, yet most deep learning models lack interpretability and ...

Learning lifetime disease liability reveals and removes genetic confounding in electronic health records

Electronic health records (EHRs) have become the cornerstone of population-scale genetic studies1, but factors including patterns of healthcare use sh...

Survival risk heterogeneity among patients with NSCLC receiving nivolumab visualized by risk scores generated from deep learning method DeepSurv using tumor gene mutations

Immunotherapy with immune checkpoint inhibitors and immunotherapy combined with chemotherapy have represented promising treatments for NSCLC patients ...

Reconstructing multi-scale tissue spatial architecture from single-cell RNA-seq with REMAP

Understanding spatial organization of cells is critical for deciphering tissue function and disease. Single-cell RNA-sequencing (scRNA-seq) profiles t...

Bacterial protein function prediction via multimodal deep learning

Bacterial proteins are specialized with extensive functional diversity for survival in diverse and stressful environments. A significant portion of th...

Genomic-island cassette architecture drives pathogenic Enterococcus cecorum lineages: Cassette2Vec-EC, a structural genomics and machine-learning framework

Mobile genetic elements and genomic islands (GIs) frequently encode antibiotic resistance and host-adaptation cargo, yet routine genome comparison pip...

Accelerated sampling of protein dynamics using BioEmu augmented molecular simulation

We introduce a workflow that integrates BioEmu-generated conformational ensemble with physics-based molecular simulations and Markov State Models to s...

Mechanistic machine learning enables interpretable and generalizable prediction of prime editing outcomes

Although prime editing (PE) can effect virtually any specified local change to genomic DNA in living systems, its efficient application currently requ...

Rational design of synthetic proteins using a genome-scale CRISPR screen

Protein structure prediction using deep learning has revolutionized protein design. Yet, our understanding of protein function remains a key limitatio...

Geometric-aware and interpretable deep learning for single-cell batch correction via explicit disentanglement and optimal transport

Single-cell RNA sequencing enables high-resolution characterization of cellular heterogeneity, yet integrating datasets from diverse sources remains c...

GeneZip: Region-Aware Compression for Long Context DNA Modeling

Genomic sequences span billions of base pairs (bp), posing a fundamental challenge for genome-scale foundation models. Existing approaches largely sid...

AgriVariant: Variant Effect Prediction using DeepChem-Variant for Precision Breeding in Rice

Predicting functional consequences of genetic variants in crop genes remains a critical bottleneck for precision breeding programs. We present AgriVar...

Intragenic methylation repatterning is associated with alternative splicing and unique epigenetic phenotypes

The role of intragenic cytosine methylation in shaping phenotypes has been contentious. Recent studies show association between stress and alternative...

Pan-cell-type prediction of splicing patterns from sequence and splicing factor expression

Alternative splicing is a core determinant of cell-type-specific gene expression in humans, and its dysregulation contributes to many diseases includi...