Genetics

Using Deep Learning with Different Architectures to Recognize RNA:DNA Triplex Structures from Histone Modification Features

Long non-coding RNAs (lncRNAs) can perform their regulatory roles by forming triple helices through RNA-DNA interaction. Although this has been verified by few in vivo and in vitro methods, in silico approaches that seek to predict the potentials of lncRNAs and DNA sites becoming a triplex forming structure is required. Triplexator have also predicted vast amounts of lncRNAs and DNA sites that has...

Decode-gLM: Tools to Interpret, Audit, and Steer Genomic Language Models

While genomic language models are enabling the de novo design of entire genomes, they remain challenging to interpret, limiting their trustworthiness. Here, we show that sparse autoencoders (SAEs) trained on Nucleotide Transformer activations decompose hidden representations into interpretable biological features without supervision. Across layers and model sizes, SAEs identified over 100 diverse ...

Data-Driven Symbolic Higher-Order Epistasis Discovery with Kolmogorov-Arnold Networks

Many human diseases are polygenic conditions that arise from a complex interplay of interactions between multiple genes at different loci, but current...

Empirical Evaluation of Single-Cell Foundation Models for Predicting Cancer Outcomes

Foundation models pretrained on large-scale single-cell RNA sequencing data present a promising opportunity to advance translational cancer research. ...

RegFormer: A Single-Cell Foundation Model Powered by Gene Regulatory Hierarchies

Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of cellular diversity, but current computational models often fail to incorpo...

Decoding Gene Responsiveness to Synthetic Chromatin Reader-Actuators with Multi-Modal Epigenomic Profiling

Cell identity is regulated by chromatin states that encode gene regulatory memory and shape responses to new inputs. To investigate how chromatin cont...

Batch-Harmonized Machine Learning Framework for Cross-Cohort RNA Biomarker Discovery in Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) lacks reliable prognostic biomarkers. RNA-based signatures suffer from poor reproducibility due to batch effec...

Improving DNA Modeling with WaveDNA: Enhancing Speed, Generalizability, and Interpretability through Wavelet Transformation

Transcription factors (TFs) regulate gene expression by binding to short, specific DNA sequences, known as transcription factor binding sites (TFBSs)....

Deep Learning links TP53 genotype to expression-defined transcriptional program in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a hematological cancer characterized by genetic diversity and poor clinical outcomes. Among various genetic mutations ...

𝒟-BLUP: a differentiable genomic BLUP model with learnable variance and marker weights

Genomic best linear unbiased prediction (GBLUP) is widely used for genomic selection in livestock and crop breeding. There is growing interest in conn...

Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage

Cells must adopt flexible regulatory strategies to make decisions regarding their fate, including differentiation, apoptosis, or survival in the face ...

Comparative Single-Cell Transcriptomics Uncovers Shared and Distinct Molecular Signatures in Cystic Fibrosis and Primary Ciliary Dyskinesia

Cystic Fibrosis (CF) and Primary Ciliary Dyskinesia (PCD) are both inherited respiratory disorders that result in impaired mucociliary clearance, and ...

TP53 and RB1 are predictive genetic biomarkers for sensitivity to cytarabine in gliomas

Therapeutic progress in glioma, one of the most lethal human cancers, has been limited by molecular heterogeneity and lack of biomarker-driven drug de...

Zygosity-Aware DNA Language Modeling Improves Ancestry and Gene Expression Prediction

DNA language models (DNA-LMs) are transforming how genomic sequence information is represented and interpreted. Yet most current approaches treat DNA ...

Puget predicts gene expression across cell types using sequence and 3D chromatin organization data

Gene expression is governed by both linear DNA sequence and three-dimensional (3D) chromatin architecture. Most gene expression prediction models rely...

Multi-cohort, cross-species urinary proteomics reveals signatures of LRRK2 dysfunction in Parkinson’s disease

Pathogenic mutations in Leucine-rich repeat kinase 2 (LRRK2) are the predominant genetic cause of Parkinson’s disease (PD) and often increase kinase a...

Pervasive binding of the stem cell transcription factor SALL4 shapes the chromatin landscape

Mechanistic understanding of how gene activity is regulated has focussed on the roles of transcription factors at promoters and enhancers, whereas mec...

Incorporating Large Language Model-Derived Information into Hypothesis Testing for Genomics

We propose strategies for incorporating the information in large language models (LLMs) into statistical hypothesis tests in genomics studies. Using g...

Billion-Scale Deciphering of Human Gene Regulatory Grammar

Predicting how DNA sequence specifies gene expression remains a core challenge across regulatory genomics. Most predictive assays and models depend on...

TEIP: A Compact, Open-Source Framework for Predicting Tumor Epitope Immunogenicity in Glioblastoma Using Deep Learning and Multi-Modal Biological Features

This work introduces a modular, open-source computational pipeline for glioblastoma (GBM) vaccine design that integrates omics-based OIP5 target disco...