Genetics

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

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Predicting Protein Cascade Expression from H&E Images

Protein expression within oncogenic or suppressive pathways is a hallmark indicator of oncogenesis. ...

Machine learning and burden analyses highlight novel genes in Parkinson's Disease

Background Genome-wide association studies (GWAS) have identified numerous risk loci for Parkinson's...

AlphaGenome -enabled analysis of non-coding regulatory variants underlying RHD Expression

Systematic identification of functional non-coding regulatory variants remains a major challenge in ...

Predicting Gene Mutations in Colon Cancer Using Long-Term Temporal Dependency Learning on a Directed Co-Occurrence Asymmetry Graph

Accurate prediction of mutational dependencies to model tumor evolution can improve our understandin...

Clinical and Cross-Domain Validation of an LLM-Guided, Literature-Based Gene Prioritization Framework

Background: We previously published a literature based pipeline for sepsis gene prioritization (PS3 ...

Noise-immune and AI-enhanced DNA storage via adaptive partition mapping of digital data

Encoding digital information into DNA sequences offers an attractive potential solution for storing ...

FASTR: Reimagining FASTQ via Compact Image-inspired Representation

Motivation: High-throughput sequencing (HTS) enables population-scale genomics but generates massive...

Gene-exposure interactions regulate cytokine-mediated chronic inflammation and cardiac remodeling

Background: Chronic inflammation predicts adverse cardiovascular outcomes, but mechanisms linking sy...

EpiTADformer: A Transformer-Based Model for High-Resolution TAD Boundary Detection Using Epigenomic Signal Embeddings

The human genome is partitioned at different levels of 3D genome organization, with topologically as...

Evolving Without Ending: Unifying Multimodal Incremental Learning for Continual Panoptic Perception

Continual learning (CL) is a great endeavour in developing intelligent perception AI systems. Howeve...

VAETracer: Mutation-Guided Lineage Reconstruction and Generational State Inference from scRNA-seq

Somatic mutations accumulate with cell division and are key to understanding tumor evolution. While ...

TPCAV: Interpreting deep learning genomics models via concept attribution

Interpreting genomics deep learning models remains challenging. Existing feature attribution methods...

SigFormer: an Attention-Based Framework for Robust Single-Sample Mutational Signature Decomposition

Somatic mutational signatures imprint the history of exogenous exposures and endogenous processes on...

Computational Discovery of CRISPR-Cas13b Guide RNAs for Broad-Spectrum Dengue Virus Targeting

Dengue (DENV), an RNA virus, remains a significant global health threat, particularly in developing ...

Robust Machine Learning for Regulatory Sequence Modeling under Biological and Technical Distribution Shifts

Robust machine learning for regulatory genomics is studied under biologically and technically induce...

Characterizing Highly Conserved Fragments in 3'UTRs via Computational and Transfer Learning Approaches

3' untranslated regions (3' UTRs) serve as regulatory platforms that modulate translation, mRNA loca...

Extracting useful information about reversible evolutionary processes from irreversible evolutionary accumulation models

Evolutionary accumulation models (EvAMs) are an emerging class of machine learning methods designed ...

Pharmacogenomic Determinants of Post-Liver Transplant Diabetes Mellitus: A Systematic Review and In Silico Pharmacogenomic Analysis

Introduction: Tacrolimus remains central to liver transplantation, yet its narrow therapeutic index ...

A predicted cancer dependency map for paralog pairs

Background Genome-wide CRISPR screening has enabled the development of dependency maps in hundreds o...

STRUCT2SEQ: RNA INVERSE FOLDING WITH DEEP Q-LEARNING

RNA molecules play critical roles in biology and therapeutics, with their function intimately tied t...

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