Genetics

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

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Machine learning-guided spatial omics for tissue-scale discovery of cell-type-specific architectures

Multiplexed protein imaging enables spatially resolved analysis of molecular organization in tissues...

Parameter-free representations outperform single-cell foundation models on downstream benchmarks

Single-cell RNA sequencing (scRNA-seq) data exhibit strong and reproducible statistical structure. T...

Designing RNAs with Language Models

RNA design, the task of finding a sequence that folds into a target secondary structure, has broad b...

A custom phenotypic profile for Fanconi anemia: Addressing gaps in existing disease annotations

Fanconi anemia (FA) is a rare genetic disorder of impaired DNA repair characterized by progressive b...

Generative AI Guided Design of High-Affinity T cell Receptors

Developing T cell receptors (TCRs) with sufficiently high affinity for tumor antigens (TAs) remains ...

Deep learning-based non-invasive profiling of tumor transcriptomes from cell-free DNA for precision oncology

Circulating tumor DNA (ctDNA) profiling from liquid biopsies is increasingly adopted as a minimally ...

A spectral framework for measuring diversity in multiple sequence alignments

Machine learning (ML) methods for proteins and RNAs rely on multiple sequence alignments (MSAs) and ...

Network-based integration of gene expression and DNA methylation identifies prognostic biomarkers for early-stage pancreatic cancer

Pancreatic ductal adenocarcinoma remains one of the most lethal malignancies, largely due to the abs...

A machine learning approach to identify key Epigenetic Transcripts for Ageing research in human blood (Epitage)

DNA methylation is an established biomarker of human ageing, and analysing CpGs grouped by transcrip...

C^2ROPE: Causal Continuous Rotary Positional Encoding for 3D Large Multimodal-Models Reasoning

Recent advances in 3D Large Multimodal Models (LMMs) built on Large Language Models (LLMs) have esta...

dnaHNet: A Scalable and Hierarchical Foundation Model for Genomic Sequence Learning

Genomic foundation models have the potential to decode DNA syntax, yet face a fundamental tradeoff i...

Interpretable machine learning model for predicting kidney failure among CAKUT children in multicenter large-scale study

Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidn...

Structural phenotypes of osteoarthritis are clinically and genetically distinct: findings from 59,539 UK Biobank participants

OBJECTIVES Osteoarthritis is a heterogeneous disease, with diverse structural patterns likely reflec...

Multi-omics Analyses of Facial Skin in Acne Identify Distinct Microbial and Metabolic Features at Lesional and Non-lesional Sites

The microbial and biochemical landscape of clinically normal-appearing skin in individuals with acne...

Leveraging Foundation Models for the Characterisation of Small RNA Properties

ABSTRACT Small interfering RNAs (siRNAs) provide a promising therapeutic approach capable of selecti...

Autoregressive forecasting of future single-cell state transitions

Existing methods for dynamic analysis of static single-cell RNA-sequencing data can reconstruct temp...

SERPINA3 and NDRG1 are critical diagnostic immune genes associated with macrophages in preeclampsia

Objective: The immune system plays a role in the occurrence and progression of numerous pregnancy co...

STRAND: Sequence-Conditioned Transport for Single-Cell Perturbations

Predicting how genetic perturbations change cellular state is a core problem for building controllab...

Deep Learning-Based Screening for POLE mutations on Histopathology Slides in Endometrial Cancer

POLE sequencing for somatic mutations (POLEmut) guides adjuvant therapy in endometrial cancer (EC), ...

EpiExpr: Predicting gene expression using epigenetic data and chromatin interactions

Decoding gene expression from epigenomic landscapes remains a fundamental challenge in genomics. We ...

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