Genetics

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

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Adversarial Domain Adaptation Enables Knowledge Transfer Across Heterogeneous RNA-Seq Datasets

Accurate phenotype prediction from RNA sequencing (RNA-seq) data is essential for diagnosis, biomark...

REMAG: recovery of eukaryotic genomes from metagenomic data using contrastive learning

Metagenome-assembled genomes (MAGs) are central to exploring microbial communities. Yet, despite the...

Contact-Guided 3D Genome Structure Generation of E. coli via Diffusion Transformers

In this study, we present a conditional diffusion-transformer framework for generating ensembles of ...

FusionRegister: Every Infrared and Visible Image Fusion Deserves Registration

Spatial registration across different visual modalities is a critical but formidable step in multi-m...

Layer-wise Instance Binding for Regional and Occlusion Control in Text-to-Image Diffusion Transformers

Region-instructed layout control in text-to-image generation is highly practical, yet existing metho...

Cancer genomic profiling predicts pathogenicity of BRCA1 and BRCA2 variants

Accurate classification of BRCA1 and BRCA2 variants is essential for cancer risk assessment and ther...

Popformer: Learning general signatures of positive selection with a self-supervised transformer

Understanding natural selection can help shed light on the genetics underpinning adaptive evolution....

Discovery of a phenazine thiol conjugase from sparse data using genome-informed machine learning

Machine learning has enabled powerful biological discoveries using models trained on large datasets....

Circular RNA identification using a genomic language model and a small number of authenticated examples

Genomic language models (gLMs) hold great promise for deciphering biological sequences, yet their ef...

Phenotypic reversion and target prioritization for cellular inflammation via representation learning with foundation models

The identification of genetic perturbations that can reverse disease-associated cellular phenotypes ...

What Do Biological Foundation Models Compute? Sparse Autoencoders from Feature Recovery to Mechanistic Interpretability

Foundation models trained on protein and DNA sequences are increasingly deployed for variant interpr...

Optimal spatial release strategies for confined gene drives and Wolbachia

Gene drives are genetic elements that can rapidly spread through populations, offering potential sol...

Machine Learning for analysis of Multiple Sclerosis cross-tissue bulk and single-cell transcriptomics data

Multiple Sclerosis (MS) is a chronic autoimmune disease of the central nervous system whose molecula...

Genome-wide classification of tumor-derived reads from bulk long-read sequencing

DNA extracted from tissue samples typically derive from of a complex mixture of cell types. Without ...

A Machine Learning Framework for Serogroup Classification of pathogenic species of Leptospira Based on rfb Locus Profiles

Leptospira is a highly diverse genus traditionally classified by serological assays into more than 3...

Tabular foundation model predicts alternative lengthening of telomeres (ALT) and identifies SMARCAL1 as a target in ALT-driven cancers

Alternative lengthening of telomeres (ALT) is a telomerase-independent pathway used by aggressive ca...

Massive-scale single-nucleus multi-omics identifies novel rare noncoding drivers of Parkinson's disease

Most genetic variants contributing to complex diseases reside in the noncoding genome. While common ...

A Resolution-Agnostic Geometric Transformer for Chromosome Modeling Using Inertial Frame

Chromosomes are the carriers of genetic information. Further understanding their 3D structure can he...

A spatial multi-omic portrait of survival outcome for clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the leading cause of kidney cancer-related death, but how...

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