Genetics

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

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PRSNet-2: End-to-end genotype-to-phenotype prediction via hierarchical graph neural networks

The emergence of large-scale biobanks has opened unprecedented opportunities for the development of ...

Integrative epigenomic analysis uncovers asymmetry of enhancer activity in Brassica napus

Non-coding regulatory regions are essential to the determination of gene expression and plant phenot...

Uncovering the dark transcriptome in polarized neuronal compartments with mcDETECT

Spatial transcriptomics (ST) is a powerful tool for studying the molecular basis of brain diseases. ...

Systematic discovery of single-cell protein networks in cancer with Shusi

Context-specific protein-protein interaction (PPI) drive heterogeneity of primary tumor, forming a f...

Context-aware geometric deep learning for RNA sequence design

RNA design has emerged to play a crucial role in synthetic biology and therapeutics. Although tertia...

Phylogeny-agnostic strain-level prediction of phage-host interactions from genomes

Bacteriophages offer promising alternatives to antibiotics for treating drug-resistant infections an...

Harnessing Contextual Embeddings: A Deep Learning Framework for Predicting PCR Amplification Using BERT Tokenization

Polymerase Chain Reaction (PCR) is a widely used molecular biology technique to amplify DNA sequence...

Nucleotide context models outperform protein language models for predicting antibody affinity maturation

Antibodies play a crucial role in adaptive immunity. They develop as B cell receptors (BCRs): membra...

CLCNet: a contrastive learning and chromosome-aware network for genomic prediction in plants

Genomic selection (GS), which integrates genomic markers with phenotypic data, has emerged as a powe...

Metappuccino: Large Language Model-driven Reconstruction of Sequence Read Archive Metadata for Cancer Research

High-throughput RNA-sequencing has significantly advanced transcriptomic profiling in on-cology. Mil...

A Multi-Agent Approach to Generating Context-Rich Gene Sets

Gene sets are collections of genes that share a common biological function, process, or component th...

Behavioral age-detection in individuals reconstructs minute-scale developmental transcriptomics

Capturing rapid changes in gene-expression across development time is crucial for uncovering the mol...

Oyster: a neural network for modelling genomic sequences that enables exact position-specific k-mer contributions

Genomic functions arise from nucleotide sequences and their overlapping k-mers – subsequences whose ...

A deep learning model captures position-specific effects of plant regulatory sequences and suggests genes under complex regulation

Deep neural networks can be trained to predict gene expression directly from genomic sequence, there...

DeepPathway: Predicting Pathway Expression from Histopathology Images

Spatial transcriptomics (ST) technologies provide spatially resolved gene expression along with imag...

Uncertainty-aware genomic deep learning with knowledge distillation

Deep neural networks (DNNs) have advanced predictive modeling for regulatory genomics, but challenge...

RNA–X: Modeling RNA interactions to design binder RNA and simultaneously target multiple molecules of different types

RNA interactions with proteins, other RNA molecules, and DNA play essential roles in numerous cellul...

SAM-based Automatic Workflow for Histology Cyst Segmentation in Autosomal Dominant Polycystic Kidney Disease

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disorder characterized by the deve...

Predictive power of different Akkermansia phylogroups in clinical response to PD-1 blockade against non-small cell lung cancer

Immune checkpoint blockade has emerged as a promising form of cancer therapy. However, only some pat...

ExactCN: Predicting Exact Copy Numbers on Whole Exome Sequencing Data

The quantification of the precise copy number variations (CNVs) is crucial to understanding the effe...

intDesc-AbMut: Describing and understanding how antibody mutations impact their environmental interactions1

Previously, we proposed a double-point mutation (DPM) strategy involving the simultaneous substituti...

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