Latest AI and machine learning research in genetics for healthcare professionals.
Accurate prognosis in lung adenocarcinoma (LUAD) requires integration of high-dimensional transcriptomic profiles with compact but clinically stable patient covariates. Naive fusion strategies allow the high-variance RNA-seq modality to dominate learned representations, suppressing clinical signal. We present Cooperative Modular Representation Learning (CMRL), an uncertainty-gated multimodal frame...
Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysi...
Single-cell drug perturbation models are increasingly used to predict how compounds remodel cellular states, but they are still largely assessed by ex...
Cell Painting microscopy captures how cells change after a chemical or genetic perturbation. Connecting these images to the perturbations that produce...
Full-length RNAs, particularly messenger RNAs, often exceed the context lengths used to pretrain existing RNA foundation models, limiting complete-tra...
Off-target cleavage is a central safety concern for CRISPR-Cas9 genome editing, particularly in therapeutic applications where unintended double-stran...
Protein phosphatase 2A containing the B56{delta} regulatory subunit (PP2A-B56{delta}) is a critical signaling enzyme whose dysregulation is associated...
Bayesian network (BN) structure learning (BNSL) from heterogeneous data is a classical problem in probabilistic machine learning and knowledge discove...
Motivated by the classical Chan-Vese model and the ability of deep priors to capture complex spatial structures, we develop a segmentation model that ...
Transcriptional regulation is governed by interactions between cis-regulatory elements (CREs) and trans-acting regulators in a context-specific manner...
BackgroundFive-year survival from lung cancer exceeds 60% at stage I-II but falls below 10% once metastasis occurs. Low-dose CT (LDCT) screening reduc...
Genome-wide association studies (GWAS) have identified hundreds of common genetic variants associated with regional brain volumes, enabling the constr...
Single-molecule protein sequencing promises to democratize clinical proteomics, but platforms retrofitting static DNA-sequencing nanopores face a fund...
PurposeThe 11 Integrative Cluster (IntClust) genomic subtypes of breast cancer have both prognostic and predictive value but require integrated DNA co...
Missense mutations and post-translational modifications (PTMs) are major molecular perturbations that reshape protein function but are traditionally s...
Epigenetic clocks based on DNA methylation patterns are among the most accurate molecular correlates of chronological age, yet widely used clocks are ...
Motivation: RNA language models learn representations that support structure and function prediction, but which biological concepts their hidden state...
In this work, we present a machine learning model for identifying pathogenic DNA variants. The model was learned from the analysis of normal and patho...
Bulk RNA sequencing remains the predominant profiling strategy for large clinical cohorts, but it aggregates transcriptional signals across cell popul...
The benzoxazolinate moiety is a key functional group found in a few natural products (NPs), exhibiting diverse bioactivities, including antitumor, ant...