Latest AI and machine learning research in genetics for healthcare professionals.
Predicting cellular responses to perturbations is essential for understanding gene regulation and advancing drug development. Most existing in silico perturbation models treat perturbation–cell interactions with simplistic fusion strategies that overlook the hierarchical nature of regulatory processes, leading to inaccurate predictions and poor generalization across perturbation types. We present ...
Characterizing tissue-specific (TSp) gene expression is crucial for understanding development and disease; however, traditional expression-based methods often overlook the latent “regulatory grammar” embedded in the non-coding DNA, particularly in distal promoter regions. Here, we introduce TSProm, a framework that specializes a DNA foundation model (DNABERT2) to decipher the long-range regulatory...
Accurate genome annotation remains a bottleneck in plants, where polyploidy and repeat-rich sequence confound homology- and RNA-based pipelines. We in...
Chromatin accessibility profiling is an important tool for understanding gene regulation and cellular function. While public repositories house nearly...
Understanding protein sequence-to-function relationship is crucial to assist studies of genetic diseases, protein evolution, and protein engineering. ...
RNA plays vital roles in diverse biological processes, thus drawing much attention as potential therapeutic target. Notably, cryptic ligand binding si...
Programmable control of gene expression in specific cell types is essential for both basic discovery and therapeutic intervention, yet current strateg...
A quantitative measurement can have variation, referred to here as measurement variation, which is a probability distribution. Machine Learning models...
Despite substantial progress in genomic foundation models, accurately predicting inter-individual variation in gene expression from DNA sequence alone...
The Neutral Theory in molecular evolution mainly addresses the allele frequency change of individual loci, postulating that the fixation process of a ...
Determining a gene’s functional significance within a cellular context has long been a challenge, as absolute expression level is an unreliable indica...
Fluorescent proteins (FPs) are widely used reporters for visualizing cellular structures and processes. Traditional wet-lab strategies for FP engineer...
Due to the late detection, aggressive nature, and paucity of treatment options, pancreatic adenocarcinoma (PAAD) remains one of the most lethal cancer...
DNA language models offer a new paradigm for sequence design, yet their ability to generate functional genomic sequences remains underexplored. Plasmi...
Astrocytes shape synapses and circuits, yet human basal ganglia astrocyte diversity is incompletely defined. We built a multimodal atlas by integratin...
P. vivax, the most geographically widespread human malaria parasite with millions of clinical cases per year, is however quasi absent in sub-Saharan A...
Perturbational studies are the gold standard for identifying causal relationships between components of biological systems. Recent technological advan...
Epigenetic clocks estimate chronological and biological age from DNA methylation patterns, but conventional models typically train on hundreds of thou...
Bladder cancer exhibits sex-specific behavior, occurring more frequently in males but progressing to advanced stages more commonly in females. The act...
Nanopore sequencing has emerged as a powerful technology for DNA methylation detection, particularly in repetitive genomic regions and at the haplotyp...