Latest AI and machine learning research in genetics for healthcare professionals.
Secondary metabolites in plants have various physiological functions, including antioxidant and anti...
The rapid evolution of DNA foundation models promises to revolutionize genomics, yet comprehensive e...
As sequencing technology improves, more genomes become available. Most lack annotation, automated me...
The rational design of high-specificity binders to peptide–HLA (pHLA) complexes remains a major chal...
Metagenomic binning is crucial for reconstructing microbial genomes from metagenomic sequencing samp...
Tumor Mutational Burden (TMB) is a widely used biomarker for selecting cancer patients for immune ch...
DNA fiber assays are powerful tools for investigating replication dynamics at the single-molecule le...
Predicting enzyme kinetics directly from sequence remains a central challenge in computational biolo...
Transcriptional regulation involves complex interactions with chromatin-associated proteins, but dis...
Neural transplantation holds the potential to repair damaged neural circuits in neurological disease...
The spatial arrangement of cells is fundamental to their function, but single-cell RNA sequencing lo...
RNA–RNA interactions (RRIs) are fundamental to gene regulation and RNA processing, yet their molecul...
Neuronal activity shapes brain development and refines synaptic connectivity in part through dynamic...
Protein foundation models have advanced rapidly, with most approaches falling into two dominant para...
Classical phylogenetics assumes site independence, potentially overlooking epistasis. Protein langua...
Fine-mapping methods, which aim to identify genetic variants responsible for complex traits followin...
Ribonucleic acids (RNAs) are involved in many important biological processes. In particular, non-cod...
Deciphering the functionality of the noncoding genome which includes important cis-regulatory elemen...
Microbial production of methylmercury from inorganic mercury in rice paddies poses health risks to c...
Deep generative models for protein structure and sequence are increasingly used to design proteins w...
Single-cell perturbation sequencing technologies (e.g., Perturb-seq, CROP-seq), which integrate CRIS...