Latest AI and machine learning research in genetics for healthcare professionals.
The spatial folding of the genome shapes gene regulation by controlling which loci interact, yet inf...
Protein language models (PLMs) have gained increasing acceptance in tasks ranging from variant effec...
Proper brain function requires the assembly and function of diverse populations of neurons and glia....
Despite growing evidence implicating cellular senescence in tumor progression, methodological challe...
In this work, we present a highly efficient machine learning method for identifying DNA sequences th...
Annotating single-cell and spatial RNA-seq data can be greatly enhanced by leveraging bulk RNA-seq, ...
Astrocytes regulate the activity of nearby neurons so disruption of astrocyte calcium dynamics by tr...
Temporal gene expression is being analyzed via high-throughput profiling of molecular data over time...
CRISPR technologies has become an integral part of plant biotechnology, synthetic biology and basic ...
Woodland strawberry (Fragaria vesca) is a widely used model system for cultivated strawberries and R...
The gut microbiome plays a crucial role in human health, but machine learning applications in this f...
Nanobodies are antigen-binding proteins of great interest as diagnostics and therapeutics. Accurate ...
Transcriptomic biomarker discovery has been a challenge due to variation in datasets and platforms, ...
Alignment-based methods are fundamental for sequence comparison but are often computationally prohib...
Transformer-based genomic sequence-to-function models effectively capture long-range genomic interac...
The integration of transcriptomic and genomic data is essential for dissecting the molecular basis o...
Missense variant interpretation in highly conserved, paralog-rich gene families remains a critical b...
T cell exhaustion limits the efficacy of cancer immunotherapies. Here, we performed genome-wide loss...
Accurate detection of mutations within bacterial species is critical for fundamental studies of micr...
Current DNA damage repair (DDR) biomarkers employ binary classifications that fail to capture the mo...
The development of CRISPR-Cas9 cleavage activity prediction tools hinges on data produced from high-...