Latest AI and machine learning research in genetics for healthcare professionals.
The ability of organisms to adapt and survive depends on the effects of genes and the environment on fitness. However, the multigenic nature of fitness traits and genotype-by-environment interactions hinder our ability to understand the genetic basis of fitness. Here, we established fitness prediction models for 35 environments using machine learning and existing fitness data and different types o...
In targeted spatial transcriptomics technologies, a key challenge is to select an informative gene panel that captures the complexity of cellular and spatial heterogeneity within tissues. Many existing methods use prior knowledge or heuristic selection rules, such as selecting highly variable genes, which overlook gene-gene correlations and may consequently result in suboptimal coverage. To addres...
Facioscapulohumeral muscular dystrophy (FSHD) is an autosomal dominant muscle disorder characterized by a complex genetic etiology, variable prognosis...
Precise modeling of RNA-ligand interactions is essential for understanding RNA functionality and designing RNA-targeted therapeutics. Current computat...
Predicting disease risk from DNA presents an unprecedented emerging challenge as biobanks approach population scale sizes (N > 106 individuals) with u...
Phytophthora capsici is a destructive, broad-host-range oomycete responsible for substantial losses in global agriculture. While most transcriptomic s...
Alzheimer’s disease (AD) is a major global health concern, expected to affect 12.7 million Americans by 2050. Machine learning (ML) algorithms have be...
Predicting whether single amino acid variants (SAVs) in proteins lead to pathogenic outcomes is a critical challenge in molecular biology and precisio...
Analogous to the Encyclopedia of DNA Elements (ENCODE) project, the Functional Annotation of ANimal Genomes (FAANG) consortium has produced chromatin ...
Epigenetic clocks are widely used to estimate biological aging, yet most are built from array-based data from peripheral tissues of predominantly Euro...
Neural circuits emerge during development through dynamic interactions between genetic instructions and environmental cues that shape cell fate, conne...
Artificial Intelligence (AI), and more specifically Machine Learning (ML), have become an increasingly prevalent tool in microbial oceanography. The h...
Accurate prediction of patient outcomes remains a major challenge in oncology. While recent machine learning (ML) approaches often rely on bulk omics ...
The extent to which human adaptations have persisted throughout history despite strong eroding demographic events such as admixture, genetic drift, an...
Nanopore sequencing technologies continue to advance rapidly, offering critical benefits such as real-time analysis, the ability to sequence extremely...
Understanding the cells of origin is essential for overcoming therapy resistance in esophageal squamous cell carcinoma (ESCC). We utilized machine lea...
Transcript assembly remains a challenging task despite the development of numerous methods. A major contributor to low assembly accuracy is the diffic...
How animals repeatedly adapted to life on land is a central question in evolutionary biology. While terrestrialisation occurred independently across a...
The rapid growth of biomedical literature has produced extensive functional knowledge on genetic variants, much of which remains buried in unstructure...
Metabolic dysfunction-associated steatotic liver disease (MASLD, previously NAFLD) is a frequent co-morbidity of obesity and diabetes, with prevalence...