Artificial intelligence (AI) models based on deep learning now represent the state of the art
for making functional predictions in genomics research. However, the underlying basis on …

Enhancers are genomic DNA elements controlling spatiotemporal gene expression. Their
flexible organization and functional redundancies make deciphering their sequence-function …

Neuroscience studies are often carried out in animal models for the purpose of
understanding specific aspects of the human condition. However, the translation of findings …

The tremendous amount of biological sequence data available, combined with the recent
methodological breakthrough in deep learning in domains such as computer vision or …

Gene regulatory elements drive complex biological phenomena and their mutations are
associated with common human diseases. The impacts of human regulatory variants are …

Investigators have recently introduced powerful methods for population genetic inference
that rely on supervised machine learning from simulated data. Despite their performance …

Recent discoveries of extreme cellular diversity in the brain warrant rapid development of
technologies to access specific cell populations within heterogeneous tissue. Available …

Gene regulatory networks (GRNs) serve as useful abstractions to understand transcriptional
dynamics in developmental systems. Computational prediction of GRNs has been …

Phytophthora sojae is a soil-borne oomycete and the causal agent of Phytophthora root and
stem rot (PRR) in soybean (Glycine max [L.] Merrill). Yield losses attributed to P. sojae are …

Decoding the epigenomic landscapes in diverse tissues and cell types is fundamental to
understanding molecular mechanisms underlying many essential cellular processes and …