Yusuke Hiki

This paper introduces a deep learning model to predict gene regulation relationships for both known and unknown transcription factors, achieving higher accuracy for unknown TFs than existing methods.

This paper introduces MaLoN, an unsupervised method for inferring gene regulatory networks from in vivo data, showing improved accuracy over existing methods in yeast and E. coli.

The paper presents a computational framework for analyzing SARS-CoV-2-host interactions to identify drug targets and model disease mechanisms.

The paper uses genome editing to show that calcium signaling pathways, specifically calmodulin-calcineurin-NFAT and calmodulin-calmodulin kinase-CREB, play distinct roles in anhydrobiosis in Pv11 cells.

The paper describes the development of a computational knowledge repository, the COVID-19 Disease Map, which curates SARS-CoV-2 virus-host interaction mechanisms and provides tools for their analysis and application.