معرفی
Professor Daisuke Kihara is a faculty member in the Department of Biological Sciences at Purdue University. His research focuses on computational methods for understanding protein structure-function relationships, including protein structure prediction, molecular docking, and cryo-EM-based modeling. He leads the Kihara Lab, which develops tools like LZerD for protein-protein docking and DeepMainmast for cryo-EM structure modeling.
Education: Ph.D., Kyoto University (Japan); B.S., University of Tokyo (Japan).
Research interests span bioinformatics, computational biology, and structural genomics. His lab emphasizes integrating machine learning with structural biology to address challenges in protein function prediction, pathway analysis, and large-scale genomic data interpretation.
Key achievements include AIMBE Fellowship (2021), contributions to Alphafold-based modeling, and leadership in international grants reviews (NIH, NSF, EU). Recent work focuses on AI-driven advancements in cryo-EM structure refinement and ligand modeling.
Lab activities include the PULSe interdisciplinary initiative and collaborations with global research networks. Notable tools developed include the DAQ-score database for model quality assessment and the GO2Sum functional summarization tool.
