생화학분자생물학회

	Daehyun Baek ( baek@snu.ac.kr )
	2010-Present	Assistant, Associate, and Full Professor of School of Biological Sciences at SNU
	2007-2010	Postdoctoral Fellow at Whitehead Institute, MIT
	2000-2007	Ph.D. in Bioengineering at University of Washington
	1993-1999	B.S. in Electrical Engineering at KAIST

Big data and deep learning for RNA biology

The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL studies in other fields, the successful implementation of DL in RB depends heavily on the effective utilization of large-scale datasets from public databases. In achieving this goal, data encoding methods, learning algorithms, and techniques that align well with biological domain knowledge have played pivotal roles. In this review, we provide guiding principles for applying these DL concepts to various problems in RB by demonstrating successful examples and associated methodologies. We also discuss the remaining challenges in developing DL models for RB and suggest strategies to overcome these challenges. Overall, this review aims to illuminate the compelling potential of DL for RB and ways to apply this powerful technology to investigate the intriguing biology of RNA more effectively.

Exp Mol Med. 2024 Jun;56(6):1293-1321. doi: 10.1038/s12276-024-01243-w.
https://pubmed.ncbi.nlm.nih.gov/38871816