KAUST DepartmentThe KAUST School, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
Computer Science Program
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Computational Bioscience Research Center (CBRC)
KAUST Grant NumberFCC/1/1976-44-01
Permanent link to this recordhttp://hdl.handle.net/10754/689996
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AbstractGene regulation is a central topic in cell biology. Advances in omics technologies and the accumulation of omics data have provided better opportunities for gene regulation studies than ever before. For this reason deep learning, as a data-driven predictive modeling approach, has been successfully applied to this field during the past decade. In this article, we aim to give a brief yet comprehensive overview of representative deep-learning methods for gene regulation. Specifically, we discuss and compare the design principles and datasets used by each method, creating a reference for researchers who wish to replicate or improve existing methods. We also discuss the common problems of existing approaches and prospectively introduce the emerging deep-learning paradigms that will potentially alleviate them. We hope that this article will provide a rich and up-to-date resource and shed light on future research directions in this area.
CitationLi, Z., Gao, E., Zhou, J., Han, W., Xu, X., & Gao, X. (2023). Applications of deep learning in understanding gene regulation. Cell Reports Methods, 3(1), 100384. https://doi.org/10.1016/j.crmeth.2022.100384
SponsorsThis work was supported by Office of Research Administration (ORA) at KAUST under award numbers FCC/1/1976-44-01, FCC/1/1976-45-01, URF/1/4098-01-01, URF/1/4352-01-01, REI/1/5202-01-01, REI/1/4940-01-01, RGC/3/4816-01-01, and REI/1/0018-01-01.
JournalCell reports methods
PubMed Central IDPMC9939384
Except where otherwise noted, this item's license is described as Archived with thanks to Cell reports methods under a Creative Commons license, details at: http://creativecommons.org/licenses/by-nc-nd/4.0/
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