Deep learning in CRISPR-Cas systems: a review of recent studies

Minhyeok Lee

doi:10.3389/fbioe.2023.1226182

Deep learning in CRISPR-Cas systems: a review of recent studies

Front Bioeng Biotechnol. 2023 Jul 3:11:1226182. doi: 10.3389/fbioe.2023.1226182. eCollection 2023.

Author

Minhyeok Lee¹

Affiliation

¹ School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Republic of Korea.

Abstract

In genetic engineering, the revolutionary CRISPR-Cas system has proven to be a vital tool for precise genome editing. Simultaneously, the emergence and rapid evolution of deep learning methodologies has provided an impetus to the scientific exploration of genomic data. These concurrent advancements mandate regular investigation of the state-of-the-art, particularly given the pace of recent developments. This review focuses on the significant progress achieved during 2019-2023 in the utilization of deep learning for predicting guide RNA (gRNA) activity in the CRISPR-Cas system, a key element determining the effectiveness and specificity of genome editing procedures. In this paper, an analytical overview of contemporary research is provided, with emphasis placed on the amalgamation of artificial intelligence and genetic engineering. The importance of our review is underscored by the necessity to comprehend the rapidly evolving deep learning methodologies and their potential impact on the effectiveness of the CRISPR-Cas system. By analyzing recent literature, this review highlights the achievements and emerging trends in the integration of deep learning with the CRISPR-Cas systems, thus contributing to the future direction of this essential interdisciplinary research area.

Keywords: CRISPR-Cas system; CRISPR-Cas9; artificial intelligence; deep learning; genome editing; guide RNA; off-target activity; on-target activity.

Publication types

Review

Grants and funding

The authors declare that this study received funding/Research Grant from Generative Artificial Intelligence System Inc. (GAIS). The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.