TY - GEN
T1 - Leveraging a Smart AI-Controlled gRNA in Genome Editing for Identification and Replacement of Genetic Mutations
AU - Guha, Debanksh
AU - Avtaran, Divya Kumar
AU - Lenka, Rahul
AU - Yang, Tiansheng
AU - Wang, Lu
AU - Rathore, Rajkumar Singh
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025/6/10
Y1 - 2025/6/10
N2 - The field of genetic engineering has witnessed a paradigm shift with the advent of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology. CRISPR empowers researchers with the remarkable ability to precisely modify genomes, offering immense potential for treating genetic diseases. However, achieving high levels of accuracy and specificity in gene editing remains a critical challenge. This paper explores the burgeoning field of AI-controlled guide RNA (gRNA) design, a revolutionary approach that harnesses the power of artificial intelligence (AI) to optimize gRNA selection and enhance CRISPR genome editing outcomes. By integrating AI algorithms for gRNA design, researchers aim to revolutionize personalized medicine and targeted therapies through a more precise and efficient approach to identifying and replacing detrimental genetic mutations.
AB - The field of genetic engineering has witnessed a paradigm shift with the advent of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology. CRISPR empowers researchers with the remarkable ability to precisely modify genomes, offering immense potential for treating genetic diseases. However, achieving high levels of accuracy and specificity in gene editing remains a critical challenge. This paper explores the burgeoning field of AI-controlled guide RNA (gRNA) design, a revolutionary approach that harnesses the power of artificial intelligence (AI) to optimize gRNA selection and enhance CRISPR genome editing outcomes. By integrating AI algorithms for gRNA design, researchers aim to revolutionize personalized medicine and targeted therapies through a more precise and efficient approach to identifying and replacing detrimental genetic mutations.
KW - Artificial intelligence
KW - Convolutional neural network
KW - Genomics
KW - Guide RNA (gRNA)
KW - Internet of Things
KW - Sensors
UR - https://www.scopus.com/pages/publications/105008992894
U2 - 10.1007/978-981-96-3244-2_51
DO - 10.1007/978-981-96-3244-2_51
M3 - Conference contribution
AN - SCOPUS:105008992894
SN - 9789819632435
T3 - Lecture Notes in Networks and Systems
SP - 649
EP - 656
BT - Proceedings of Fourth International Conference on Computing and Communication Networks, ICCCN 2024
A2 - Kumar, Akshi
A2 - Swaroop, Abhishek
A2 - Shukla, Pancham
PB - Springer Science and Business Media Deutschland GmbH
T2 - 4th International Conference on Computing and Communication Networks, ICCCN 2024
Y2 - 17 October 2024 through 18 October 2024
ER -