TY - GEN
T1 - Enhanced Detection and Localization of Zinc Finger Proteins Using Advanced Neural Network Techniques
AU - Al Bataineh, Mohammad Fayez
N1 - Publisher Copyright:
© 2024 Owner/Author.
PY - 2024/10/12
Y1 - 2024/10/12
N2 - Zinc Finger proteins play a crucial role in DNA recognition and binding, representing a significant area of study in molecular biology and genetics. Leveraging the advancements in neural network technologies, this paper introduces a groundbreaking approach to detect and localize Zinc Finger protein sequences more effectively. We propose a deep learning-based framework that enhances detection accuracy and operational speed, overcoming the limitations of conventional methods. Our experimental results demonstrate the method's effectiveness, highlighting its potential to transform protein sequence analysis. This research not only furthers our understanding of Zinc Finger proteins but also exemplifies the application of neural networks in complex biological data analysis.
AB - Zinc Finger proteins play a crucial role in DNA recognition and binding, representing a significant area of study in molecular biology and genetics. Leveraging the advancements in neural network technologies, this paper introduces a groundbreaking approach to detect and localize Zinc Finger protein sequences more effectively. We propose a deep learning-based framework that enhances detection accuracy and operational speed, overcoming the limitations of conventional methods. Our experimental results demonstrate the method's effectiveness, highlighting its potential to transform protein sequence analysis. This research not only furthers our understanding of Zinc Finger proteins but also exemplifies the application of neural networks in complex biological data analysis.
KW - Computational Biology
KW - Deep Learning in Bioinformatics
KW - Neural Network Applications
KW - Protein Sequence Detection
KW - Zinc Finger Protein Analysis
UR - http://www.scopus.com/inward/record.url?scp=85209397732&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85209397732&partnerID=8YFLogxK
U2 - 10.1145/3678935.3678936
DO - 10.1145/3678935.3678936
M3 - Conference contribution
AN - SCOPUS:85209397732
T3 - ACM International Conference Proceeding Series
SP - 1
EP - 4
BT - ICBET 2024 - Proceedings of the 2024 14th International Conference on Biomedical Engineering and Technology
PB - Association for Computing Machinery
T2 - 14th International Conference on Biomedical Engineering and Technology, ICBET 2024
Y2 - 14 June 2024 through 17 June 2024
ER -