EMERGING TRENDS IN DEEP LEARNING AND ARTIFICIAL INTELLIGENCE APPLICATIONS FOR COMPUTATIONAL BIOLOGY
Keywords:
Computational Biology, Deep Learning, Artificial Intelligence, Genomics, Proteomics, Drug Discovery, Convolutional Neural NetworksAbstract
Computational Biology has witnessed significant advancements owing to the integration of Deep Learning (DL) and Artificial Intelligence (AI) techniques. This paper explores the emerging trends in the application of DL and AI in Computational Biology. We discuss the utilization of DL models such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) in genomics, proteomics, and drug discovery. Additionally, we delve into the adoption of AI-driven approaches like reinforcement learning and generative adversarial networks (GANs) in tackling complex biological problems. The synthesis of DL and AI methodologies with Computational Biology has paved the way for innovative solutions, offering insights into biological processes and accelerating the pace of scientific discovery
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Copyright (c) 2024 Rajan S. Chandrakuma (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
