Artificial Intelligence and Computational Biology in Gene Therapy: A Review

Area of Science:

• * Computational biology and artificial intelligence applications in gene therapy.
• * Interdisciplinary research at the intersection of AI, computational biology, and medicine.

Background:

• * Gene therapy is a rapidly advancing field with significant potential across various scientific disciplines.
• * Computational biology and artificial intelligence (AI) are increasingly integrated into biological research and development.

Purpose of the Study:

• * To highlight the role of computational biology and AI in enhancing gene therapy.
• * To outline the key steps in gene therapy where AI and computational biology offer significant contributions.
• * To showcase the diverse tools and methodologies employed in this interdisciplinary field.

Main Methods:

• * Analysis of genomics, transcriptomics, and proteomics data.
• * Application of machine learning algorithms for predictive modeling.
• * Utilization of molecular interaction studies for understanding biological systems.
• * Computational modeling for gene delivery and vector design.

Main Results:

• * Identification of novel gene targets for therapeutic intervention.
• * Design of innovative vectors for efficient gene delivery.
• * Optimization of experimental conditions for gene therapy protocols.
• * Prediction of treatment outcomes and potential adverse effects, such as immune responses.

Conclusions:

• * AI and computational biology provide powerful tools to advance gene therapy.
• * These technologies enable more precise gene identification, editing, and vector development.
• * Integration of computational approaches can lead to safer, more effective gene therapy treatments.