Artificial intelligence (AI) is playing an increasingly crucial role in advancing bioinformatics and healthcare. It enables the efficient analysis of large-scale biological and biomedical data and provides innovative solutions to complex health-related challenges. AI-driven approaches have been widely adopted in areas such as biomedical imaging, drug discovery and development, disease prediction, genomic and proteomic analysis, and the identification of clinically significant patterns from high-throughput datasets. These technologies are transforming modern healthcare research and are essential for the development of precision medicine and intelligent clinical decision-making.

This Special Issue aims to present recent advances in AI methodologies, computational strategies, and practical health applications within bioinformatics. It focuses on the development and application of novel AI tools to address biological and medical challenges, improve health analytics, and enhance the interpretation of complex biomedical data. Additionally, the Special Issue will highlight emerging AI solutions for ensuring the security and privacy of biological and medical data, safeguarding reliability, and implementing trustworthy AI in healthcare environments. Contributions that address both methodological innovation and real-world clinical or healthcare applications are particularly encouraged.

Also, it discusses recent approaches in bioinformatics related to Genomic Signal Processing (GSP) and Genomic Image Processing (GIP). GSP and GIP are cutting-edge, interdisciplinary fields that apply engineering principles and mathematical transforms to biological data. They allow researchers to treat complex DNA, RNA, and protein sequences as mathematical signals or visual patterns.

Topics of interest include, but are not limited to:

• AI-driven biomedical image analysis
• Machine learning and deep learning in bioinformatics and health
• AI applications in drug discovery and precision medicine
• Genomic, proteomic, and multi-omics data analysis
• Disease prediction, diagnosis, and prognosis using AI
• Explainable and trustworthy AI in healthcare
• AI for clinical decision support systems
• Biological and medical data security and privacy
• Intelligent health analytics and large-scale biomedical data processing
• AI applications in Microarray
• AI applications in drug- drug interaction predication
• Bioinformatics analysis in triple‑negative breast cancer
• Genomic Image Processing approach
• Genomic Signal Processing approach