Artificial Intelligence in Biotechnology
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 20 May 2026 | Viewed by 847
Special Issue Editors
Interests: AI; digital biology; digital twins; decentralized learning; IoBNT
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) is revolutionizing biotechnology, facilitating intelligent, data-driven approaches to analyze biological complexity, enhance diagnostics, and optimize bioprocesses. Advances in machine learning, deep learning, and intelligent systems can be utilized for numerous tasks, ranging from multi-omics integration to real-time biosensor analysis and personalized healthcare solutions. Notably, AI has shown great promise in accelerating cancer diagnostics, prognosis prediction, and therapeutic response modeling.
This Special Issue, “Artificial Intelligence in Biotechnology”, aims to compile original research papers and comprehensive reviews that explore the integration of AI across various biotechnological domains. Topics of interest include, but are not limited to, the following:
- AI-driven optimization in bioprocess and fermentation engineering;
- Machine learning for genomics, transcriptomics, and proteomics integration;
- Deep learning applications in cancer diagnostics and imaging;
- Digital twins of biological systems for predictive modeling;
- Internet of Bio-Nano Things (IoBNT) and embedded AI for biosensing;
- AI in synthetic biology and genetic circuit design;
- Federated learning and decentralized AI for biomedical applications;
- AI-guided drug discovery and bio-manufacturing.
Contributions on all research areas are welcome, provided that artificial intelligence is central to the methodology or innovation.
Dr. Mohammad (Behdad) Jamshidi
Dr. Omid Moztarzadeh
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence (AI)
- biotechnology
- machine learning
- deep learning
- digital twins
- multi-omics integration
- cancer diagnostics
- synthetic biology
- internet of bio-nano things (IoBNT)
- drug discovery
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