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 November 2025 | Viewed by 28

Special Issue Editors


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Guest Editor
School of Electrical and Data Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia
Interests: AI; digital biology; digital twins; decentralized learning; IoBNT

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Guest Editor
Faculty of Medicine in Pilsen, Charles University, 323 00 Pilsen, Czech Republic
Interests: biotechnological intelligence; medical AI; cancer diagnostics; predictive healthcare

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:

  1. AI-driven optimization in bioprocess and fermentation engineering;
  2. Machine learning for genomics, transcriptomics, and proteomics integration;
  3. Deep learning applications in cancer diagnostics and imaging;
  4. Digital twins of biological systems for predictive modeling;
  5. Internet of Bio-Nano Things (IoBNT) and embedded AI for biosensing;
  6. AI in synthetic biology and genetic circuit design;
  7. Federated learning and decentralized AI for biomedical applications;
  8. 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

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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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Published Papers

This special issue is now open for submission.
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