AI Proteomics: Technologies and Their Potential
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 3580
Special Issue Editor
Interests: AI proteomics; social implementation of proteomics; healthcare based on personalized proteomics; commercialization of proteomics in industry; database construction and operation by integrating a wide variety of data including life logs; effective use of biobanks; solving problems in a super-aging societies; solving the problem of high medical costs
Special Issue Information
Dear Colleagues,
Since the dawn of molecular biology, it has been considered that bird’s-eye and comprehensive analysis (proteomics) of gene products (proteins) that change in real time is the ultimate biological diagnosis. However, to date, there has been a limit in manually handling massive and complicated proteomics data. In recent years, though, the capabilities of AI have progressed innovatively, and it has become possible to process proteomics data using AI. Unlike the conventional science of repeating hypothesis construction and its verification, AI is effective in data-driven knowledge discovery in proteomics, which constructs a hypothesis from the obtained data. In that sense, proteomics and AI are very compatible. Thus, although proteomics data have always been a treasure trove of knowledge, there is a high possibility that a lot more of these wonderful treasures will be unearthed by processing proteomics data with AI. In addition, high-speed processing of data by AI is also envisioned for real-time vital diagnosis via real-time analysis of proteomics data that reflects real-time changing vital conditions. What is more, there are great expectations for the practical application of proteomics by AI in all fields dealing with living organisms, not just those limited to humans.
In this Special Issue, we invite submissions exploring cutting-edge research and recent advances in the fields of AI-aided proteomics. Both theoretical and experimental studies are welcome, as well as comprehensive review and survey papers.
Prof. Dr. Nobuhiro Hayashi
Guest Editor
Manuscript Submission Information
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Keywords
- Artificial intelligence (AI)
- Proteomics
- Diagnosis
- Healthcare
- Database
- Data-driven research
