[Call for papers] Special Issue "Application of Machine Learning Algorithms for Biological Data and Biological Systems"
Tong Gao
Dear Colleagues,
Biological data are collected from a variety of sources, including humans, animals, and viruses. Research on these data has emerged in many fields, such as genetics, proteomics, and healthcare applications, to name a few. Presently, thanks to the development of computer technology, extracting useful data from raw biological data and deciphering intricate biological data have become more feasible through the application of machine learning techniques.
The purpose of this Special Issue is to publish recent developments in machine learning applications for biological data. We invite researchers to submit their research articles and reviews to this Special Issue. Example topics include (but are not limited to) the following, which relate machine learning applications to biological data:
- Use of machine learning algorithms for investigating biological systems;
- New machine learning algorithms;
- Genetics/genomics;
- Proteomics;
- Medical image analysis and diagnosis;
- Drug discovery/development;
- Healthcare applications.
Keywords: machine learning; artificial intelligence; biological data; genetics; genomics; proteomics; bioimage; drug discovery
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.
The deadline for manuscript submissions: 30 June 2024 (can be extended)
More details about the Special Issue can be found here.
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