Special Issue "Machine Learning and Bioinformatics: Discovering Biomarkers for Respiratory and Cardiovascular Diseases"

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Biochemistry, Biophysics and Computational Biology".

Deadline for manuscript submissions: 31 October 2023 | Viewed by 218

Special Issue Editor

Business School, University of Surrey, Guildford, UK
Interests: medical statistics; machine learning; deep learning; diagnostics; respiratory diseases; cardiovascular diseases

Special Issue Information

Dear Colleagues,

Machine learning and bioinformatics have been widely applied in the field of disease diagnosis, prognosis, and treatment. In this Special Issue, we focus on discovering biomarkers for respiratory and cardiovascular diseases using machine learning and bioinformatics.

Respiratory and cardiovascular diseases are major causes of morbidity and mortality worldwide. Biomarkers, which are measurable indicators of biological processes, can be used to diagnose, prognosis, and monitor the progression of these diseases. Machine learning algorithms can be used to identify and validate potential biomarkers from high-throughput data generated from various omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics.

The Special Issue invites original research articles, reviews, and perspectives on the following topics:

  1. Applications of machine learning and bioinformatics in the discovery of biomarkers for respiratory and cardiovascular diseases.
  2. Integration of multi-omics data for the identification of disease-specific biomarkers.
  3. Development of machine learning-based models for the prediction of disease risk, diagnosis, prognosis, and treatment response.
  4. Validation of identified biomarkers using clinical samples and large-scale population-based studies.
  5. Challenges and opportunities in the application of machine learning and bioinformatics in biomarker discovery for respiratory and cardiovascular diseases.

We welcome contributions from researchers in the fields of machine learning, bioinformatics, respiratory diseases, cardiovascular diseases, and related disciplines. The Special Issue aims to provide a platform for the exchange of ideas, discussion, and dissemination of cutting-edge research in this area.

Dr. Vasilis Nikolaou
Guest Editor

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. Life 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 2600 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.


  • machine learning
  • bioinformatics
  • biomarkers
  • respiratory diseases
  • cardiovascular diseases
  • genomics
  • diagnosis
  • prognosis
  • treatment response
  • disease-risk prediction

Published Papers

This special issue is now open for submission.
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