Computational and AI Methods for Disease Gene Identification and Diagnosis

Dear Colleagues,

Over the past few decades, it has become clear that exceptional diversity and biodiversity are recurrent features in human evolution, leading advances in predictive, preventative and genomics medicine.

Rapid advances in multiomics techniques, computational data-driven health data science innovation and AI approaches are expected to revolutionize disease gene identification, early disease detection, prediction and diagnosis and strengthen whole-person health research in the next decade. These advances will lead to an improvement in the health of individuals and populations and enhance precision and patient-focused medicine, cost-effective therapeutic strategies and drug discovery, patient outcomes, counselling and delivery of care, as well as support policymakers.

This Special Issue on Computational and AI Methods for Disease Gene Identification and Diagnosis will provide an update on the state of the art in computational data-driven and AI approaches for disease gene identification, risk prediction, risk-stratification and diagnosis as well as critical perspectives and novel insights in data-driven diagnosis. Given the broadness and complexity of these topics, we welcome contributions from experts in the field.

Prof. Dr. Emile R. Chimusa
Dr. Bruno Silvester Lopes
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. Genes 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.

• disease gene identification
• disease risk prediction
• risk stratification
• data-driven data science
• artificial intelligence
• multiomics
• diagnosis
• polygenic risk scores
• genome-wide association studies
• next-generation sequences