Computational Intelligence and Deep Learning in Bioinformatics

Dear Colleagues,

The increasing availability of large-scale biological data, coupled with the complex nature of these interactions, has made it necessary to develop new computational approaches for data analysis and modeling. Computational intelligence and deep learning have emerged as powerful tools for addressing these challenges, providing new avenues for discovering biological insights.

This Special Issue aims to provide a comprehensive overview of the latest advancements in applying computational intelligence and deep learning in bioinformatics. We welcome original research articles, reviews, and perspectives that address the following topics:

• Interpretability and explainability of deep learning models in bioinformatics;
• Integration of multi-omics data using deep learning;
• Applications of deep reinforcement learning and generative models in bioinformatics;
• Computational intelligence methods for gene expression analysis, genetic association studies, and genomic data integration;
• Computational intelligence and deep learning for epigenetics;
• Computational intelligence and deep learning for functional genomics;
• Deep learning and computational intelligence for metagenome analysis;
• Deep learning for gene editing and synthetic biology.

Dr. Marcio Dorn
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. 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.

• interpretability and explainability of deep learning models in bioinformatics
• integration of multi-omics data using deep learning
• applications of deep reinforcement learning and generative models in bioinformatics
• computational intelligence methods for gene expression analysis, genetic association studies, and genomic data integration
• computational intelligence and deep learning for epigenetics
• computational intelligence and deep learning for functional genomics
• deep learning and computational intelligence for metagenome analysis
• deep learning for gene editing and synthetic biology