Recent Applications of Machine Learning and Data Mining in Bioinformatics

Dear Colleagues,

The integration of machine learning and data mining techniques with bioinformatics has significantly advanced our understanding of complex biological processes and revolutionized the field of computational biology. As researchers continue to explore innovative ways to analyze and interpret vast biological datasets, this Special Issue aims to showcase the latest developments and applications of machine learning and data mining methods in various areas of bioinformatics.

This Special Issue invites original research articles, reviews, and case studies that demonstrate the recent applications of machine learning and data mining in bioinformatics. The scope of the Special Issue encompasses, but is not limited to, the following topics:

• Genomics: Machine learning techniques for gene expression analysis, gene prediction, variant calling, and genome-wide association studies (GWAS).
• Proteomics: Applications of data mining to proteomic data for protein structure prediction, protein–protein interaction networks, and post-translational modification analysis.
• Biomedical Data Integration: Integrative approaches that combine diverse biological data types such as genomics, proteomics, and clinical data to gain comprehensive insights into biological systems.
• Drug Discovery and Development: The use of machine learning models in drug target identification, virtual screening, and drug design for precision medicine.
• Pathway Analysis: Data mining techniques to uncover biological pathways and functional annotations from high-throughput data.
• Single-Cell Analysis: Machine learning methods for analyzing and interpreting single-cell RNA sequencing data.
• Biological Image Analysis: Applications of deep learning in the analysis of biological images, including microscopy and medical imaging.

Dr. Gianni Costa
Dr. Riccardo Ortale
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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
• data mining
• bioinformatics
• genomics
• proteomics
• biomedical data
• computational biology