Advances in Structural Bioinformatics and Next-Generation Sequence Analysis for Drug Design

Dear Colleagues,

Structural Bioinformatics and Next-Generation Sequencing (NGS) are two emerging fields that have revolutionized the way we approach drug design. Structural Bioinformatics allows us to analyze the three-dimensional structures of proteins and other biological macromolecules and to gain insights into their functions and interactions. NGS has enabled us to sequence large amounts of genetic data quickly and efficiently and to explore the genetic basis of diseases and drug responses.

This Special Issue aims to bring together researchers and practitioners working in the areas of Structural Bioinformatics, Bioinformatics, Next-Generation Sequencing, Drug Design, and Deep Learning. We welcome original research articles that report on novel and significant findings in these areas.

Scope and Topics:

We invite high-quality research papers that report on innovative and significant research findings in the following areas:

    Structural Bioinformatics for Drug Design
    Computational methods for analyzing protein–ligand interactions;
    Next-Generation Sequencing for Personalized Medicine;
    Genomic data analysis for drug discovery;
    Deep learning in structural biology and drug design;

Submission Guidelines:

We welcome original and unpublished research articles that report on innovative and significant research findings in the field of Structural Bioinformatics and Next-Generation Sequencing for Drug Design. The submissions should not have been published elsewhere and should not be under consideration for publication in any other venue. We only accept full-length research articles for this Special Issue, and we encourage authors to follow the standard research paper format and provide a clear and concise description of their research findings.

All submitted papers will be peer-reviewed by experts in the field. Manuscripts should be submitted in English, and the submission should adhere to the journal's guidelines and formatting requirements.

Conclusion:

This Special Issue aims to present cutting-edge research in the field of Structural Bioinformatics and Next-Generation Sequencing for Drug Design. We welcome high-quality research papers that report on novel and significant research findings in these areas. We look forward to receiving your submissions and making this Special Issue a success.

Prof. Dr. Alexandre G. De Brevern
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. BioMedInformatics is an international peer-reviewed open access quarterly 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 1000 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.

• structural Bioinformatics for drug design
• computational methods for analyzing protein–ligand interactions
• next-generation sequencing for personalized medicine
• genomic data analysis for drug discovery
• deep learning in structural biology and drug design