Special Issue "Genomics and Proteomics in Personalized and Precision Medicine"

Dear Colleagues,

The rapidly evolving fields of genomics and proteomics hold extraordinary potential for transforming healthcare and disease management through personalized and precision medicine. This revolution in medicine is driven by high-throughput technologies and the exponential growth of genomic data, providing us with an unprecedented level of detail about the intricate biological networks that determine individual health and disease predisposition. This Special Issue, titled “Genomics and Proteomics in Personalized and Precision Medicine”, aims to explore the dynamic interface between genomics, proteomics data, network biology, and their visualization, all within the scope of individualized healthcare.

The aim of this Special Issue is to provide a multidisciplinary platform that brings together state-of-the-art research at the intersection of genomics, proteomics, and individualized healthcare. We strive to showcase innovative methodologies and techniques that enhance our understanding of the complex interplay between genomic and proteomic data and their role in personalized medicine. Through highlighting applications in network biology and data visualization, we hope to provide a comprehensive view of the breadth and depth of the research being conducted in this domain.

This Special Issue is seeking cutting-edge research papers, review articles, and methodological reports. We invite papers that explore novel genomic and proteomic methodologies, address the challenges of visualizing and interpreting high-dimensional genomic data, and elucidate the role of network biology in understanding complex diseases and therapeutic responses. Additionally, we welcome papers that investigate the potential of genomics and proteomics to influence clinical decision making and patient care.

In summary, this Special Issue on "Genomics and Proteomics in Personalized and Precision Medicine" provides an opportunity to engage in a multidisciplinary discourse at the forefront of individualized healthcare. We invite scholars, clinicians, informaticians, bench work scientists, and bioinformaticians to contribute their expertise and perspectives to this rapidly evolving field. Together, we will explore the future landscape of genomics, proteomics, and their synergistic potential in advancing personalized and precision medicine.

Dr. Alper Uzun
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. Journal of Personalized Medicine 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.

• genomics
• proteomics
• personalized medicine
• precision medicine
• genomic data visualization
• network biology
• high-throughput technologies
• bioinformatics
• clinical decision making
• disease predisposition