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Integrative Analysis of Multi-Omics Data for Precision Medicine

Edited by:

Professor Li Shen, PhD, FAIMBE, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, United States of America

Associate Professor Jingwen Yan, PhD, Department of BioHealth Informatics, Indiana University Indianapolis, United States of America

Submission Status: Open   |   Submission Deadline: 31 July 2024

BioData Mining is calling for submissions to our new Collection on "Integrative Analysis of Multi-Omics Data for Precision Medicine".

Image credit: janews094 /

About the collection

Recent advances in acquiring large-scale high-throughput multi-omics data across multiple biological layers have provided us unprecedented opportunities to gain new insights into the intricate molecular landscapes of human health and disease. This Collection is aimed at showcasing cutting-edge research that harnesses the power of multi-omics data integration to drive advancements in precision medicine. The Collection will feature peer-reviewed papers focusing on the development, evaluation, and application of innovative approaches that bridge genomics, transcriptomics, proteomics, metabolomics, and other omics domains, ultimately paving the way for a deeper understanding of disease mechanisms and the development of personalized therapeutic strategies. 

We encourage submissions that delve into the challenges and opportunities posed by multi-omics data integration, including but not limited to:

• Novel computational methodologies
• Integrative frameworks
• Data fusion techniques
• Network analyses
• Machine learning approaches

Specific biomedical and clinical topics of interest include, but are not limited to:

• Diagnosis and prognosis
• Biomarker discovery
• Disease subtyping and patient stratification
• Systems biology and disease mechanisms
• Therapeutic development and drug repurposing

By fostering collaboration between diverse scientific disciplines, this Collection seeks to unravel the complex interplay of molecular factors driving health and disease, and how this knowledge can be translated into more effective, precise, and personalized patient care.

  1. Prioritizing candidate drugs based on genome-wide expression data is an emerging approach in systems pharmacology due to its holistic perspective for preclinical drug evaluation. In the current study, a networ...

    Authors: Regan Odongo, Asuman Demiroglu-Zergeroglu and Tunahan Çakır
    Citation: BioData Mining 2024 17:5

Submission Guidelines

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Before submitting your manuscript, please ensure you have read our submission guidelines. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Integrative Analysis of Multi-Omics Data for Precision Medicine" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Guest Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests.