Health Information Science and Systems - Call for Papers: Special Issue in Integrative Multi-omics for Human Health and Disease Studies

Special Issue in Integrative Multi-omics for Human Health and Disease Studies

Complex diseases feature in the tremendous diversities both in pathogenesis and clinical situations, which have posed great challenges to traditional statistical and bioinformatic analysis. In recent years, there have been growing attempts to employing integrated data from multiple omics levels to achieve a better understanding of the underlying molecular mechanisms during complex disease developments, which would potentially lead to more precise diagnosis and prediction performances, as well as discovery of therapeutic strategies. Nevertheless, current statistical methods are weak in exploiting the inter-omics relationship knowledge. Also, the fast pace growth of multi-omics data and variables brings significant computational challenges such as the curse of dimensionality, intrinsic heterogeneity and information missing, etc. Developing statistical, bioinformatic, and machine learning methods as well as pipelines for efficient and in-depth analysis of multi-omics data becomes an urgent demand.

This special issue aims at reflecting the most recent advances covering computational solutions and successful applications of knowledge discoveries that efficiently utilize the integration of multi-omics data and knowledge to serve health sciences. Both original research and review papers are welcome. 

Topics include but are not limited to:
Data mining and machine learning methods for handling large-scale, heterogeneous, and/or incomplete multi-omics data;Methods for incorporation of biological domain knowledge in multi-omics analysis;Bioinformatics tools and pipelines for integrative analysis and visualization of multi-omics data; andApplications of integrative multi-omics analysis on population study, biomarker discovery, diagnosis and prediction, pathology and drug target discovery, etc.

Integration of molecular omics data with clinical information (EMR, medical images, physiology signals) is encouraged. Animal, plant, or microbial studies without human data are discouraged unless with very prominent clinical implications. Works containing only simple statistical analysis of omics data are also discouraged.

Online Submission:

Please follow the hyperlink “Submit manuscript”  (this opens in a new tab)and upload all of your manuscript files following the instructions given on the screen.

Please ensure you provide all relevant editable source files. Failing to submit these source files might cause unnecessary delays in the review and production process.

Guest Editors:

Yunpeng Cai, Professor, Shenzhen Institutes of Advanced Technology-CAS, China; Email: yp.cai@siat.ac.cn (this opens in a new tab)

Yaohang Li, Professor, Old Dominion University, VA, USA; Email: yaohang@cs.odu.edu (this opens in a new tab)

Xuan Guo, Assistant Professor, University of North Texas, TX, USA; Email: xuan.guo@unt.edu (this opens in a new tab)

Eric Lu Zhang, Assistant Professor, Hong Kong Baptist University, HK, China; Email: ericluzhang@comp.hkbu.edu.hk (this opens in a new tab)

Timeline:

Submission deadline: May 31, 2023 (extensible through personal requests)