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Advanced machine learning and health-related multi-omics data

Guest Editors:
Alejandro Rodriguez Gonzalez: Universidad Politécnica de Madrid, Spain
Wei Lan Guangxi University, China


BMC Medical Informatics and Decision Making, BMC Medical Genomics welcomed submissions to Collection on Advanced machine learning and health-related multi-omics data.

The development of novel techniques based on data-driven approaches, especially focused on artificial intelligence techniques, for the study of human health from a computational perspective, is gaining momentum nowadays. Different types of available data are making new types of analysis possible, opening new research areas. Multi-omics data are a particular case of data combining different sources of information that can be used for deeper analysis of human health, to have a better understanding of underlying connections and associations. The application of artificial intelligence can be of particular interest to unveil such complex relationships, with potential insights in real-world scenarios, including the clinical application.

Please email Patrik Flammer, the in-house editor for BMC Medical Genomics, (patrik.flammer@springernature.com) or Piero Lo Monaco, the in-house editor for BMC Medical Informatics and Decision Making (piero.lomonaco@springernature.com) if you would like more information. 

Meet the Guest Editors

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Prof. Alejandro Rodríguez-González, Universidad Politécnica de Madrid, Spain

Prof. Alejandro Rodríguez-González, Ph.D., is a Full Professor and Principal Investigator of the Medical Data Analysis laboratory (MEDAL) at the Center for Biomedical Technology in Universidad Politécnica de Madrid. His main research expertise is focused on applying machine learning methods to different types of biomedical information with a special focus on the area of disease networks to increase our current understanding of diseases and their relationships.


Dr. Wei Lan, Guangxi University, China
Dr. Wei Lan received his PhD degree from Central South University in 2016. He is currently an associate professor of the School of Computer, electronic and information at Guangxi University. His research interests include bioinformatics and artificial intelligence. He has published more than 50 refereed papers in international journals and conferences. He has been serving as an associate editor of frontiers in genetics and editorial board member of BMC Medical Genomics, BMC Digital Health, BMC Medical Informatics and Decision Making, Frontiers in Bioscience-Landmark and BioMed Research International.

 


About the collection


This cross-journal collection welcomed articles presenting novel developments and applications of advanced machine learning methods in multi-omics data with clinical relevance for human health, from the perspective of either medical informatics or genomics, with particular attention to deep learning and reinforcement learning methods. For submissions reporting associations between a specific parameter and a health condition, the collection considered studies that include at least an experimental validation step to support their findings. Studies about specific applications, such as high-dimensional statistics & omics data analysis and diagnostic tools, or novel software or databases were also considered.

In this context, potential lines of interest, include, but are not limited to:

  • Multi-omic data integration methods for machine learning analysis
  • Explainable machine learning methods for multi-omic data
  • Design and development of deep-learning/reinforcement learning based methods for multi-omic data


Image credit: © naddi / iStock

  1. LMNA gene encodes lamin A/C protein which participates in the construction of nuclear lamina, the mutations of LMNA result in a wide variety of diseases known as laminopathies. LMNA-related dilated cardiomyopathy...

    Authors: Lei Chang, Rong Huang, Jianzhou Chen, Guannan Li, Guangfei Shi, Biao Xu and Lian Wang
    Citation: BMC Medical Genomics 2023 16:229
  2. This retrospective study aims to validate the effectiveness of artificial intelligence (AI) to detect and classify non-mass breast lesions (NMLs) on ultrasound (US) images.

    Authors: Guoqiu Li, Hongtian Tian, Huaiyu Wu, Zhibin Huang, Keen Yang, Jian Li, Yuwei Luo, Siyuan Shi, Chen Cui, Jinfeng Xu and Fajin Dong
    Citation: BMC Medical Informatics and Decision Making 2023 23:174
  3. Diabetic peripheral neuropathy (DPN) is a common complication of diabetes. Predicting the risk of developing DPN is important for clinical decision-making and designing clinical trials.

    Authors: Xiaoyang Lian, Juanzhi Qi, Mengqian Yuan, Xiaojie Li, Ming Wang, Gang Li, Tao Yang and Jingchen Zhong
    Citation: BMC Medical Informatics and Decision Making 2023 23:146
  4. As the first point of contact for patients with health issues, general practitioners (GPs) are frequently confronted with patients presenting with non-specific symptoms of unclear origin. This can result in de...

    Authors: Dania Schütze, Svea Holtz, Michaela C. Neff, Susanne M. Köhler, Jannik Schaaf, Lena S. Frischen, Brita Sedlmayr and Beate S. Müller
    Citation: BMC Medical Informatics and Decision Making 2023 23:144
  5. Atherosclerosis (AS) is a leading cause of morbidity and mortality in older patients and features progressive formation of plaques in vascular tissues. With the progression of atherosclerosis, plaque rupture m...

    Authors: Zhanli Peng, Kangjie Wang, Shenming Wang, Ridong Wu and Chen Yao
    Citation: BMC Medical Genomics 2023 16:139
  6. The aim of this study was to construct a model used for the accurate diagnosis of Atopic dermatitis (AD) using pyroptosis related biological markers (PRBMs) through the methods of machine learning.

    Authors: Wenfeng Wu, Gaofei Chen, Zexin Zhang, Meixing He, Hongyi Li and Fenggen Yan
    Citation: BMC Medical Genomics 2023 16:138
  7. Glycosylation involved in various biological function, aberrant glycosylation plays an important role in cancer development and progression. Glycosyltransferase 8 domain containing 1 (GLT8D1) and GLT8D2, as me...

    Authors: Huimei Xu, Ke Huang, Yimin Lin, Hang Gong, Xueni Ma and Dekui Zhang
    Citation: BMC Medical Genomics 2023 16:123

    The Correction to this article has been published in BMC Medical Genomics 2023 16:136