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Big Data and Machine Learning in Bioinformatics and Medical Informatics

This collection comprises articles presenting novel developments in artificial intelligence, big data analysis and cloud computing in both biology and medicine, and their applications to the analysis of high-throughput biological and medical data, including image and microbiome data, as well methodologies and tools to manage complex electronic health information and records.New Content Item

This includes, but is not restricted to, the design, implementation, use and evaluation of artificial intelligence and machine learning methods, software packages and novel webservers that allow big data analysis.

Please email Alison Cuff, the inhouse editor for BMC Bioinformatics, (alison.cuff@biomedcentral.com) or Piero Lo Monaco, the inhouse editor for BMC Medical Informatics and Decision Making (piero.lomonaco@springernature.com) if you would like more information about this collection.



Meet the Guest Editors

Frank Eisenhaber (BMC Bioinformatics)

New Content ItemFrank Eisenhaber studied at the Humboldt-University in Berlin, at the Pirogov Medical University in Moscow and received the PhD in molecular biology from the Engelhardt Institute of Molecular Biology in Moscow 1988. He worked at the EMBL in Heidelberg (1991-1999), at the Institute of Molecular Pathology (IMP) in Vienna (1999-2007) and at A*STAR Singapore (since 2007). During 2007-2020, he was the Executive Director of the Bioinformatics Institute of A*STAR. Frank Eisenhaber’s research interest is focused on the discovery of new biomolecular mechanisms from biological and medical data and the functional characterization of yet uncharacterized genes and pathways. Frank Eisenhaber is one of the scientists credited with the discovery of the SET domain methyltransferases, ATGL, kleisins, many new protein domain functions (for example in the GPI lipid anchor biosynthsis pathway), with the development of accurate prediction tools for posttranslational modifications and subcellular localizations and with algorithms for omics data analysis. 

Somali Chaterji (BMC Bioinformatics)

New Content ItemSomali Chaterji (pronounced shoh-MAH-lee CHA-ter-jee) is an Assistant Professor in the Department of Agricultural and Biological Engineering at Purdue University, where she leads the Innovatory for Cells and Neural Machines [ICAN]. ICAN specializes in developing algorithms and statistical models for IoT and edge computing on the one hand and genome engineering on the other. ICAN is driven to learn and inter-change tools between these two thrusts with the goal to create new algorithms to understand the genome of living cells, on the one hand, and to enable IoT sensors to perceive and actuate on the other. 

Khanh N.Q. Le (BMC Bioinformatics)

New Content ItemKhanh N.Q. Le is an assistant professor with the College of Medicine, Taipei Medical University (TMU), Taiwan. Prior to joining TMU, he was a Research Fellow at the School of Humanities, Nanyang Technological University (NTU), Singapore. His research interests are to apply AI (machine learning, deep learning, and natural language processing) in multidisciplinary studies, especially Bioinformatics, Computational Biology, Biomedical Informatics, and Radiomics.

Placide Poba-Nzaou (BMC Medical Informatics and Decision Making)

New Content ItemDr. Placide Poba-Nzaou is a Professor of Information Systems and Human Resources at the University of Quebec in Montreal. His research interests include Digital Health, Information Systems and Human Resources.



  1. Given a genome-scale metabolic model (GEM) of a microorganism and criteria for optimization, flux balance analysis (FBA) predicts the optimal growth rate and its corresponding flux distribution for a specific ...

    Authors: Clémence Joseph, Haris Zafeiropoulos, Kristel Bernaerts and Karoline Faust
    Citation: BMC Bioinformatics 2024 25:36
  2. Graph embedding techniques are using deep learning algorithms in data analysis to solve problems of such as node classification, link prediction, community detection, and visualization. Although typically used...

    Authors: Edwin Alvarez-Mamani, Reinhard Dechant, César A. Beltran-Castañón and Alfredo J. Ibáñez
    Citation: BMC Bioinformatics 2024 25:1
  3. Point-of-care lung ultrasound (LUS) allows real-time patient scanning to help diagnose pleural effusion (PE) and plan further investigation and treatment. LUS typically requires training and experience from th...

    Authors: Damjan Vukovic, Andrew Wang, Maria Antico, Marian Steffens, Igor Ruvinov, Ruud JG van Sloun, David Canty, Alistair Royse, Colin Royse, Kavi Haji, Jason Dowling, Girija Chetty and Davide Fontanarosa
    Citation: BMC Medical Informatics and Decision Making 2023 23:274
  4. Depression is one of the most significant health conditions in personal, social, and economic impact. The aim of this review is to summarize existing literature in which machine learning methods have been used...

    Authors: David Nickson, Caroline Meyer, Lukasz Walasek and Carla Toro
    Citation: BMC Medical Informatics and Decision Making 2023 23:271
  5. The widespread adoption of telehealth services necessitates accurate online department selection based on patient medical records, a task requiring significant medical knowledge. Incorrect triage results in co...

    Authors: Jinming Shi, Ming Ye, Haotian Chen, Yaoen Lu, Zhongke Tan, Zhaohan Fan and Jie Zhao
    Citation: BMC Medical Informatics and Decision Making 2023 23:269
  6. Identifying variants associated with complex traits is a challenging task in genetic association studies due to linkage disequilibrium (LD) between genetic variants and population stratification, unrelated to ...

    Authors: Aritra Bose, Myson Burch, Agniva Chowdhury, Peristera Paschou and Petros Drineas
    Citation: BMC Bioinformatics 2023 24:411
  7. Predicting medications is a crucial task in intelligent healthcare systems, aiding doctors in making informed decisions based on electronic medical records (EMR). However, medication prediction faces challenge...

    Authors: Yang An, Haocheng Tang, Bo Jin, Yi Xu and Xiaopeng Wei
    Citation: BMC Medical Informatics and Decision Making 2023 23:243
  8. The COVID-19 patients in the convalescent stage noticeably have pulmonary diffusing capacity impairment (PDCI). The pulmonary diffusing capacity is a frequently-used indicator of the COVID-19 survivors’ progno...

    Authors: Fu-qiang Ma, Cong He, Hao-ran Yang, Zuo-wei Hu, He-rong Mao, Cun-yu Fan, Yu Qi, Ji-xian Zhang and Bo Xu
    Citation: BMC Medical Informatics and Decision Making 2023 23:169
  9. Quantitative analysis of neurite growth and morphology is essential for understanding the determinants of neural development and regeneration, however, it is complicated by the labor-intensive process of measu...

    Authors: Joseph T. Vecchi, Sean Mullan, Josue A. Lopez, Madeline Rhomberg, Annamarie Yamamoto, Annabelle Hallam, Amy Lee, Milan Sonka and Marlan R. Hansen
    Citation: BMC Bioinformatics 2023 24:320
  10. Monitoring blood pressure and peripheral capillary oxygen saturation plays a crucial role in healthcare management for patients with chronic diseases, especially hypertension and vascular disease. However, cur...

    Authors: Yan Chu, Kaichen Tang, Yu-Chun Hsu, Tongtong Huang, Dulin Wang, Wentao Li, Sean I. Savitz, Xiaoqian Jiang and Shayan Shams
    Citation: BMC Medical Informatics and Decision Making 2023 23:131
  11. Today, clinical decision support systems based on artificial intelligence can significantly help physicians in the correct diagnosis and quick rapid treatment of endophthalmitis as the most important cause of ...

    Authors: Mahdi Shaeri, Nasser Shoeibi, Seyedeh Maryam Hosseini, Fatemeh Rangraze Jeddi, Razieh Farrahi, Ehsan Nabovati and Azam Salehzadeh
    Citation: BMC Medical Informatics and Decision Making 2023 23:130
  12. Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathwa...

    Authors: Alyssa N. Obermayer, Darwin Chang, Gabrielle Nobles, Mingxiang Teng, Aik-Choon Tan, Xuefeng Wang, Y. Ann Chen, Steven Eschrich, Paulo C. Rodriguez, G. Daniel Grass, Soheil Meshinchi, Ahmad Tarhini, Dung-tsa Chen and Timothy I. Shaw
    Citation: BMC Bioinformatics 2023 24:266
  13. A nonhomogeneous dynamic Bayesian network model, which combines the dynamic Bayesian network and the multi-change point process, solves the limitations of the dynamic Bayesian network in modeling non-stationar...

    Authors: Jiayao Zhang, Chunling Hu and Qianqian Zhang
    Citation: BMC Bioinformatics 2023 24:264
  14. Lung cancer is a malignant tumour, and early diagnosis has been shown to improve the survival rate of lung cancer patients. In this study, we assessed the use of plasma metabolites as biomarkers for lung cance...

    Authors: Xiuliang Guan, Yue Du, Rufei Ma, Nan Teng, Shu Ou, Hui Zhao and Xiaofeng Li
    Citation: BMC Medical Informatics and Decision Making 2023 23:107
  15. Long non-coding RNA (lncRNA) closely associates with numerous biological processes, and with many diseases. Therefore, lncRNA-disease association prediction helps obtain relevant biological information and und...

    Authors: Hua Zhong, Jing Luo, Lin Tang, Shicheng Liao, Zhonghao Lu, Guoliang Lin, Robert W. Murphy and Lin Liu
    Citation: BMC Bioinformatics 2023 24:234
  16. Clinical studies have shown that miRNAs are closely related to human health. The study of potential associations between miRNAs and diseases will contribute to a profound understanding of the mechanism of dise...

    Authors: Min Chen, Yingwei Deng, Zejun Li, Yifan Ye and Ziyi He
    Citation: BMC Bioinformatics 2023 24:229
  17. Epilepsy is a neurological disorder that is usually detected by electroencephalogram (EEG) signals. Since manual examination of epilepsy seizures is a laborious and time-consuming process, lots of automatic ep...

    Authors: Wenna Chen, Yixing Wang, Yuhao Ren, Hongwei Jiang, Ganqin Du, Jincan Zhang and Jinghua Li
    Citation: BMC Medical Informatics and Decision Making 2023 23:96
  18. Accurately classifying complex diseases is crucial for diagnosis and personalized treatment. Integrating multi-omics data has been demonstrated to enhance the accuracy of analyzing and classifying complex dise...

    Authors: Yating Zhong, Yuzhong Peng, Yanmei Lin, Dingjia Chen, Hao Zhang, Wen Zheng, Yuanyuan Chen and Changliang Wu
    Citation: BMC Medical Informatics and Decision Making 2023 23:82
  19. The identification of disease-related genes is of great significance for the diagnosis and treatment of human disease. Most studies have focused on developing efficient and accurate computational methods to pr...

    Authors: Linlin Zhang, Dianrong Lu, Xuehua Bi, Kai Zhao, Guanglei Yu and Na Quan
    Citation: BMC Bioinformatics 2023 24:162
  20. Intraoperative blood transfusion is associated with adverse events. We aimed to establish a machine learning model to predict the probability of intraoperative blood transfusion during intracranial aneurysm su...

    Authors: Shugen Xiao, Fan Liu, Liyuan Yu, Xiaopei Li, Xihong Ye and Xingrui Gong
    Citation: BMC Medical Informatics and Decision Making 2023 23:71
  21. Bronchopulmonary Dysplasia (BPD) has a high incidence and affects the health of preterm infants. Cuproptosis is a novel form of cell death, but its mechanism of action in the disease is not yet clear. Machine ...

    Authors: Mingxuan Jia, Jieyi Li, Jingying Zhang, Ningjing Wei, Yating Yin, Hui Chen, Shixing Yan and Yong Wang
    Citation: BMC Medical Informatics and Decision Making 2023 23:69
  22. Identification of hot spots in protein–DNA binding interfaces is extremely important for understanding the underlying mechanisms of protein–DNA interactions and drug design. Since experimental methods for iden...

    Authors: Yu Sun, Hongwei Wu, Zhengrong Xu, Zhenyu Yue and Ke Li
    Citation: BMC Bioinformatics 2023 24:129
  23. Using visual, biological, and electronic health records data as the sole input source, pretrained convolutional neural networks and conventional machine learning methods have been heavily employed for the iden...

    Authors: Mpho Mokoatle, Vukosi Marivate, Darlington Mapiye, Riana Bornman and Vanessa. M. Hayes
    Citation: BMC Bioinformatics 2023 24:112
  24. Drug‒drug interactions (DDIs) are reactions between two or more drugs, i.e., possible situations that occur when two or more drugs are used simultaneously. DDIs act as an important link in both drug developmen...

    Authors: Zihao Yang, Kuiyuan Tong, Shiyu Jin, Shiyan Wang, Chao Yang and Feng Jiang
    Citation: BMC Bioinformatics 2023 24:110
  25. Although research on non-coding RNAs (ncRNAs) is a hot topic in life sciences, the functions of numerous ncRNAs remain unclear. In recent years, researchers have found that ncRNAs of the same family have simil...

    Authors: Kai Chen, Xiaodong Zhu, Jiahao Wang, Lei Hao, Zhen Liu and Yuanning Liu
    Citation: BMC Bioinformatics 2023 24:68