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Big Data and Machine Learning in Bioinformatics and Medical Informatics

Call for papers

This collection welcomes 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 © NicoElNino (iStock)

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, ( or Piero Lo Monaco, the inhouse editor for BMC Medical Informatics and Decision Making ( if you would like more information before you submit. The deadline for submissions is December 31st, 2022.

To submit an article for consideration in BMC Bioinformatics, please click here.

To submit an article for consideration in BMC Medical Informatics and Decision Making, please click here.

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.