ICBRA 2023

Keynote Speakers

Prof. Huiru Zheng

Ulster University, UK

Prof. Huiru Zheng is a Professor of Computer Science with the School of Computing at Ulster University. Within her broad interests in machine learning, bioinformatics, and biomedical informatics, Prof. Zheng has particular research interests and expertise in integrative data analysis. Her research has been supported by a number of funding bodies, such as the European Commission, COST Action, UK Research Council, Innovate UK, Invest NI, Depart of Economy, and industries. She has co-authored over 250+ research papers and is currently leading the bioinformatics research in the Artificial Intelligence Research Centre at Ulster. Prof. Zheng is a Senior Member of IEEE. She serves on the editorial board of several international journals and served as co-chairs at IEEE International Conference on Bioinformatics and Biomedicine (BIBM) in 2014, 2018, and the Collaborative European Research Conference (CERC) in 2020.

Speech Title: "Towards AI-empowered Biomedicine and Digital Health"

Abstract: Advances in biology and medical sciences have led to an explosive growth of biomedical data, which has great potential to provide profound insights into a number of important areas including health care and medical science. In the meantime,population ageing has become a global phenomenon and traditional health systems are under pressure from rising costs, and growing consumer expectations in caring for their elderly. With the rapid advance of AI technologies, it is increasingly possible to drive early interventions to better prevention, prediction, diagnosis, treatment and management of diseases and health conditions. In this talk, an overview of recent years' research will be presented, with a discussion of opportunities and challenges in adopting AI in real applications.

Prof. Ralf Hofestädt

University Bielefeld, Germany

Ralf Hofestädt studied Computer Science and Bioinformatics at the University of Bonn. He finished his PhD 1990 (University Bonn) and his Habilitation (Applied Computer Science and Bioinformatics) 1995 at the University of Koblenz. From 1996 to 2001 he was Professor for Applied Computer Science at the University of Magdeburg. Since 2001 he is Professor for Bioinformatics and Medical Informatics at the University Bielefeld. His research interests are Databases and database integration; Datawarehousing, Modeling and Simulation of metabolic processes, Drug Pointing, Knowledge Representation, Medical Diagnosis Systems, Parallel Computing, GRID Computing, Detection of Metabolic Diseases.

Speech Title: "Computation of Drug Drug Interactions and Side Effects based on Molecular Data"

Abstract: Drug side effects and interactions are one of the most common causes of death in industrialized Western countries. Nowadays, different information systems are available for the identification of such effects based on clinical studies. However molecular databases are available which can give more information about such effects. Based on this idea we implemented different tools which analyze drug interactions and side effects based on freely available molecular databases. The systems are able to analyze single and combined drug-drug interactions, drug-molecule interactions as well as single and cumulative side effects.

Invited Speakers

Prof. Taesung Park

Seoul National University, South Korea

Prof. Taesung Park received his B.S. and M.S. degrees in Statistics from Seoul National University (SNU), Korea in 1984 and 1986, respectively and received his Ph.D. degree in Biostatistics from the University of Michigan in 1990. From Aug. 1991 to Aug. 1992, he worked as a visiting scientist at the NIH, USA. From Sep. 2002 to Aug. 2003, he was a visiting professor at the University of Pittsburgh. From Sep. 2009 to Aug. 2010, he was a visiting professor in Department of Biostatistics at the University of Washington. From Sep. 1999 to Sep. 2001, he worked as an associate professor in Department of Statistics at SNU. Since Oct. 2001 he worked as a professor and currently the Director of the Bioinformatics and Biostatistics Lab. at SNU. He served as the chair of the bioinformatics Program from Apr. 2005 to Mar. 2008, and the chair of Department of Statistics of SNU from Sep. 2007 and Aug. 2009. He has served editorial board members and associate editors for the international journals including Genetic Epidemiology, Computational Statistics and Data Analysis, Biometrical Journal, and International journal of Data Mining and Bioinformatics. His research areas include microarray data analysis, GWAS, gene-gene interaction analysis, and statistical genetics.

Speech Title: "Statistical Analysis of Longitudinal Microbiome Data"

Abstract: High-throughput technologies allow a new era of metagenomics studies to explore microbial communities sampled directly. Main goal of human microbial studies is to detect associations between microbiota and phenotypes. It is well known that microbiome composition varies across time points. Analysis of such longitudinal microbiome data has several challenging issues to overcome such as correlation between counts, varying compositional structures, various total sequence reads per samples, over-dispersion and zero-inflation. Although several methods have been developed to handle these characteristics, none of the approaches have resolved these challenges well. While taking these challenges, we propose a novel statistical approach to identifying differentially abundant markers associated with the phenotypes of interest. The proposed method is based on the generalized estimating equations model and has an advantage of handling multiple markers easily. Compared to existing methods, the proposed approach show better performance in empirical studies including simulations and real data studies. The proposed approach is expected to be a useful tool to the analysis of longitudinal microbiome data.