Advisory Board and Editors Computational Biology
Xing Li
Dr. Xing Li is an Assistant Professor and Associate Consultant in the Division of Biomedical Statistics and Informatics, Department of Health Science Research at Mayo Clinic - voted the best hospital by U.S. News & World Report. Dr. Li completed his PhD in Bioinformatics from The University of Michigan at Ann Arbor, Michigan, USA. Dr. Li also holds a Masters Degree in Biochemistry and Molecular Biology and Bachelors Degree in Microbiology. Dr. Li’s research interests focus on machine learning, bioinformatics, and statistical data mining in large scale data in biomedical research, such as next generation sequencing data (whole genome sequencing, RNA-seq, microarray data), in the file. He has published more than 20 peer-reviewed papers in reputable journals and book chapters in the fields of Bioinformatics and Biostatistics, cancer research, cardiovascular disease, embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) research, and human genomics, genetics and development, and Microbiology. Dr. Li’s publications have been highlighted as Journal Cover Stories, Journal Featured Articles, Highlights Section Papers, Must Read by Faculty 1000, and ESC & iPSC News, etc. Dr. Li has been developing data analysis tools, such as RCircle and PCA3d, etc. Dr. Li is also a member of American Association for Cancer Research (AACR), International Society for Computational Biology (ISCB), American Statistics Association (ASA) and American Heart Association (AHA).
Jingyi Jessica Li
I am an Assistant Professor in the Department of Statistics and Department of Human Genetics at University of California, Los Angeles. I am also a faculty member in the Interdepartmental Ph.D. Program in Bioinformatics and a member in the Jonsson Comprehensive Cancer Center (JCCC) Gene Regulation Research Program Area. Prior to joining UCLA, I obtained my Ph.D. degree from the Interdepartmental Group in Biostatistics at University of California, Berkeley, where I worked with Profs Peter J. Bickel and Haiyan Huang. I received my B.S. (summa cum laude) from Department of Biological Sciences and Technology at Tsinghua University, China in 2007.
Chun Liang
Professor in Bioinformatics, Biology Department, Miami University, Ohio, USA
Qi Liu
Research Assistant Professor of Biomedical Informatics, Vanderbilt University
Pengcheng Liu
Pengcheng Liu is a member of IEEE, IEEE Robotics and Automation Society (RAS), IEEE Control Systems Society (CSS) and International Federation of Automatic Control (IFAC). He is also a member of the IEEE Technical Committee on Bio Robotics, Soft Robotics, Robot Learning, and Safety, Security and Rescue Robotics. Dr Liu is an Associate Editor of IEEE Access, PeerJ Computer Science, and he received the Global Peer Review Awards from Web of Science in 2019, and the Outstanding Contribution Awards from Elsevier in 2017. He has published over 70 papers on flagship journals and conferences. He was nominated as a regular Funding/Grants reviewer for EPSRC, NIHR and NSFC and he has been leading and involving in several research projects and grants, including EPSRC, Newton Fund, Innovate UK, Horizon 2020, Erasmus Mundus, FP7-PEOPLE, NSFC, etc. He serves as reviewers for over 30 flagship journals and conferences in robotics, AI and control. His research interests include robotics, machine learning, automatic control and optimization.
Tao Liu
I am an Assistant professor at Department of Biochemistry, State University of New York at Buffalo. I have expertise and extensive experience with developing and applying computational approaches for transcriptional and epigenetics regulation studies. As a postdoctoral fellow at Dana-Farber Cancer Institute, I developed widely used open-source algorithms, including MACS (cited over 3,200 times according to Google Scholar) to analyze ChIP-seq data, and an integrative platform for comprehensive analyses on cis-regulatory elements (http://cistrome.org/ap), which has over 3,000 users. I was a member of the Data Analysis Center and Analysis Working Group of the ENCODE and modENCODE consortium and was involved in deciphering functional elements through analyzing high-throughput profiles of chromatin factors and in comparing chromatin features between fly, worm and human genome. I have actively participated in the development of ChIP-seq guidelines for the broad scientific communities. My laboratory at University at Buffalo is focused on studying transcriptional and epigenetic regulatory mechanisms, and the influence of the genetic variations at regulatory elements.
Nicholas J Loman
Nick works as an Independent Research Fellow in the Institute for Microbiology and Infection at the University of Birmingham, sponsored by an MRC Fellowship in Biomedical Informatics. His research explores the use of cutting-edge genomics and metagenomics approaches to the diagnosis, treatment and surveillance of infectious disease. Nick has so far used high-throughput sequencing to investigate outbreaks of important pathogens such as Pseudomonas aeruginosa,Acinetobacter baumannii and Shiga-toxin producing Escherichia coli. His current work focuses on the application of novel sequencing technologies such as the Oxford Nanopore for genome diagnosis and epidemiology of important pathogens, including most recently real-time surveillance of the Ebola outbreak in West Africa. A more general aim is to develop bioinformatics tools to aid the interpretation of genome and metagenome-scale data in routine clinical practice in collaboration.
Marta Lovino
Dr. Marta Lovino is an assistant professor with a time contract at the University of Modena and Reggio Emilia, since 2023. She obtained her Ph.D. in Computer and Control Engineering with honors from Politecnico di Torino in 2021 and joined the AImage lab group as a Postdoctoral Research Fellow.
Dr. Lovino's primary research interests include cancer prognosis prediction, gene expression analysis, miRNA target prediction, gene regulatory networks, gene fusions, and multi-omics data integration. With a particular focus on leveraging artificial intelligence (AI) in the field of genetics to improve the understanding of cancer biology and enhance patient care.
Gerton Lunter
My group is interested in investigating the processes of evolution and biology using computational methods. We apply machine learning methods (HMMs, Bayesian statistics, particle filters, deep learning) to large data sets to study for example human demographic history or non-coding functional elements in the genome.
Weijun Luo
Faculty member at the Department of Bioinformatics and Genomics, College of Computing and Informatics, UNC Charlotte.
Research areas include: High throughput genomic data analysis Computational method development and implementation Systems biology on complex diseases and processes Biomedical informatics and computing Personal genome and personalized medicine
Emiliano Maiani
Emiliano Maiani earned his MS and PhD in Molecular and Cellular Biology at the University of Rome “Tor Vergata”, Rome, Italy. In 2013, he joined the Cell Stress and Survival laboratory headed by prof. Francesco Cecconi at the Danish Cancer Society Research Center (DCRC), Copenhagen, Denmark. At the end of 2017, he moved for a second postdoc at the Computational Biology Laboratory headed by Elena Papaleo at the DCRC, Copenhagen. In this period, he expanded his knowledge to computational and structural biology. His research is focused on cancer biology and in particular in autophagy and DNA damage response pathways.
Kathleen Marchal
Associate Professor Bioinformatics, Department of Bioinformatics and Plant Biotechnology, Ghent University, Belgium; VIB department Plant Systems Biology. Associate Professor Bioinformatics, Department of Microbial and Molecular Plant Sciences, KU Leuven, Belgium. Recipient of the DSM award 2000. Recipient of the Biannual Siemens award 2002. Associate editor of BMC Release notes, BMC Bioinformatics, Journal of Integrative Omics