Advisory Board and Editors Computational Biology
Juro Gregan
- associate professor, Dept. of Genetics, Comenius University in Bratislava, Slovakia
- group leader, MFPL, Dept. of Chromosome Biology, University of Vienna, Vienna, Austria
- postdoctoral researcher, IMP (Research Institute of Molecular Pathology), Vienna, Austria (K. Nasmyth lab)
- postdoctoral researcher, Dept. of Zoology, Univ. of Oxford, Oxford, UK (S. Kearsey lab)
- PhD study, Dept.of Microbiology and Genetics, Univ. of Vienna, Vienna, Austria (R. Schweyen lab)
Sam Griffiths-Jones
Professor of Computational Biology, Faculty of Biology, Medicine and Health, University of Manchester. Manages the miRBase database of microRNA sequences. Founded the Rfam RNA families database. Interested in RNA structure, function and evolution.
Arthur Gruber
Prof. Arthur Gruber received his Bachelor’s in Veterinary Medicine, PhD in Biochemistry, Associate degree in Animal Pathology from the University of São Paulo. He is Associate Professor at the Institute of Biomedical Sciences, University of São Paulo, affiliated member, European Viral Bioinformatics Center, and member of the directory board, Brazilian Association for Bioinformatics and Computational Biology (AB3C). Prof. Gruber is PI of the Viral Genomics and Bioinformatics research group, developing bioinformatics methods and tools for viral detection, classification and discovery.
Marcin Maciej Grynberg
Assistant Professor in The Institute of Biochemistry and Biophysics Polish Academy of Sciences, Warsaw, Poland. Graduate from The University of Warsaw. Former post-doc at The Burnham Institute, La Jolla, CA. Co-founder of the social scientist movement Citizens of Academia.
Fanglin Guan
Prof. Fanglin Guan is Dean at Xi'an Jiaotong University. He is engaged in the integrated biological research of complex diseases, including tumor microenvironment and novel immunotherapeutic modalities, and research on the mechanisms and medical applications related to tumor cell vaccines, especially for the exploration of the mechanism of determining the biomarkers of complex diseases.
Michael Hallett
I am primarily interested in computational biology and bioinformatic approaches to biomarkers based on multi-variate, multi-modal gene signatures, especially in the context of cancer.
Jin-Kao Hao
Distinguished Professor of Computer Science, Université d'Angers (France); Senior Fellow of the French "Institut Universitaire de France", Working on computational methods for large scale and complex combinatorial optimization problems.
Martin Hartmann
Senior Researcher at ETH Zurich with strong interests in microbial ecology, molecular biology, bioinformatics and statistics.
Catherine F Higham
Dr. Catherine Higham works at the interface between mathematics, deep learning and experimental science. Her first degree was in mathematics and her PhD involved mathematical modelling and statistical inference applied to somatic genetic mutations arising in myotonic dystrophy and Huntington's disease. Subsequent areas of research include Bayesian inference in nonlinear ODEs and the circadian clock. Currently, she is developing and applying deep learning techniques to inverse problems arising in novel quantum imaging technologies such as the single pixel camera and lidar. She also has an interest in quantum machine learning and framing problems for quantum annealing.
Noriko F Hiroi
Noriko Hiroi is Assistant Professor of the Department of Biosciences and Informatics, Keio University. She started to develop her career in Molecular Biology and Biochemistry, and currently works in Systems Biology and Quantitative Biology area. Her research interest includes in vivo oriented modelling, molecular mechanisms of higher-functions of central nerve systems, microfluidics technology and optical technologies and informatics for bioimaging.
Harry Hochheiser
My research has covered a range of topics, including human-computer interaction, information visualization, bioinformatics, universal usability, security, privacy, and public policy implications of computing systems. I am currently working on a variety of NIH-funded projects, including areas such as bioinformatics research portals, visualization for review of chart records, and tools for aiding the discovery of animal models of human diseases.
Michael M. Hoffman
Michael Hoffman creates predictive computational models to understand interactions between genome, epigenome, and phenotype in human cancers. His influential machine learning approaches have reshaped researchers' analysis of gene regulation. These approaches include the genome annotation method Segway, which enables simple interpretation of multivariate genomic data. He is a Senior Scientist in and Chair of the Computational Biology and Medicine Program, Princess Margaret Cancer Centre and Associate Professor in the Departments of Medical Biophysics and Computer Science, University of Toronto. He was named a CIHR New Investigator and has received several awards for his academic work, including the NIH K99/R00 Pathway to Independence Award, and the Ontario Early Researcher Award.