Advisory Board and Editors Bioinformatics
Christian Hoffmann
Assistant Professor of Microbiome and Nutrition, at the Dept of Food Sciences and Experimental Nutrition, at the University of São Paulo, Brazil, and a Research Fellow at the Laboratory of Applied Immunology, at the University of Brasilia. His experience is focused on the molecular ecology of microbial systems, especially host-associated microbial ecosystems. For the last 10 years, he has centered his research questions on the human gut microbiome, using both human studies as well as animal models. Key aspects of this research include the influence of the gut microbiome on health and disease, the modulation of the gut microbiome through diet and the immune system, especially through the use of unavailable carbohydrates.
Hongfei Hou
Hongfei Hou, a senior scientist at Pacific Northwest National Laboratory, has attained a Ph.D. in Computer Science from Washington State University. His research area includes cloud computing and machine learning.
Sun-Yuan Hsieh
Sun-Yuan Hsieh received the PhD degree in computer science from National Taiwan University, Taipei, Taiwan, in June 1998. In February 2002, he joined the Department of Computer Science and Information Engineering, National Cheng Kung University, and now he is a distinguished professor. His current research interests include design and analysis of algorithms, fault-tolerant computing, bioinformatics, parallel and distributed computing, and algorithmic graph theory.
Ming Hu
Dr. Hu is currently an Assistant Staff in the Department of Quantitative Health Sciences, Lerner Research Institute at Cleveland Clinic. He is also an Assistant Professor (non-tenure track) in the Department of Medicine at Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, an Associate Member of Molecular Oncology Program at Case Comprehensive Cancer Center, and a joint faculty member of Institute for Computational Biology at Case Western Reserve University School of Medicine. Dr. Hu received his B.S. degree in Statistics from University of Science and Technology of China in 2006 and Ph.D. degree in Biostatistics from University of Michigan in 2010. He was a postdoctoral fellow in Dr. Jun S. Liu’s group in Department of Statistics at Harvard University from 2010 to 2013. He jointed the Department of Population Health, Division of Biostatistics at New York University School of Medicine in 2013. In 2016, he moved to his current position in Cleveland Clinic. Dr. Hu has more than 10 years of experience in statistical modeling and statistical computing with applications in statistical genetics and genomics. Recently, his research is focused on genome-wide mapping and analysis of chromosome spatial organization. Dr. Hu has published more than 60 peer-reviewed research papers covering statistics, bioinformatics, statistical genetics and computational biology.
Jun Huan
Dr. Jun (Luke) Huan is a Professor in the Department of Electrical Engineering and Computer Science at the University of Kansas. He directs the Data Science and Computational Life Sciences Laboratory at KU Information and Telecommunication Technology Center (ITTC). He holds courtesy appointments at the KU Bioinformatics Center, the KU Bioengineering Program, and a visiting professorship from GlaxoSmithKline plc. Dr. Huan received his Ph.D. in Computer Science from the University of North Carolina.
Dr. Huan's research is recognized internationally. He was a recipient of the prestigious National Science Foundation Faculty Early Career Development Award in 2009. His group won the Best Student Paper Award at the IEEE International Conference on Data Mining in 2011 and the Best Paper Award (runner-up) at the ACM International Conference on Information and Knowledge Management in 2009. His work appeared at mass media including Science Daily, R&D magazine, and EurekAlert (sponsored by AAAS). Dr. Huan's research was supported by NSF, NIH, DoD, and the University of Kansas.
Starting January 2016, Dr. Huan serves as a Program Director in NSF/CISE/IIS and is on leave from KU.
Simon J Hubbard
I am a Professor in the Faculty of Biology, Medicine and Health at the University of Manchester. My scientific career has taken me from a PhD in Biochemistry at UCL, London, via the European Molecular Biology Laboratory, back to Manchester in the UK where I undertook a Wellcome Trust fellowship, before gaining a Lectureship in 1998. My research covers themes in computational and systems biology and bioinformatics. We apply computational approaches to the study of biological systems and molecules, and my particular areas of interests are broadly in the areas of protein and genome bioinformatics including quantitative proteomics, regulation of gene expression (and particularly translation from mRNA to protein), and general bioinformatics.
Jacob J Hughey
I’m an Assistant Professor of Biomedical Informatics and Biological Sciences at Vanderbilt University. My group's research is centered around developing and applying computational methods to large, noisy datasets in order to quantify, model, and understand dynamic biological systems. We are particularly interested in the mammalian circadian system.
Lilia M Iakoucheva
Assistant Professor in the Department of Psychiatry at the University of California San Diego, USA. Currently investigates the molecular basis of neurodevelopmental and psychiatric diseases using genomic and systems biology approaches.
Dr. Iakoucheva’s research focuses on understanding of the molecular basis of autism and schizophrenia using systems biology approaches. The aim is to discover functional protein interaction networks connecting seemingly unrelated candidate genes for psychiatric diseases. Dr. Iakoucheva’s lab is building comprehensive protein-protein interaction networks for autism and schizophrenia candidate genes and their splicing isoforms. In addition, they are integrating gene expression data with our experimentally derived networks to understand spatio-temporal dynamics of protein interactions in the brain. Their immediate goal is to investigate perturbations of the disease networks by the Copy Number Variants (CNVs) and protein-damaging Single Nucleotide Variants (SNVs) identified in the patients using the Whole Exome Sequencing (WES) studies. Additionally, they are interested in interpreting non-coding genetic variation with relevance to psychiatric diseases. They are investigating functional impact of UTR, promoter and splice site mutations identified in the Whole Genome Sequencing (WGS) studies of autism and schizophrenia using in vitro cellular systems.
Syed Anas Imtiaz
I am a researcher in wearable medical devices working on creating new technologies for the monitoring and diagnosis if neurological, neurodevelopmental and sleep disorders. My research focuses on developing new biomedical signal processing methods, algorithms and mixed-signal circuit design for wearable systems, low power digital circuits for medical applications and embedded systems design. I am a Research Fellow at Imperial College London where I am developing new technologies for long-term monitoring, management and diagnosis of COPD, sleep disorders, epilepsy, and autism. I am also the Head of Engineering at Acurable leading development and at-scale manufacturing of a wearable medical device and its accompanying smartphone applications for the diagnosis of respiratory disorders.
Mohammad Irfan
Dr. Mohammad Irfan is a plant biologist having research interests in abiotic stress biology of crop plants particularly horticultural crops. During his doctoral and postdoctoral projects, he studied the fruit quality traits affected by abiotic stresses. In his current projects, he investigates the molecular mechanism underlying plant-specialized metabolic pathways and biosynthesis of high-value phytochemicals, such as anthocyanins and carotenoids of horticultural crops under abiotic stresses using transcriptomics, metabolomics, glycomic and functional genomic approaches.
Jose MG Izarzugaza
Associate Professor at the Technical University of Denmark (DTU). As a senior scientist in Prof. Søren Brunak's group at the Center for Biological Sequence Analysis (CBS), I have a profound interest in different aspects of next generation sequencing (NGS) data analysis. This covers a broad spectrum of scenarios and applications. Actively involved in the Genome Denmark initiative, with two main goals: to assemble and annotate the first draft of the Danish reference genome and to identify viruses driving cancer. Other current projects include the prediction of the pathogenicity of mutations in the protein kinase superfamily for the TCGA/ICGC Pancancer initiative.
Christof M Jäger
I am a computational chemist and data scientist and group leader at AstraZeneca. My research activities all share the motivation to bring the power of computational chemistry to new chemical problems in pharmaceutical research and beyond, to fundamentally understand properties and functions of organic molecules, to reveal hidden chemical questions and to promote solutions for chemical challenges and focus on the development and application of efficient and transferable computational techniques and workflows.
Past and present research involved multi-disciplinary research in the areas of reactivity prediction, catalysis, biotechnology, bio-organic, colloid, and radical chemistry, molecular self-assembly and supramolecular chemistry, ion effects, and molecular electronics in organic electronic devices.
Following my undergraduate studies of Molecular Science I received my PhD in Computational Chemistry from the University of Erlangen-Nuernberg, Germany in 2010. I then worked as a Postdoc for the Cluster of Excellence Engineering Advanced Materials (EAM) until 2014, when I joined the Sustainable Process Technology (SPT) Research Group in in the Faculty of Engineering of the University of Nottingham, first as an EU and UoN funded fellow, then as Assistant Professor in Biotechnology and Computational Chemistry. In September 2022 I joined AstraZeneca in Gothenburg / Sweden to work in predictive computational chemistry and data science within the Pharmaceutical Science department.