Advisory Board and Editors Bioinformatics
Ryan Hernandez
Assistant Professor at the University of California San Francisco in the Department of Bioengineering and Therapeutic Sciences, the Institute for Quantitative Biosciences (QB3), and the Institute for Human Genetics.
Grant A Hill-Cawthorne
Senior Lecturer in Communicable Disease Epidemiology, School of Public Health, University of Sydney; Public Health Lead and Node Leader for Mass Gathering Medicine, Marie Bashir Institute, University of Sydney; Honorary Life Fellow, St Andrew's College within the University of Sydney; Senior Member and College Research Associate, Wolfson College, University of Cambridge
Biographical details:
I studied medicine in Cambridge and during my junior doctor years was very interested in both neurology and infectious diseases. Clinically I specialised in medical microbiology, keeping a particular interest in neurological infections. For the past 3 years I have been in Saudi Arabia developing a pathogen genomics laboratory where I have gained first-hand experience of second generation sequencing and bioinformatics.
Research interests:
Infectious diseases and medical microbiology are undergoing the most significant shift since PCR was introduced. By the end of this decade, sequencing will have become the main option when investigating any outbreak or infection. I study the interface between genomics as a pure science and its translation into clinical and public health benefits.
At present I am examining the worldwide genomics of tuberculosis, the use of sequencing to characterise MRSA strains and the genomic variations in BCG vaccine strains used around the globe.
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.
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.
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.