Journal of Computational Systems Biology

Dr. Haiting Ji is an Associate Chief Physician at the Eye, Ear, Nose and Throat Hospital affiliated with Fudan University. She holds a combined M.D.-Ph.D. degree from Fudan University Shanghai Medical College and completed joint doctoral training at Emory University (USA). She has also been a Harvard Medical School Program Scholar under the Harvard–Fudan T2T Faculty Development Program. Dr. Ji serves as: Committee Member, Otorhinolaryngology Branch, Chinese Society of Integrative Medicine, International Committee Member (China Representative), Association for Research in Otolaryngology (ARO), USA, Lecturer, “Youth Faculty Lecturer Group,” Fudan University. Her research focuses on genetic hearing loss, molecular otology, and auditory gene therapy. She has led four funded research projects, published eight peer-reviewed papers as first or corresponding author, and actively engages in public science communication and clinical education.

Research: genetic hearing loss, molecular otology, and auditory gene therapy

Dr. Yu Shyr received his PhD in biostatistics from University of Michigan (Ann Arbor) in 1994 and subsequently joined the faculty at Vanderbilt University School of Medicine. At Vanderbilt, he has collaborated on numerous research projects; assisted investigators in developing clinical research protocols; collaborated on multiple grants funded through external peer-reviewed mechanisms; and developed biostatistical and bioinformatic methodologies for clinical trial design, high-dimensional data preprocessing, estimating relative potency in a parallel line bioassay, and other statistical and bioinformatic approaches, published in journals such as Statistics in Medicine, Bioinformatics, Clinical Trials, Computational Statistics and Data Analysis, BMC Bioinformatics, and Journal of Bioinformatics and Computational Biology in the last three years.

Research: Major Research Areas Biostatistics Bioinformatics Biomedical Informatics   Current Research Dr. Shyr’s current research interests lie in developing and analyzing predictive models of the statistical relationships between multiple-variable protein and next generation sequencing data and clinical endpoints using both supervised and unsupervised classification and pattern recognition approaches, which focus on analyses of gene expression array and protein expression profile data to identify the molecular “fingerprint” of different types of cancers.

Research: Moecular genetics Molecular mechanisms of mutation Structural conformations of DNA and chromatin

Research: Modeling and assessing diaphragm mechanics: Investigation of the determinants of diaphragm muscle mechanics and kinematics, including the unique mechanical properties of the diaphragm and structural issues such as the geodesic properties of diaphragm muscle fibers. Current works describe numerous approaches to dealing with these determinants, including measuring diaphragm curvature, displacement and muscle shortening, as well as computational modeling of the effect of muscle anisotropic properties on diaphragm shape. This work is established in collaboration with Dr. Rolf Hubmayr at Mayo Clinic. Modeling and assessing diaphragm function in disease: We have recently been interested in assessing diaphragm function in chronic obstructive pulmonary disease (COPD) patients. In particular, we are interested in assessing the effect of body mass index (BMI) on a realistic model of diaphragm structure in subjects with airflow obstruction. In addition, we hope to examine how body mass index affects the kinematics of the diaphragm and its interaction with the rib cage in subjects with airflow obstruction. Furthermore, we will determine the contrasting effects of lung volume reduction surgery (LVRS) and medical therapy on diaphragm and chest wall remodeling and whether BMI is a factor in mediating such effects in severe COPD subjects. This work is established in collaboration with Drs. Hanania and Sharafkhaneh, clinical investigators at Baylor College of Medicine as well as Dr. Eric Hoffman of Iowa University. Those collaborators are principal investigators of the ongoing COPDGene National Trial. Assessment of respiratory muscle function in mouse models of muscular dystrophy: A complex rearrangement mutation in the mouse titin gene leads to an in-frame 83-amino acid deletion in the N2A region of titin. Autosomal recessive inheritance of the titin muscular dystrophy with myositis (Ttn(mdm/mdm)) mutation leads to a severe early-onset muscular dystrophy and premature death. We have tested the hypothesis that the titin N2A deletion in the mdm mouse diaphragm would have a deleterious impact on its force-generating capacity and would alter its passive mechanical properties, independent of major histopathology. Our data show significant structural and functional aberrations of the respiratory pump in the mdm mouse that may be attributable to a critical function of titin's N2A region. This work was part of the Ph.D. thesis of Dr. Michael Lopez who has been a member of our research group. Mechanical signal transduction: We have been interested in the anisotropic regulation of the mechanosensitive genes, such as Ankrd2. We found that axial stretch activated Akt, which up-regulated Ankrd2 expression through NF-kappaB. However, stretch in the orthogonal direction to the muscle fibers activated Ras-GTP, Raf-1, and Erk1/2 proteins, which up-regulated Ankrd2 expression through AP-1. Our data show the anisotropic regulation of Ankrd2 gene expression in the diaphragm muscles occurs via two distinct mechanosensitive signaling pathways. This work was conducted in collaboration with my colleague Dr. Junaith Mohamed, a Research Associate who has been a member of our research group. In addition, we have been interested in the physiologic role of Sirt1 in skeletal muscles. We have recently unraveled a mechanism triggered by mechanical stretch of skeletal muscle cells that leads to an EGR1-dependent transcriptional activation of the Sirt1 gene. The resulting transient increase in SIRT1 expression generates an antioxidative response. This work was conducted in collaboration with my colleague Dr. Patricia Pardo, a Research Associate who has been a member of our research group

Dr. Danail Bonchev received his PhD degree in quantum chemistry from the Bulgarian Academy of Sciences (Sofia), and in 1984 he was awarded SciD degree by the Lomonosov Moscow State University (Russia). Postdoctoral experience in St. Petersburg University (Russia), University of Milano (Italy), Max-Planck Institute in Mulheim, Ruhr and Technical University in Merseburg (Germany), University of Paris-7 (France), as well as Texas A&M University and Virginia Commonwealth University (US). Full Professor of Physical Chemistry with Assen Zlatarov University in Burgas, Bulgaria (1987-1992). With Texas A&M University in Galveston since 2002. Since 2003/2004 Professor of Mathematics and Director for research in bioinformatics, networks and pathways at the Center for the Study of Biological Complexity , Virginia Commonwealth University (VCU). Elected Corresponding Member of the Bulgarian Academy of Sciences; elected member of the International Academy of Mathematical Chemistry.

Research: Long time interests in theoretical/mathematical chemistry: Characterization of molecular structure by quantum chemistry, information theory and graph theory. Since 2002 joined the new area of systems biology and computational biology, with a focus on molecular level. Developed the first graduate course in network biology in 2006. Research interest in analyzing and quantifying complexity of networks. Current Research: Network theory and its biomedical applications, including evolutionary studies, identification of markers and drug candidates, molecular mechanisms of diseases.

Dr. Josep Bassaganya-Riera is the Director of the Nutritional Immunology and Molecular Medicine Laboratory (NIMML). He has held and currently holds many research grants from various sources including the National Institutes of Health, the United States Department of Agriculture, and industrial corporations. He is the Principal Investigator and Director for the Modeling Immunity to Enteric Pathogens (MIEP) project, Center that investigates the immunoregulatory mechanisms underlying infections with gut pathogens by applying mathematical systems to mucosal immunology. He is also Principal Investigator on an RO1 award designed to study the mechanisms of immune modulation by abscisic acid. Dr. Bassaganya-Riera has published over 80 scientific papers, 7 patents.

Research: Nutritional immunology Gastrointestinal health Type 2 diabetes, cardiovascular disease and obesity Modeling Immune Responses

Research: Bioinformatics Systems biology Biomedical imaging Informatics

Dr. Baker joined the Baylor University faculty as an assistant professor in Bioinformatics in August of 2002. Prior to this academic appointment he served as a post-doctoral research fellow at Oak Ridge National Laboratories in the Genome Analysis and System Modeling Group. At Baylor Dr. Baker directs the Bachelor of Science in Informatics (Bioinformatics) degree program where he has the privilege to interact with many dedicated students. His research agenda includes translational functional genomics, distributed database systems, and data harmonization. This includes areas of biological information management systems, distributed databases, application of graph algorithms to biological processes and systems biology. He currently serves as the lead bioinformatics developer for the  MATRR and GeneWeaver web systems.

Research: Distributed Databases and BigData LIM Systems Graph Algorithms Translational Genomics

Research: Computational biology Machine learning Structural bioinformatics Structural systems biology Pattern recognition

Research: Computational Genomics

Dr. Yang Cao received PhD in Computer Science from University of California at Santa Barbara. He joined the Computer Science Department at Virginia Tech as an assistant professor in 2006 and became an associate professor in 2012. Dr. Cao has been active in the area of computational systems biology, particularly in modeling and simulation of stochastic effects. He has collaborated with with many researchers in related areas. He has won the prestigious NSF early career award and two best paper awards.

Research: Dr. Cao’s research interest spans many areas of computational science, such as numerical solution of ordinary differential equations and differential algebraic equations, sensitivity analysis, adjoint methods, multiscale simulation, and stochastic modeling and simulation in biochemical systems. His recent research interest focuses on the modeling and simulation of stochastic effects in biological systems.

Dr Shiva M. Singh (PhD in Genetics) is a Distinguished University Professor and Professor of Molecular Genetics in the Department of Biology, Division of Medical Genetics (Paediatrics), and Division of Developmental Disability (Psychiatry) at the University of Western Ontario, where he is also Graduate Faculty in Biology, Bioinformatics and Neuroscience. In addition to these roles he is an Associate Scientist in Molecular Medical Genetics at the Child Health Research Institute of the London Health Sciences Centre, London, Ontario and a Senior Research Fellow of the Ontario Mental Health Foundation. Dr Singh has received a number of honors, including the Senior Award of Excellence from the Genetics Society of Canada and Distinguished Research Professorship of the Faculty of Science. He has published over 225 papers in international journals and has supervised >100 graduate students and trainees. His research interests are genome-wide molecular (epi-) genetics and neurogenomics of mental disorders as a means to understand neurodevelopment and functioning of the brain. His current foci are Schizophrenia twin genomics, Fetal Alcohol Spectrum Disorders (FASD) and animal models of complex disorders.

Research: Genetics Neurogenomics 

Prof. Don Kulasiri obtained the BSc Eng (honours) at University of Peradeniya (1980) Sri L Lanka and MS and PhD in Engineering at Virginia Tech, USA, in 1988 and 1990, respectively. He joined Lincoln University, Christchurch, New Zealand in 1990 as a lecturer and was appointed to a personal Chair in 1999 by the university. He founded the Centre for Advanced Computational Solutions (C-fACS) at Lincoln University in 1999. He has been: a Visiting Professor, Integrated Systems Biology Cente/Centre for Mathematical Biology, University of Oxford, UK (Jan - June, 2008, Nov 2010, June 2013), a Visiting Fellow, Princeton University, New Jersey (Jan-June, 2004; July 2006) , a Visiting Professor to Institute of Scientific Computing, Technical University of Braunschweig, Germany (since 2001), a Visiting Scholar, Stanford University (Jan-June, 1998), a visiting member of the Centre for Mathematical Biology, Oxford University, a member of Modelling and Simulation Society of Australia and New Zealand and Sigma Xi honour society; and a Panel member of Mathematics, Information Science and Technology (MIST) panel for the PBRF 2012 quality evaluations, Govt  of New Zealand.

Research: Computational and Mathematical modelling of biochemical processes/pathways ( inter/intra cellular) based on biophysical considerations; Dynamics of networks far from thermodynamic equilibrium ; stochastic modelling of biological systems; and computational systems biology in general. Prof. Kulasiri maintains a strong interest in bioengineering/biotechnology as well.

Research: Statistical genetics/genomics High-dimensional data analysis

Dr. Abdel-Badeh M Salem is a professor emeritus of Computer Science since September 2007 till now. He was a former Vice Dean of the Faculty of Computer and Information Sciences at Ain Shams University, Cairo-Egypt (1996-2007).  He was a professor of Computer Science at Faculty of Science, Ain Shams University from 1989 to 1996.  He was a Director of Scientific Computing Center attain Shams University (1984-1990). His research includes intelligent computing, expert systems, medical informatics, and intelligent e-learning technologies. He is author for many books and co-author of 15 books in English and Arabic languages. He has published around 200 papers in refereed journals and conference proceedings in these areas.  He has been involved in more than 200 conferences and workshops as an Int. Program Committee , organizer and Session Chair.  He is author and co-author of 15 Books in English and Arabic Languages. He is a member of the Editorial Board of many journals. 

Research: Dr. Abdel-Badeh M Salem ‘s research interests include Medical Data Mining and Expert Systems. Image Processing and Pattern Recognition. Bio-informatics and e-Health Intelligent e-Learning. Medical Informatics, . Knowledge Engineering. Current research includes BIO-METRICS CANCER INFORMATICS  

Research: COLLABORATIVE RESEARCH: My collaborative research has been in numerous areas including diabetes, pediatric autism and delayed developmental, HIV, hypertension, dermatology, stroke, obesity and fibromyalgia. My primary long term research has been in diabetes focusing on preventing diabetes, understanding barriers to insulin initiation and interventions on improving diabetes related clinical outcomes. This major collaboration resulted in several publications, e.g. the long term effect of a community-based lifestyle intervention to prevent type 2 diabetes and reduced 10-year risk of coronary heart disease (Ackerman et. al. Chronic Illness, 2011; Diabetes Care, 2009), barriers to insulin initiation (Diabetes Care, 2010), and use of multimedia technology for improving clinical outcomes through improved communication on cardiovascular disease risk between diabetic patients and physicians (Diabetes Specterm, 2010). The second major collaboration I had was in stroke and hypertension. Stroke research includes a wide variety topic, e.g. how children view their abilities, feeding problems in children, cerebral palsy and association with other disability in children with perinatal stroke (Barkat-Masih et. al. Journal of Child Neurology 2011 and 2009, Golomb et. al. Journal of Child Neurology 2008 and 2007). Research in hypertension was on methodologies of identifying hypertension in hemodialysis patients (Agarwal and Saha, Blood pressure monitoring 2007, Agarwal et. al. Kidney international 2006 and 2007), improvement of blood pressure with suppression of ENaC (Saha et. al. Hypertension 2005) and change in blood pressure during pubertal growth (Shankar et. al. The journal of Clinical Endocrinology and Metabolism, 2005). Other significant collaborative research includes treatment of HIV related endothelial dysfunction (Gupta et. al. AIDS 2010 and 2008), onset of overweight during childhood and adolescents in relation to race and sex (Saha et. al. The Journal of Clinical Endocrinology and Metabolism 2005) and severe electrocardiographic abnormalities and risk of arrhythmias and sudden death in myotonic dystrophy type I (Groh et. al. New England Journal of Medicine 2008).   METHODOLOGICAL RESEARCH: Subject dropout is an inevitable problem in longitudinal studies and very often the reason for dropout might be informative. Use of linear mixed effects model in comparing rate of change in outcome and use of last observation carried forward approach (LOCF) in comparing the change in outcome from baseline are very common approaches. In collaboration with Dr. Jones at the University of Iowa, we quantified bias in parameter estimates both for linear mixed effect model and LOCF approach under informative dropout (Saha and Jones, Journal of Royal Statistical Society Series B 2005 and Saha and Jones, Journal of Statistical Planning and Inference 2009). The current follow up research in this area has been quantifying type I and type II error rates in the LOCF approach under informative dropout.

Research: Phase I/II/III clinical trials and experiment design Linear Mixed Models Longitudinal data analysis (in mixed models with repeated Missing data  

I studied biology at the University of Groningen (RUG; the Netherlands), obtained my PhD also at the RUG on molecular biology of Gram-positive bacteria. In 2002 I started working as a Post-Doc at the laboratory of Prof. Kuipers (Molecular Genetics; RUG) in the early days of microarrays and bioinformatics. The amazing speed at which the high-throughput experimental biology and bioinformatics develop and the unprecedented view on microbial metabolism and regulation soon drew my attention and firmly hold me in their grip ever since. After Post-Docs at the RUG and the University of Greifswald (Germany) I started my job at NIZO food research as senior scientist bioinformatics and as academic group leader of my bioinformatics group in Nijmegen.

Research: My group (bacterial genomics, Rumc) focuses on researching the association of microbial consortia and human health through (meta)genomics approaches. The research performed in Nijmegen is inspired both by biological research questions from academia as well from industry. For the latter, my second work-place at NIZO food research is instrumental. The group has a strong track record on predicting bacterial functional properties, microbial sequencing, population profiling, and multi-variate data analysis. My scientific goal is to develop and use bioinformatics and systems approaches to translate knowledge of well-established microbial model organisms to microbes of emerging importance, both from a fundamental and an applied perspective. Integration of information from heterogeneous sources obtained for different model organisms is key to deduce hypotheses concerning how microbes interact with each-other and their matrix. 

Wynand started his professional life with a PhD in Theoretical Physics and taught a variety of courses to Physics students since 1972 at the University of Pretoria, before being appointed as professor at the University of South Africa in 1980. His main research interest in this period was the application of quantum chemistry and molecular modelling methods to understand the structure and properties of semiconductor surfaces. In pursuit of this he spent several extended research stays in Europe: at the University of Paris; two stays with a Alexander von Humboldt fellowship at the University of Clausthal, and at Woolfson College of Oxford University. For variety he punctuated this by the occasional consulting contract as applied mathematician in fields ranging from engineering to orthodontics. A sabbatical stay at the University of Otago convinced him of the charms of New Zealand, where he moved in 1998. At the same time he switched fields to computational modelling, and was awarded a second PhD in Computational Systems Modelling for work on stochastic differential equation modelling of porous media by Lincoln University in Christchurch. A further course of direction led to his present appointment as senior lecturer in Computational Biology at Lincoln University, where he currently does research on modelling of metabolic networks in cell molecular biology.

Research: Constraints based modelling methods Cellular metabolic networks Flux balance analysis Electrochemical applications of microbes Computational approaches to bioengineering

Dr. Kang Ning is Professor and Leader of the Bioinformatics Group of Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences (QIBEBT-CAS) from 2010. He also served as the PI of CUDA Researh Center at QIBEBT-CAS. He received the Bachelor degree from University of Sciences and Technology of China, and the Ph.D. degree from the National University of Singapore. He has a postdoctoral research experience at the University of Michigan. He has won more than ten competitive funding from Nature Science Foundation of China (NSFC), Ministry of Science and Technology (MoST) and Chinese Academy of Sciences (CAS).

Research: Method and algorithm development for genomics, metagenomics, single-cell omics and proteomics Synthetic biology and high-performance-computing

Tuan D. Pham received his PhD in 1995 from the University of New South Wales (Sydney, Australia) and is currently Professor and Leader of the Aizu Research Cluster for Medical Engineering and Informatics, Center for Advanced Information Science and Technology, The University of Aizu, Japan. He has served as an Editorial Board Member and Associate Editor of several journals and book series, and Chair and Technical Member of a number of international conferences in the areas of pattern recognition, image and signal processing applied to medicine and biology. He is the founder of the International Symposium on Computational Models for Life Sciences (CMLS) and The International Aizu Conference on Biomedical Informatics and Technology (ACBIT).

Research: Major Research Areas Bioinformatics Biological imaging Medical imaging Biosignals   Current Research Chaos and complexity analysis of intracellular space and cell-signaling dynamics Alignment-free sequence comparisons Automated microcopy image quantification of biological cells Image analysis of brain MRI and abdominal CT scans

Dr Lin Feng is currently an Associate Professor, the Director of Bioinfomatics Research Centre and the Programme Director of MSc (Digital Media Technology) at School of Computer Engineering, Nanyang Technological University. He has worked for 18 funded research projects since joining NTU and has published 170+ technical papers including 70+ in journals of high impact factors, edited books and chapters; he has been serving Editorial Board, Guest Editor / Reviewer for tens of journals and books; and he has won 7 prestigious research awards, including the “National Science and Technology Advance Award (Second Class)” by Chinese State Council. He is a Senior Member of IEEE.

Research: Dr Lin's research interest includes biomedical informatics, biomedical imaging and visualization, computer graphics, high-performance computing. Currently active funded projects include: AcRF - Nonrigid graphics shaders for GPU, A-Star/BMRC - Creating an In Vivo Navigational Cellular Fluorescence Imaging System with Dynamically Optimized Endomicroscopy, AcRF - Real-time Diagnostic Endomicroscopy, A-Star/SERC - Collaborative Creation and Application of Interactive Digital Media over the Internet, AcRF - Cellular Fluorescence Imaging with Endomicroscopy, AcRF - Dynamically Adaptable Neurocomputer and Its Application to Recognition of Steroid Hormone Response Elements, SingHealth Foundation Development of a Real-time Fluorescence Endoscopy Diagnostic System for the Early Detection of Oral and Bladder Cancers, NTU/BPE Cluster SEED Funding - Gene Expression Profiling with Oligonucleotide Microarray Technology; and some completed funded projects: SCE ER Lab Research Programme Grant DNA Chip Design Programme, BMRC&NMRC Joint Research Fund - Elucidation of Expression Profiles of Genes in Alpha-fetoprotein Positive and Alpha-fetoprotein Negative Hepatocellular Carcinoma by cDNA Microarray Analysis, AcRF - Design and Simulation of Artificial Bone Implantation, NMRC Research Fund -Nasopharyngeal Carcinoma: 3D Imaging for Staging and Treatment Planning, AcRF - Design and Development of Bio-medical Devices Using Rapid Prototyping (RP) Techniques, AcRF - Real-time Dynamic Simulation, MOH & Singapore Totalisator Research Fund - Transforming Medical Ultrasound Scanning into 3-Dimensional Real-time Organ Imaging to Aid Clinical Diagnosis.

Dr. Zhenglong Gu received his Bachelors of Science degree in Biochemistry and Molecular Biology from Peking University in 1998, and his PhD degree in Ecology and Evolution in 2003 from University of Chicago. He conducted his postdoctoral research at Stanford Genome and Technology Center and became an Assistant and Associate Professor in the Division of Nutritional Sciences at Cornell University in 2006 and 2012 respectively.

Research: Dr. Gu's laboratory uses a combination of computational and experimental approaches to understand the structure of metabolic networks and how these have been shaped over evolutionary time by selective pressures, such as those imposed by nutrient constraints, in model organisms and human.

Research: My scientific training has been multidisciplinary (medicine, basic research in biology, and computer science). My ongoing research projects bring together the fields of bioinformatics and cancer biology. My primary interest is to elucidate molecular mechanisms of disease using high-throughput functional genomic approaches. More specifically, I have developed large-scale databases of gene expression signatures related to human cancer and developed a strategy to perform meta-analyses of gene expression profiles from published cancer studies and the TCGA project. The results from data mining of gene expression signatures have helped us identify prognostic and predictive signatures and novel candidate metastasis-regulatory genes in cancer. I have further investigated one intriguing candidate gene in my lab by in vivo and in vitro functional approaches. 

Jason W. Locasale, Ph.D. is an Assistant Professor in the Division of Nutritional Sciences at Cornell University. He graduated from Rutgers University, Summa Cum Laude with a dual degree in Chemistry and Physics. He received his Ph.D. at the Massachusetts Institute of Technology in Biological Engineering. He then studied cancer metabolism at Harvard Medical School where he worked as an American Cancer Society postdoctoral fellow and then later as an Instructor on the faculty. Dr. Locasale is a recipient of the NIH Pathway to Independence Award, the Ruth Kirchstein National Service Award, the Benjamin Trump Award for Excellence in Cancer Research from the Aspen Cancer Society, and was elected as a Junior Fellow at the Bert and N. Kuggee Vallee Foundation. Dr. Locasale serves on the advisory board of the American Association of Cancer Research - Chemistry in Cancer section. He has authored over 35 publications and has co-authored numerous textbooks and patents.

Research: Dr. Locasale’s research focuses on understanding metabolism in cell growth, cancer pathogenesis and therapeutic intervention. His efforts have focused on understanding the Warburg Effect – the observation that tumor cells process glucose through fermentation even when oxygen is abundant for respiration. He has defined the mechanistic principles that lead to the Warburg Effect and is now investigating its downstream consequences on cellular physiology. He is currently translating this knowledge to develop biomarkers of agents that affect glucose metabolism in cancer. As a postdoctoral fellow, Dr. Locasale made the seminal discovery that a major pathway utilized by glucose-metabolizing cancer cells involved the diversion of glycolytic flux into one-carbon metabolism through de novo serine and glycine metabolism. Dr. Locasale is currently pursuing the role this pathway in disease pathogenesis and cell transformation and this work has led him to study the interplay between metabolism, signal transduction, and epigenetics. At the core of this effort lies the utilization of computational modeling and mass spectrometry-based metabolomics. Together this systems biology approach combines these tools with an integration of genetics, biochemistry, and cell biology.

Dr. Bingshan Li received his Ph.D. in Computational Biology in 2009 and joined Vanderbilt University as an assistant professor in 2011. His main research is developing statistical methods and computational tools for genetics studies of human complex disease. He is currently interested in cancer genomics and developing methods to link genomic aberrations with clinical outcomes.

Research: Statistical and computational genetics Genetics of complex traits Cancer genomics

Prof. Sarath Chandra Janga obtained his Bachelors and Masters degrees in Bio-chemical Engineering and Biotechnology from the Indian Institute of Technology, Delhi. He obtained his PhD in Molecular and Systems Biology from the prestigious MRC Laboratory of Molecular Biology & Darwin college, University of Cambridge, UK from 2008-2010, on employing computational and graph-theoretical approaches to studying problems in molecular and cellular biology. He is currently an Assistant Professor in the Department of Biohealth Informatics, School of Informatics and Computing at IUPUI with joint appointments in the Center for Computational Biology and Bioinformatics, Department of Medical and Molecular Genetics as well as Division of Gastroenterolgy/Hepatolgy in the Department of Medicine at the Indiana University School of Medicine. He has published more than 50 research publications on various aspects of basic and applied translational research in the fields of computational, molecular and systems biology. Early in his career, he has been the founding member and vice chair of the student body of the International Society for Computational Biology (ISCB). He has been invited for more than 70 international seminars and lectures for his work in understanding gene regulatory networks using computational and systems approaches. His group’s current research interests include understanding the structure and dynamics of post-transcriptional and post-translational gene control at a whole-genome level. In addition, his group is actively exploiting next generation clinical sequencing data to mine genetic alterations in diseases and their impact on human health using integrated computational data mining and systems biology techniques to uncover the principles and causes of specific phenotypes.

Research: Translational Bioinformatics Computational and Systems Biology

Dr. Naiji Lu received his PhD in Mathematics from University of Rochester in 2007 and subsequently worked in the Department of Biostatistics and Computational Biology. As an Assistant Professor, he collaborated with Biologists, Psychiatrists, Computer Scientists and experts in other areas on numerous projects. Dr. Lu has extensive experience in the areas of longitudinal data analysis, distribution-free models, robust statistics, causal inference, structural equation models, survey data analysis, social network data analysis and their applications to large clinical trials and biomedical research.

Research: Longitudinal Data Analysis and U-statistics Survival Analysis Nonparametric and Semiparametric Regression Spatial and Network Analysis

Research: Structural bioinformatics Protein recognition Monte Carlo and molecular dynamics studies of biological macromolecules Non-covalent interactions in biological macromolecules Structural modeling of proteins and protein-protein complexes (docking) Knowledge-based constrains to protein docking Modulation of protein-protein interactions by small molecules Design of databases/servers/software for storage and analysis of protein interaction data

Yanni Sun is an Assistant Professor in the Department of Computer Science and Engineering at Michigan State University. She received the B.S. and M.S. degrees from Xi'an JiaoTong University in 1998 and 2001 respectively, both in Computer Science. She received the Ph.D. degree in Computer Science from Washington University in Saint Louis in 2008. She works in bioinformatics and computational biology. In particular, her recent research interests include sequence analysis, next-generation sequencing data analysis, protein domain annotation, and noncoding RNA annotation. She was a recipient of NSF CAREER Award in 2010.

Research: Bioinformatics/computational biology: algorithm design for large-scale sequence database analysis, protein domain and noncoding RNA identification in the next-generation sequencing data (RNA-Seq and Metagenomic data), genome-scale noncoding RNA search, sequence similarity search, protein domain classification, miRNA identification, CRISPR annotation in metagenomic data.

I obtained my PhD from the Department of Computer Science, University of South Carolina, with focus on bioinformatics. Soon after my graduation, I became a research assistant professor at the Department of Cancer Biology, Vanderbilt University. Currently I am serving as the Technical Director of Bioinformatics for Vanderbilt Technologies for Advanced Genomics Analysis and Research Design (VANGARD), a core to consolidate the genomics data pipeline across Vanderbilt University by providing biostatistical and bioinformatic support for next-generation sequencing and other genomics technologies. Much of my research was related to bioinformatics with specific focus on methodology development around next-generation sequencing technologies. My second area of research interest is mitochondrial function and epigenetic biomarker identification in cancer.

Research: Research on developing bioinformatics-specific methodologies, especially in cancer research, is my primary interest. I am also interested in mitochondrial function and epigenetic biomarker in caner. Much of my research time has focused on methodology development for next generation sequencing data analysis.  My most recent research work was centered on the “lost treasures” of sequencing data. I am also interested in the quality control procedures for NGS data analysis. Also of interest are topics such as mitochondria function in cancer research. For example, in 2011, we evaluated 44 DNA blood samples from 17 Danish and 1 Finnish families (18 mothers and 26 children) using NGS technology. All mothers had been treated for cancer as children and radiation doses to their ovaries were determined based on medical records and computational models. We sequenced their mitochondria genome in order to determine if any mutation damage to mother’s ovaries got carried to the offspring. The result of this study was published in Mutation Research.

Dr. Jie Zheng is a tenure-track assistant professor of School of Computer Engineering, Nanyang Technological University (NTU), Singapore, and an adjunct faculty (senior research scientist) of Genome Institute of Singapore (GIS). He received Ph.D. in 2006 from the University of California, Riverside and his B. Eng (first class honors) in 2000 from Zhejiang University in China, both in Computer Science. Before joining NTU in 2011, he was a research scientist at the National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), USA. While trained as a Computer Scientist, Dr. Zheng maintains active and long-standing collaborations with Life Scientists.

Research: In the age of “big data” for biomedicine, computational technologies play ever more important roles in life sciences. The objectives of my research consist of: (1) developing computational methods to analyze the data from biomedical research, to understand the mechanisms of human diseases; (2) building integrative and predictive models that can recapitulate phenomena observed in wet-lab experiments; (3) using the models to predict behaviors of living systems under different conditions, thereby facilitating the discovery of novel therapeutics and healthcare solutions. Currently my group works on the following areas: (1) Computational genomics and systems biology in human disease study (cancer and malaria); (2) epigenetic regulation of gene expression; (3) in silico modeling of cell fate for cancer and stem cell research.

Research: Cell adhesion is crucial for many biological phenomena such as tissue morphogenesis, immune response and tumor invasion. The aggregations of membrane receptors on cellular interfaces during these physical processes initiate the elaborate intracellular networks of signaling pathways. Despite of remarkable experimental achievements, there is still long way to eventually form a mechanistic understanding to cell adhesion, and further decipher its intricate connection to signal transduction. By integrating computational analysis with experimental measurements, our lab focuses on developing multi-scale modeling frameworks to study the cross-talks between cell adhesion and cell signaling. We are particularly interested to ask following questions: why and how different cells form contacts; when and where these contacts are formed at specific locations of our bodies; what are their functional impacts to the downstream signaling pathways, and further to our human health.

Ramanathan is an Associate Professor in the School of Bio Sciences and Technology at VIT University. He received the B.Tech. and M.Tech. degrees from Bharathiar and SASTRA University in 2002 and 2004 respectively, both in Chemical Engineering. He received his Ph.D. degree in Bioinformatics from VIT University in 2011. His main research is bioinformatics and computational biology. He published more than 65 international articles in high impact factor journals.

Research: Dr. Ramanathan’s research includes:  Molecular modeling on biological systems such as influenza, hepatitis viruses and cancer drug targets Rotational drug design against influenza neuraminidase