Keynote Speakers

 

Prof. Kenta Nakai                                                                                                                

The University of Tokyo, Japan

 

Kenta Nakai was born in Osaka, Japan, in 1963. He received the PhD degree on the prediction of subcellular localization sites of proteins from Kyoto University, Kyoto, Japan, in 1992.
From 1989, he has worked at several institutions, including, Kyoto University, National Institute of Basic Biology, and Osaka University. From 1999 to 2003, he was an Associate Professor at the Human Genome Center, the Institute of Medical Science, the University of Tokyo, Japan. Since 2003, he has been a full Professor at the same institute. He was elected as the president of the Japanese Society for Bioinformatics in 2006 and 2007. His main research interest is to develop computational ways for interpreting biological information, especially that of transcriptional regulation, from genome sequence data. Two of his papers reporting the development of a knowledge-based prediction system of subcellular localization sites have been cited more than 1,200 times so far.

 

Speech Title: "Analyses of Transcriptional Regulatory Codes through a Variety of NGS Data"

 

Abstract: Nowadays, it is becoming more and more important to interpret the impact of differences between individual genomes and/or the genomes of normal and abnormal cells (e.g., tumor cells). In many cases, however, this is difficult mainly because we do not understand how the gene regulatory information is encoded in the non-coding regions of the genome. To overcome this difficulty, so-called next generation sequencers (NGSs) are quite useful: they are not only useful just for reading DNA sequences per se but also getting a variety of information, such as the information on gene expression profiles in a single cell under various conditions/stages. They are also useful for probing the epigenetic status and the approximate 3D structure of chromatin. In this talk, I will introduce some of our research activities in this direction. The talk will include (1) our efforts in automatically extracting the frequent patterns of motif placements in the genome and our future plan of constructing an encyclopedia of gene regulatory regions; (2) our ongoing project to combine multiple sources of Hi-C data for understanding the differential gene expression through differential chromatin loop structure; and (3) our efforts in analyzing single-cell transcriptome data to understand inter-tissue communication in the mammalian immune system.

 

Prof. Sung Wing Kin, Ken                                                                                                    

National University of Singapore, Singapore

 

Prof. Dr. Wing-Kin Sung received both the B.Sc. and the Ph.D. degree in the Department of Computer Science from the University of Hong Kong in 1993, 1998, respectively. He is a professor in the Department of Computer Science, School of Computing, NUS. Also, he is a senior group leader in Genome Institute of Singapore. He has over 20 years experience in Algorithm and Bioinformatics research. He also teaches courses on bioinformatics for both undergraduate and postgraduate. He was conferred the 2003 FIT paper award (Japan), the 2006 National Science Award (Singapore), and the 2008 Young Researcher Award (NUS) for his research contribution in algorithm and bioinformatics.

 

Speech Title: "Fast, Sensitive and Accurate Detection of Virus Integrations in Cancer"

 

Abstract: The study of virus integrations in human genome is important since virus integrations were shown to be associated with diseases. In the literature, few methods have been proposed that predict virus integrations using next generation sequencing datasets. Although they work, they are slow and are not very sensitive.
This talk introduces a new method BatVI to predict viral integrations. Our method uses a fast screening method to filter out chimeric reads containing possible viral integrations. Next, sensitive alignments of these candidate chimeric reads are called by BLAST. Chimeric reads that are co-localized in the human genome are clustered. Finally, by assembling the chimeric reads in each cluster, high confident virus integration sites are extracted.
Finally, we applied BatVI to some cancer datasets and we will discuss the findings we have.

 

Prof. Satoru Miyano                                                                                                              

The University of Tokyo, Japan

 

Satoru Miyano, PhD, is the Director of Human Genome Center, the Institute of Medical Science, the University of Tokyo. He received the B.S. (1977), M.S. (1979) and PhD (1984), all in Mathematics from Kyushu University, Japan. He is an ISCB Fellow. His research mission is to develop "Computational Medical Systems Biology towards Genomic Personalized Medicine, in particular, cancer research and clinical sequence informatics. He has been involved as PI with the International Cancer Genome Consortium, the Grant-in-Aid for Scientific Research on Innovative Areas (MEXT) "Systems Cancer Research in Neo-dimension", and MEXT Priority Issues on Post-K computer "Integrated Computational Life Science to Support Personalized and Preventive Medicine". By massive data analysis and simulation with the supercomputers, his group is developing computational methods to link differences in our genomes to diseases, drugs, and environmental factors with systems understanding.

 

Speech Title: "Unraveling Cancer Systems Disorders from Big Data by Supercomputers"

 

Abstract: Cancer is a very complex disease that occurs from accumulation of multiple genetic and epigenetic changes in individuals who carry different genetic backgrounds and have suffered from distinct carcinogen exposures. We present our computational methods for breaking cancer big data by using the supercomputers SHIROKANE at Human Genome Center of University of Tokyo and K computer at RIKEN Advanced Institute of Computational Science. The first challenge is unraveling gene networks and their diversity lying over genetic variations, mutations, environments and diseases from gene expression profiles of cancer cells. The second part of this lecture gives details of a suite of bioinformatics tools named Genomon for analyzing cancer genomes and RNA sequencing data produced by next-generation sequencers. We present some of our recent results on cancer genomics with Genomon, including a mechanism involved with “how cancer evades immune systems.”
 

Plenary Speakers

 

Prof. Keimei Oh                                                                                                                     

Akita Prefectual University, Japan

 

Dr. Keimei Oh was born in Shanghai, China. He received B.Sc. in the Department of Chemistry from Shanghai University and Ph.D. degree from the Graduate School of Agricultural and Life Sciences, The University of Tokyo in 1997. After working at RIKEN as a Special Postdoctoral Fellow, he joined the Department of Biotechnology faculty at Akita Prefectural University in 1999. In 2003, he worked as a visiting scientist at US Department of Energy, Plant Research Laboratory in Michigan State University. He was appointed as Associate Professor at Akita Prefectural University in 2007. Currently, he is working in the field of design and synthesis biological active chemicals targeting plant hormone biosynthesis and signaling transduction pathways. He received numerous awards including the Society Award of the Japanese Society for Chemical Regulation of Plants.

 

Speech Title: "Chemical Genetics Strategy Identifies Small Molecules Induce Triple Response in Arabidopsis"

 

To explore small molecules with ethylene like biological activity, we conducted a triple response based assay system for chemical library screening. Among 9600 compounds, we found that N-[(1, 3, 5-trimethyl-1H-pyrazol-4-yl)methyl]-N-methyl-2-naphthalenesulfonamide (EH-1) displayed promising biological activity on inducing triple response in Arabidopsis seedlings. Chemical synthesis and SAR analysis of EH-1 analogues with different substitution on the phenyl ring structure of the sulfonamide group indicated that 3, 4-dichloro-N-methyl-N-(1, 3, 5-trimethyl-1H-pyrazol-4-yl-methyl) benzenesulfonamide (compound 8) exhibits the most potent biological activity. To determine the action mechanism, we conducted RNA-Seq analysis of the effect of EH-1 and ACC, the precursor of ethylene biosynthesis, following the quantitative RT-PCR confirmation. Data obtained from RNA-Seq analysis indicated that EH-1 and ACC significantly (above 20 fold of control) induced the expression of 39 and 48 genes, respectively. Among which 5 genes are up-regulated by EH-1 as well as by ACC. We also found 67 and 32 genes are significantly down-regulated, respectively. Among which 7 genes are in common. For quantitative RT-PCR analysis. 12 up-regulated genes were selected from the data obtained from RNA-Seq analysis. We found a good correlation of quantitative RT-PCR analysis and RNA-Seq analysis. Based on these results, we conclude that the action mechanism of EH-1 on inducing triple response in Arabidopsis is different from that of ACC.

 

Prof. Manoj R. Tarambale                                                                                                     

Marathwada Mitra Mandal’s College of Engineering, Pune, India

 

Prof. Manoj R. Tarambale has received Bachelor's Degree (B.E.) in Electrical Engineering from BVCOE, Pune-43, University of Pune, India, in 1992 and Master of Engineering Degree (M.E.) in Control System ( specialization in Instrumentation ) from WCOE, Sangli, Shivaji University, Kolhapur, India in 2002. Currently, he is pursuing his Ph.D. degree from PACIFIC University, Udaipur, India in the field of Biomedical Engineering.He has one year industrial experience and twenty one years teaching experience. At present, he is working as a Head of Electrical Engineering Department of Marathwada Mitra Mandal’s College of Engineering, University of Pune, Pune-52, India.
He has published fifteen papers in prestigious International Journals and in International Conferences. He has got “Most Excellent Paper Award” and “Inter Science Scholastic Young Investigator Award” for his technical papers published.His main research interests are in the field of Bio-Medical Image Processing, Bio-Medical Instrumentation, Bio-sensors, Green Environment, Computer Applications in Bio-Medical Analysis, Artificial Intelligence in Disease Detection and Electrical Engineering. He is giving an important contribution in implementing various early detection cancer technique projects through Bio-Medical Image Processing. He has also done two consultation projects for the reputed industries. Prof. Tarambale is a member of Institute of Engineers (India) and Indian Society for Technical Education (ISTE).

 

Speech Title: "Detection of Medical Disease (Lung Cancer) Using Image Processing Tool–An Engineering Approach"

 

Today, cancer is one of the most formidable health problem faced by mankind. This cancer confirmation process is complex, time consuming and costly. It might be possible during the above process the stage of the cancer may change. Though MRI, CT scan, PET etc. radiological images helps us to detect lung nodule easily, but because of huge cost involve still avoided in poor and developing country. Inexpensive method involve detection of cancer from simple chest X-ray.  Abnormal masses seen in the chest X-ray in the form of white spot / tumors are analyze through engineering image processing methods, so that in early stage cancer conformation took place, which reduce the mortality rate. In an engineering approach to detect lung cancer various steps involved are data acquisition, image processing, segmentation, feature extraction and use of artificial intelligence. First digitized images are obtain by scanning X-ray image by high resolution scanners and adjusted to standard size by applying size normalization algorithm. The image processing refer to the tasks necessary for enhancing the quality of acquired digitizes X-ray scanned images. . The quality of the original image obtained can be improved further by applying histogram equalization algorithm and segmentation of suspicious region is done by using various edge detection algorithms, labeling algorithm etc. Various features are extracted on the basis of mathematics using simple software programming which help to classify suspicious tumor as malignant or benign using machine learning process or also called it as using Artificial Intelligence. The proposed system will not replace the doctor’s role in detection of cancer but it will help doctor to take correct decision in short time with accuracy (It will act as second opinion before conformation of cancer).

 

Assoc. Prof. Hiroyuki KUDO                                                                                                   

Meiji University, Japan

 

Prof. Dr. Hiroyuki Kudo received both the M.E. and Ph.D. degrees in the Department of Electronics and Communications from Waseda University in 1999 and 2004, respectively. He was a research officer of MEMS laboratory, Tokyo Metropolitan Industrial Technology Research Institute from 2003 to 2007. He worked at Tokyo Medical and Dental University as an assistant professor from 2005, a junior associate professor from 2007 to 2011 and an associate professor from 2011 to 2013. Currently, he has been an associate professor of Department of Electronics at Meiji University. Currently, his research interests include biomicrosystems based on enzymatic biosensors and immunosensors and for life science applications.

 

Speech Title: "Electrochemical Biosensors for Healthcare IoT"

 

The internet of things (IoT), which is a new paradigm rapidly spreading in highly developed information society, have been expected to open new window in treatment and diagnosis in medicine and daily personal healthcare. Particularly, plenty of physical information (e.g. body weight, temperature, fat rate, etc.) has been already utilized in cloud services. However, hurdles for using biochemical information in such information services are still high. One of the most considerable reason is that simplified means for obtaining biochemical information are not provided. From this point of view, we position that simplified method to measure or assess biochemical information (e.g. blood content, saliva content, etc.) as the key technology for providing health big data and healthcare IoT. It is necessary to realize a series of processes from ‘sampling’ to ‘measurement’ by an operation that anyone can do with simple and low-cost instruments for the applications in those fields. We have been developed new biosensors and biomicorsystems for those purposes by combining the microelectromechanical system (MEMS) techniques and biochnology. In this talk, our recent status of development and possible applications will be presented.

 

Assoc. Prof. Riichi Kajiwara                                                                                                   

Meiji University, Japan

 

Riichi Kajiwara is Associate Professor of Department of Electronics and Bioinformatics at Meiji University. He received a B.Eng. from Tohoku University in 1993, and M.S. and Ph.D. degree in information science from Tohoku University, in 1995 and 1998. During the Ph.D. course degree, he was working at Electrotechnical Lab AIST in Tsukuba science city, and learned about the basis of electrophysiology and the optical imaging technique with the use of voltage-sensitive dye. From 1998 to 2013 he worked at AIST, eventually as a Senior Research Scientist. His research interest is the brain network physiology of the mnemonic and emotional function.

 

Speech Title: "Network Properties of Limbic Neurons Revealed by Voltage-Sensitive Dye Imaging"

 

The 'limbic system' is considered as a crucial structure for the neural plasticity caused by learning and memory behavior. Therefore the neural circuitry of limbic system is the primary target of functional modifications relating to the higher cognitive dysfunctions caused by various factors. The in vitro brain slice preparations have been used for the purpose so often, due to the difficulty in recording neural activities from deep brain structures under in vivo conditions. Particularly, hippocampal slice preparations are more commonly used to investigate the plasticity on a cellular / synaptic level. However, the functional connectivity should also be examined in much larger scales. Here we discuss about this issue by showing the optical imaging data obtained from two types of ex vivo brain preparations, cortico-hippocampal brain slices and isolated whole brain preparations. The isolated whole brain preparation, in which multi-synaptic circuits and the intracellular activity they generate are well preserved, can be useful to examine such large scale neural circuitry. In the presentation, we describe about the functional connectivity of various brain regions in the limbic system using this unique preparation. This experimental approach combines the advantages of the in vivo experimental condition with those of in vitro slice preparations, i.e. an intact synaptic network, excellent mechanical stability, and control over the ionic and biochemical extracellular environment. In particular, it provides easy access to brain areas of the limbic system and preserved the neuronal network of the entorhinal-hippocampal loop. Here we present example data obtained from this preparation in combination with optical imaging of voltage-sensitive dyes.

 

Invited Speakers

 

Assoc. Prof. Siew Woh Choo                                                                                                 

Xi'an Jiatong-Liverpool University, China

 

Choo completed his PhD study in Genetics from the University of Cambridge and secured a scholarship from the Singapore government, to pursued MSc at the School of Medicine at the National University of Singapore. He is currently an Associate Professor at Xi'an Jiatong-Liverpool University. Choo has 15 years of working experience in research, academia and private industry in the fields of genetics and bioinformatics, and mastered a number of high-end core technologies. He has led a team to participate in local and international projects with a total funding amount of about RMB 10 millions and published more than 53 peer-reviewed articles (1st or corresonding author in at least 42 articles) in prestigious journals including Nature and Genome Research with >4850 citations. He has set up and led the International Pangolin Research Consortium that has members from prestigious Yale University, Peking University, Washington University, St. Petersburg State University and Smithsonian Conservation Biology Institute. Choo has also actively transformed scientific research achievements by setting up a high-tech enterprise and won several national awards. He has been the Chairman and CEO of a biotechnology company, as well as a Senior Scientist and Consultant at a personal genomics company. He has served on the editorial board of Scientitic Reports and has been appointed as National Bioinformatics Expert Appraiser Panel of the National Malaysian Qualifications Agency (MQA). In addition, he devoted himself to the higher education industry, taught and educated many postgraduates, postdoc, undergraduates, and research assistants.

 

Speech Title: "Pangolin Genomes and the Evolution of Mammalian Scales and Immunity"

 

Pangolins, unique mammals with scales over most of their body, no teeth, poor vision, and an acute olfactory system, comprise the only placental order (Pholidota) without a whole-genome map. To investigate pangolin biology and evolution, we developed genome assemblies of the Malayan (Manis javanica) and Chinese (M. pentadactyla) pangolins. Strikingly, we found that interferon epsilon (IFNE), exclusively expressed in epithelial cells and important in skin and mucosal immunity, is pseudogenized in all African and Asian pangolin species that we examined, perhaps impacting resistance to infection. We propose that scale development was an innovation that provided protection against injuries or stress and reduced pangolin vulnerability to infection. Further evidence of specialized adaptations was evident from positively selected genes involving immunity-related pathways, inflammation, energy storage and metabolism, muscular and nervous systems, and scale/hair development. Olfactory receptor gene families are significantly expanded in pangolins, reflecting their well-developed olfaction system. This study provides insights into mammalian adaptation and functional diversification, new research tools and questions, and perhaps a new natural IFNE-deficient animal model for studying mammalian immunity.