KEYNOTE SPEAKERS

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Dr. Igor Berezovsky

Bioinformatics Institute (BII),
Agency for Science, Technology and Research (A*STAR)

Dr. Berezovsky obtained PhD in molecular biophysics from the Moscow Institute of Physics and Technology (1997). He worked as a postdoctoral researcher at the Weizmann Institute of Science (1999-2002) and Harvard University (2003-2006). In 2007-2012 he was a senior scientist/group leader at the Bergen Center for Computational Science, University of Bergen (Norway), then visited the Weizmann Institute of Science in 2013. Dr. Berezovsky joined Bioinformatics Institute in January 2014. His research interests are in the areas of molecular mechanisms of adaptation to extreme environments, protein structure and dynamics in relation to enzymatic function and allosteric regulation, and the very emergence and evolution of the protein function.

Goncearenco A, Mitternacht S, Yong T, Eisenhaber B, Eisenhaber F, Berezovsky IN. SPACER: Server for predicting allosteric communication and effects of regulation. Nucleic Acids Res. 2013 Jul; 41:W266-72

Mitternacht S, Berezovsky IN. Coherent conformational degrees of freedom as a structural basis for allosteric communication. PLoS Comput Biol. 2011 Dec; 7(12):e1002301

Mitternacht S, Berezovsky IN. Binding leverage as a molecular basis for allosteric regulation. PLoS Comput Biol. 2011 Sep; 7(9):e1002148.

Dr. Chen-Ching Lin

Institute of Biomedical Informatics
National Yang-Ming University, Taiwan

Dr. Lin received PhD degree in Graduate Institute of Biomedical Electronics and Bioinformatics in National Taiwan University in 2012. After that, he worked as Post Doctor in Academia Sinica, University of Chicago and Vanderbilt University from 2012 to 2015. Science the end of 2015, he has been the assistant professor of Institute of Biomedical Informatics, National Yang-Ming University of Taiwan. His research focuses on bioinformatics, systems biology, and network biology.

Lin CC, Chang YM, Pan CT, Chen CC, Ling L, Tsao KC, Yang RB, Li WH. Functional evolution of cardiac microRNAs in heart development and functions. Mol Biol Evol. 2014 Oct; 31(10):2722-34.

Lin CC, Lee CH, Fuh CS, Juan HF, Huang HC. Link clustering reveals structural characteristics and biological contexts in signed molecular networks. PLoS One. 2013 Jun 24; 8(6):e67089.

Lin CC, Chen YJ, Chen CY, Oyang YJ, Juan HF, Huang HC. Crosstalk between transcription factors and microRNAs in human protein interaction network. BMC Syst Biol. 2012 Mar 13; 6:18.

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Dr. Dong-Yup Lee

Department of Chemical and Biomolecular Engineering (ChBE), National University of Singapore
Bioprocessing Technology Institute (BTI), Agency for Science, Technology and Research (A*STAR)

Dr. Lee received his PhD in Chemical and Biomolecular Engineering from KAIST. From 2005 till present, Dr. Lee is an assistant professor of the Department of ChBE at the National University of Singapore, with a joint appointment at the BTI of A*STAR as a senior research scientist. His research interests include computational analysis and engineering of biological systems, bioinformatics analysis of omics data, bioinformatics platform and tool development, system and synthetic biology, and drug and disease modelling.

Chin JX, Chung BK, Lee DY. Codon Optimization OnLine (COOL): a web-based multi-objective optimization platform for synthetic gene design. Bioinformatics. 2014 Aug 1; 30(15):2210-2.

Kim PJ, Lee DY, Kim TY, Lee KH, Jeong H, Lee SY, Park S. Metabolite essentiality elucidates robustness of Escherichia coli metabolism. Proc Natl Acad Sci USA. 2007 Aug 21; 104(34):13638-42.

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Dr. Hyunju Lee

School of Information and Communications,
Gwangju Institute of Science and Technology, South Korea

Field interested

  • Computational biology
    • An integrated framework for cancer module identification
    • Integration of gene expression and microRNA expression in cancer
    • Gene Regulatory Network
    • Alzheimer’s Disease association study using various biomarkers
    • Copy Number Variation(CNV) detection in cancer patients
    • Predicting drug-target interaction
    • Identification of markers associated with gene expression and DNA methylation data in cancers
    • Event extraction for pathway construction
    • Information retrieval for complex disease and cancer
  • Mining in social network
    • Recommendation of personalized social media content
    • Topic Modeling for personalized recommendation using social media data
    • Link recommendation using social media data for mobile user

Jin D, Lee H. A computational approach to identifying gene-microRNA modules in cancer. PLoS Comput Biol. 2015 Jan 22; 11(1):e1004042.

Han J, Lee H. Adaptive Landmark Recommendations for Travel Planning: Personalizing and Clustering. Pervasive and Mobile Computing. 2014 Aug 13;

Amgalan B, Lee H. WMAXC: a weighted maximum clique method for identifying condition-specific sub-network. PLoS One. 2014 Aug 22; 9(8):e104993.

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Dr. Jun Sese

National Institute of Advanced Industrial Science and Technology (AIST), Japan

Dr. Jun received PhD degree in Dept. of Computational Biology of University of Tokyo in 2005. After that, he worked as associate professer in Ochanomizu University for five years and Tokyo Insitute of Techology for four years. He is now Senior Research Scientist at National Institute of Advanced Industrial Science and Technology (AIST). His research focuses on developing new algorithms and statistical methods for analyzing Big Data in biology and medicine. The techniques are applied to find new insights of cellular mechanisms in the collaborations with biologists and medical scientists.

Terada A, Okada-Hatakeyama M, Tsuda K, Sese J. Statistical significance of combinatorial regulations. Proc Natl Acad Sci USA. 2013 Aug 6; 110(32):12996-3001.

Shingo Okuno, Tasuku Hiraishi, Hiroshi Nakashima, Masahiro Yasugi, and Jun Sese. Parallelization of extracting connected subgraphs with common itemsets. Information and Media Technologies. 2014; 9(3):233-250.

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Dr. Vladimir Kuznetsov

Bioinformatics Institute (BII),
Agency for Science, Technology and Research (A*STAR)

Dr. Vladimir obtained his degree in Physics at Kyrghyz State University (Kyrghyz Republic, Soviet Union). He went on to obtain a PhD in Biophysics at Moscow State University (Russian Federation, Soviet Union) in 1984. While he was a postgraduate student at the Institute of Molecular Biology (Moscow), Dr. Vladimir simultaneously worked as a Junior Scientist at the Research Institute of Oncology and Radiology (Kyrghyz Republic) and a lecturer at the Department of Mathematics and Mechanics. In 1992, Dr. Vladimir received a Doctor of Science degree in Mathematics and Physics at the Technical Union of Russian Academy of Sciences. Dr. Vladimir is an inventor of the pattern recognition algorithm – Statistically Weighed Syndromes voting method. This algorithm allows for the selection of a small number of variables from high dimension (e.g. microarray) data and provides robust individual prediction even if the original data set is noisy, contains missing values and is represented by very limited number of samples.

Ow GS, Kuznetsov VA. Multiple signatures of a disease in potential biomarker space: Getting the signatures consensus and identification of novel biomarkers. BMC Genomics. 2015; 16(Suppl 7):S2

Tang Z, Ow GS, Thiery JP, Ivshina AV, Kuznetsov VA. Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma. Int J Cancer. 2014 Jan; 134(2):306-18

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Dr. Ping Wei

Center for Quantitative Biology, Peking University

Dr. Wei received PhD degree in Physical Chemistry from Peking University in 2007. He did his post-doctoral training in Cellular and Molecular Pharmacology at University of California, San Francisco. After that, he worked as associate professor in Peking University. His research interest is using synthetic biology to understand and reprogram signaling networks.

Wei P, Wong WW, Park JS, Corcoran EE, Peisajovich SG, Onuffer JJ, Weiss A, Lim WA. Bacterial virulence proteins as tools to rewire kinase pathways in yeast and immune cells. Nature. 2012 Aug 16; 488(7411):384-8.

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Dr. Pauline Ng

Genome Institute of Singapore (GIS),
Agency for Science, Technology and Research (A*STAR)

Dr. Ng received her PhD in Bioengineering from the University of Washington in 2002. After graduation, she was the Computational Research Associate of Fred Hutchinson Cancer Research Center for a year. From 2002 to 2006, she worked at Illumina first as a bioinformatics scientist before promoted to senior scientist. She joined J. Craig Venter Institute in 2006 as a senior scientist and was then promoted to assistant professor in 2009. At present, she is a group leader at the Genome Institute of Singapore. Her major research focus is to understand the relationship between genotype and phenotype. This includes research in personalized medicine, understanding disease mutations, and working with next-generation sequencing technologies and protein sequence.

Javed A, Agrawal S, Ng PC. Phen-Gen: combining phenotype and genotype to analyze rare disorders. Nat Methods. 2014 Sep; 11(9):935-7.

Ng PC, Murray SS, Levy S, Venter JC. An agenda for personalized medicine. Nature. 2009 Oct 8; 461(7265):724-6.

Ng PC, Henikoff S. Predicting the effects of amino acid substitutions on protein function. Annu Rev Genomics Hum Genet. 2006; 7:61-80.