The Association for Medical and Bio-Informatics, Singapore (AMBIS) welcomes all biomedical professionals to its annual symposium. This event features prominent speakers from various healthcare and research institutions in Singapore, with opportunities for learning and networking.
Date/Time: 25th May 2012. 12 noon till 6pm
Venue: National University Singapore, Lecture theatre 29.
Symposium fee: $60 includes meals and free annual AMBIS membership*
BioInformatics Track
About the Seminars & Speakers
Predictive Analytics in Biomedicine
Since the advent of the Human Genome Project, a great deal of interest has been centred on the applications of large scale "omics" data in biomedical research, with the ultimate goal of enabling personalized treatments of human diseases. Inadvertently, such "omics"-based research present significant challenges for biomedical researchers, often leaving them questioning how they could intelligently extract, harness and derive actionable knowledge from the bewildering amount of data. Data mining techniques - such as machine learning - can be used to uncover meaningful patterns from complex biomedical datasets and derive useful predictions for knowledge discovery. Biomedicine analytics involve theoretical concepts and practical solutions spanning a wide range of domains - such as cellular biology, immunology and neuroimaging.
Interested in this topic? Sign up for our 25 May 2012 symposium to learn more!
Speaker's Biography
Dr. Lawrence Wee is a research scientist at the Institute for Infocomm Research, specializing in the application of data mining techniques for basic and translational biomedical research. He has developed several novel techniques and proprietary software for analyzing and modelling biomedical data, and is currently involved in a number of collaborative research with bench scientists and clinicians globally. His services to the scientific community include reviewing submissions to top-tiered bioinformatics journals and conferences, as well as organizing local and international bioinformatics conferences, meetings and workshops. Dr Wee obtained his Ph.D. from the National University of Singapore. He is also a member of the International Society for Computational Biology (ISCB) and the Association for Medical and Bio-informatics Singapore (AMBIS).
Interested in this topic? Sign up for our 25 May 2012 symposium to learn more!
Speaker's Biography
Dr. Lawrence Wee is a research scientist at the Institute for Infocomm Research, specializing in the application of data mining techniques for basic and translational biomedical research. He has developed several novel techniques and proprietary software for analyzing and modelling biomedical data, and is currently involved in a number of collaborative research with bench scientists and clinicians globally. His services to the scientific community include reviewing submissions to top-tiered bioinformatics journals and conferences, as well as organizing local and international bioinformatics conferences, meetings and workshops. Dr Wee obtained his Ph.D. from the National University of Singapore. He is also a member of the International Society for Computational Biology (ISCB) and the Association for Medical and Bio-informatics Singapore (AMBIS).
Statistical Tools for Biomedical Data Analysis
The objective of biomedical data analysis is to discover useful and meaningful patterns hidden in the biomedical data. Statistical tools (measurements and tests) are often necessary to assess the “usefulness” and “meaningfulness” of patterns. In the literature, the commonly used statistical tools include t-test, Chi-2 test, fisher’s exact test, etc. All the statistical tools are developed and can be applied under certain assumptions and constrains. However, many researchers tend to apply the statistical tools without careful examination of the validness of the underlying assumption. This may often lead to false discoveries and invalid conclusions. A researcher needs to know the commonly used statistical tools for biomedical data analysis along with their underlying assumptions and constraints.
Sign up for our 25 May symposium to avoid common mistakes in applying these tools, and learn about alternatives and necessary corrections!
Speaker Biography
Dr. Feng Mengling is currently working as a Scientist in the Data Mining Department of Institute for Infocomm Research (I2R), A*STAR. He is involved in a wide spectrum of research projects across the fields of bio-imaging, bioinformatics, medical data analysis, continuous time-series analysis, data mining for business strategies and fundamental data mining. Dr. Feng has found his real interest in knowledge discovery and data analysis during his PhD study with Prof. Wong Limsoon and Prof. Tan Yap-Peng. Dr. Feng’s current research focus is on biostatistics, data mining for business intelligence and medical time-series analysis.
Sign up for our 25 May symposium to avoid common mistakes in applying these tools, and learn about alternatives and necessary corrections!
Speaker Biography
Dr. Feng Mengling is currently working as a Scientist in the Data Mining Department of Institute for Infocomm Research (I2R), A*STAR. He is involved in a wide spectrum of research projects across the fields of bio-imaging, bioinformatics, medical data analysis, continuous time-series analysis, data mining for business strategies and fundamental data mining. Dr. Feng has found his real interest in knowledge discovery and data analysis during his PhD study with Prof. Wong Limsoon and Prof. Tan Yap-Peng. Dr. Feng’s current research focus is on biostatistics, data mining for business intelligence and medical time-series analysis.
