AMBIS Biomedical Symposium 2012 - Medical Informatics Track

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. 10am till 6pm

Venue: National University Singapore, Lecture theatre 28.

Fees:

Morning Keynote Lectures are FREE for all professionals.

Afternoon M.I Seminar & Workshop fee: S$60 includes meals and free annual AMBIS membership*

Register Now!

Program details (Click on program to enlarge)

More details on the Speakers and Topics.

*AMBIS is a national member of the International Medical Informatics Association (IMIA), a member of the Asia-Pacific Association for Medical Informatics (APAMI) and a regional affiliate of the International Society for Computational Biology (ISCB

AMBIS Biomedical Symposium - BioInformatics Track

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*

Register Now!

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).

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.

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.

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).

AMBIS Annual Lecture Series - Prof. Thomas August - 21 Feb 2011

Biography
----------
Dr. Joseph Thomas August, University Distinguished Service Professor of Pharmacology and Molecular Sciences and Oncology, joined the Hopkins faculty in 1976 as Director of Pharmacology and Experimental Therapeutics. A graduate of Stanford University School of Medicine, he previously served as Chairman, Department of Molecular Biology and Director, Division of Biology, The Albert Einstein College of Medicine, 1972-1976.

From 2001 to 2004, he was interim director of the division of biomedical sciences at Johns Hopkins Singapore, and is currently adjunct professor of medicine at the National University of Singapore. Dr. August’s current research centers on the development of novel virus and cancer vaccines and has more than 200 publications and 40 years of experience in genetic immunotherapy of infectious diseases and cancer, development of DNA vaccine; and has over the past 8 years worked closely with groups in Singapore to integrate bioinformatics technologies in these and other research areas.

Lecture Details
---------------
We are honored to host Dr. August for the AMBIS Annual Lecture Series. The details of the lecture are as follows:

Date: 21 Feb Monday
Time: 6.30pm
Venue: Eusoff Hall Seminar Room

Title: Genetic immunotherapy of infectious diseases and cancer

Abstract: Vaccines have been one of the most effective instruments for the prevention of disease in the history of medicine. Nevertheless, despite this record of success, there are many remaining challenges in the design and application of vaccines effective against many current major pathogens, including cancer, influenza, HIV-1, malaria, and dengue virus. The scope of this seminar is to present the rationale for the application of genetic vaccines and the continuing critical problems of genetic vaccine research, and the developments of our laboratory at The Johns Hopkins University School of Medicine with applications of new technologies to several
pathogens, including dengue virus, West Nile virus, yellow fever virus, hepatitis A virus, influenza A virus and human immunodeficiency virus-1. The impact of bioinformatics and medical informatics on this project will be discussed.

Map: Google Maps
Directions: Nearest MRT: Clementi MRT Station

EUAsiaGrid BioWorkshop 4-6 May 2010

EUAsiaGrid BioWorkshop

Master Class on High Performance Applications For Life Sciences
Date: 4-6 May 2010

Venue: CSD Computer Lab, Block S13 Physics Dept,
National University of Singapore (NUS)
Info: http://trg.apbionet.org/euasiagrid/

AMBIS AGM 2010

AMBIS AGM 2010

Date: 5th May, Wednesday

Time: 7pm

Venue: NUS Guild House, Evans Room