CONFERENCE SERIES: Informatics & IT
Recorded at: Bio-IT World Conference & Expo
Digital Course: Imaging Informatics: Optimizing Image Collection, Management and Analysis to Improve Drug Discovery
April 20, 2010
About this Product:
The richness of information in images has made it one of the most popular readouts for high-throughput screening in recent years. This increasing amount of images requires the development of tools to automatically analyze and interpret them. However, neither the infrastructure nor the development of image analysis has been able to keep up with the fast growth of image data. This digital course offers you some solutions including data management, image analysis algorithm, image and metadata integration, etc. The main focus of this course is to share available resources, experiences and promote discussion for current needs in the HCS community.
About the Conference:
Since its debut in 2002, the annual Bio-IT World Conference & Expo
(www.bio-itworldexpo.com) has established itself as a premier event showcasing the myriad applications of IT and informatics to biomedical research and the drug discovery enterprise. The Conference attracts a highly influential audience consisting of senior level scientists, IT professionals and Executives from organizations across the life sciences industry including Pharmaceutical, Biotechnology, Health Systems, Academia, Government and National Laboratories. In 2010, over 1700 delegates gathered to share information and discuss enabling technologies that are driving the drug discovery process. The event features concurrent tracks with 100+ technology and scientific presentations.
Agenda at a Glance:
Considerations and Practice in High-Throughput Imaging and Image Analysis
Tiao Xie, Ph.D., Image Analyst, ICCB-Longwood, Systems Biology, Harvard
Biography: Tiao Xie, Ph.D. is the image analyst at the Institute of Chemistry and Cell Biology - Longwood (ICCBL) screening center. He received his B.S. from Peking University, China, Ph.D. in computational chemistry from Emory University and trained as a postdoctoral fellow with Tim Mitchison at Harvard Medical School. His research is focused on high content image analysis and 3-dimensional image reconstruction.
Optimizing Image Acquisition for Efficient High-Content Screening
Tom Hasaka, Ph.D., Senior Automation Engineer, Broad Institute
Biography: Manager of High-Content Screening at the Broad Institute’s Chemical Biology Platform. Currently screening libraries of about 30,000 small molecules. Background in Cell and Developmental Biology, Microscopy, Imaging Hardware and Software, Image Analysis and High-Content Imaging.
High-Content Screens for Complex and Subtle Phenotypes
Vebjorn Ljosa, Ph.D., Computational Biologist, Broad Institute
Biography: Vebjorn Ljosa is a computational biologist at the Broad Institute of MIT and Harvard. He received his PhD in computer science from the University of California, Santa Barbara, in 2007, and is now part of an interdisciplinary research group that develops and applies methods for extracting quantitative information from biological images. Vebjorn’s current research interests include data-driven methods for scoring and mining image-based screens and other high-throughput experiments.
Automated Analysis of Subcellular Patterns in Cells and Tissues
Estelle Glory Afshar, Ph.D., Postdoctoral Fellow, Murphy Lab, Center for Bioimage Informatics, Carnegie Mellon University
Biography: Estelle Glory-Afshar is currently a postdoctoral fellow at Murphy Lab in Carnegie Mellon. She received her MS in Computer Science Applied to Biology from the University Paris V (France) in 2001 and her PhD in Computer Science from the University Paris V and the Institut Pasteur in 2005. Her fields of interest are microscopy image analysis, pattern recognition, machine learning algorithms and databases.
Presented by Luis Pedro Coelho, Carnegie Mellon University
About this Course:
Over 103 slides
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