Sunday, January 25, 6:00-9:00 pm
5:00-6:30 pm Short Course Registration and Main Conference Pre-Registration
6:00-9:00 Dinner Course*: Introduction to High-Content Phenotypic Screening
The ever-increasing demand for improved productivity in research through the generation of robust analysis outputs has driven both the development and deployment of automated high-content analysis (HCA) and phenotypic cell-based approaches to drug discovery. In contrast to the more traditional cellular analysis and target-based approaches, here the researcher is able to evaluate the efficacy of potential therapeutics by monitoring the physiological state of cells through the simultaneous analysis of multiple cellular parameters in the context of an intact biological system. This course will cover the key features of HCS/A technologies and the best approaches to using these technologies for phenotypic cell-based screening.
Instructor: Anthony M. Davies, Ph.D., Center Director, Translational Cell Imaging Queensland (TCIQ), Institute of Health Biomedical Innovation, Queensland University of Technology
Who should attend?
This course has been developed to introduce and facilitate scientists who are either moving into the field or who are interested in further developing new phenotypic discovery applications and tools for use with these technologies.
(i) An introduction to HCA technologies
(ii) Advanced cell-based models for use with HCA
(iii) Worked examples of the phenotypic screening approach and future directions
(iv) Group discussion and Q&A
- Develop a familiarity of the basics of HCS/A technologies
- Gain an understanding of the capabilities of this technology
- Learn of the latest developments in cell-based models for use in this field
- Get a better understanding of the key principles of assay design and development for phenotypic screening
Monday, January 26, 6:30-9:00 pm
6:30-9:00 Dinner Course*: Introduction to High-Content Data Analysis
One of the most crucial parts of a successful high-content screen (HCS) is the proper analysis of the data. This course gives an insight into the most important steps of a successful analysis and highlights its bottlenecks. While recent developments in microscopy result in larger images and increased throughput, they also give rise to image creation problems. To account for these errors, novel image correction methods will be introduced. One of the key points for any further measurement in HCS is the successful detection and analysis of the object of interest. Segmentation, feature detection and related questions will be studied. In the end of the course, machine learning methods will be presented for single cell-based phenotypic analysis.
Instructor: Peter Horvath, Ph.D., Group Leader, Synthetic and Systems Biology Unit, Hungarian Academia of Sciences; Finnish Distinguished Professor (FiDiPro) Fellow, Institute for Molecular Medicine Finland
1. Image correction methods
2. Object analysis: image transformations, segmentation, feature extraction, deconvolution
3. Phenotypic analysis: machine learning using classification, regression
methods, active learning for classification and regression
Who should attend:
The course is developed for scientists working in different fields of HCS who want to better understand and/or implement novel data analysis technologies in facilities. The course does not require preliminary knowledge in computer science, but assumes that the participants have at least basic knowledge in high-content screening.
*Separate registration required