Мини-курс "Microscopy image analysis". Лектор: Петер Хорват, PhD, Hungarian Academy of Sciences, Biology Research Institute/Finnish Institute for Molecular Medicine
16 февраля 2017 стартует мини-курс «Microscopy image analysis». Лектор - Петер Хорват, PhD, Hungarian Academy of Sciences, Biology Research Institute/Finnish Institute for Molecular Medicine
Description:
High-content screening (HCS) combines cell biology (including all molecular techniques), automated high resolution microscopy, informatics and robotics. It aims to discover small and large molecules (such as drugs, siRNAs) that change the phenotypes of cell in a desired manner. High-content analysis (HCA) refers to the analysis and evaluation of large data produced during an HCS scenario. Despite the fact that informatics was revolutionized recently, HCA suffers from the lack of solutions to the computational problems that arise and the limited computational capacity. To overcome these, recently numerous image analysis and machine learning approaches were proposed. This course will give an insight into the different most popular methods including automated microscopy, image processing, and multiparametric analysis of the data. During this course we will create 10.000-100.000 images (virtually in this case) and we will develop methods to analyze them using image segmentation and supervised machine learning.
Thematic:
High content screening – Introduction, History
High content microscopy
Data storage, databases
Image correction methods (CIDRE)
Image analysis, image segmentation, 2d/3d
Feature extraction
Multiparametric quality control
Machine learning methods (Classification, regression)
Matlab applications
Recommended literature:
1. Taylor, Haskins, Giulliano: High Content Screening (Methods in Molecular Biology); ISBN-10: 1588297314 | ISBN-13: 978-1588297310 | Edition: 2006
2. Steven A. Haney; High Content Screening: Science, Techniques and Applications
3. Marjo Götte and Daniela Gabriel (2011). Image-Based High-Content Screening in Drug Discovery, Drug Discovery and Development - Present and Future, Dr. Izet Kapetanović (Ed.), ISBN: 978-953-307-615-7
4. Bickle M. The beautiful cell: high-content screening in drug discovery. Anal. Bioanal. Chem. 2010 Sep;398(1):219-26
5. I. Banerjee, Y. Yamauchi, A. Helenius, P. Horvath: High-content analysis of sequential events during the early phase of influenza A virus infection; PLoS One 2013
6. Peter Horvath, Thomas Wild, Ulrike Kutay, Gabor Csucs. Machine learning improves the precision and robustness of high-content screens – using non-linear multi-parametric methods to analyze screening results. J. Biomolecular Screening. 2011Расписание
16 февраля, четврег – 18.00 – 21.00, аудитория 416
21 февраля, вторник – 15.10 – 18.00, аудитория 327
Зарегистрироваться можно письмом на адрес ikorolkova@hse.ru