10:00 – 13:00
(SC3) CLOUD COMPUTING: Using Cloud Computing Infrastructure as a Service to Aid Research Scientists
The use of automated provisioning and configuration management tools is an essential “best practice” for cloud-based systems. The scriptable nature of infrastructure cloud platforms makes them a perfect fit for tools designed to automatically provision, configure and deploy systems, servers, clusters & complex scientific pipelines. We will demonstrate our primary configuration management system – the open source OpsCode Chef platform. We will also show how Chef can bootstrap public Amazon EC2 AMIs into Chef-managed nodes. Hands-on practices are included.
Instructors:
Chris Dagdigian, Co Founder & Principal, BioTeam, Inc.
Adam Kraut, Scientific Consultant, BioTeam, Inc.
10:00 – 13:00
(SC4) MICROSCOPY IMAGING ANALYSIS: Quantitative Analysis of Large-Scale Biological Image Data
Microscopy has emerged as one of the most powerful and informative ways to analyze cell-based high-throughput screening samples in experiments designed to uncover novel drugs and drug targets. During this workshop we will cover the basic theory of digital image analysis of this type of data, including quality control and machine learning for phenotype classification. We will introduce the free and open source Cell Profiler software and relate the image analysis theory to some recent results, including high-throughput screening using the worm C.elegans as model system for human disease.
Instructor:
Carolina W鄣lby, PhD, Principal Investigator at the Imaging Platform of the Broad Institute of Harvard and MIT and Associate Professor in Quantitative Microscopy at the Centre for Image Analysis at Uppsala University
14:00-17:00
(SC9) Visualization of Large-Scale Biological Data
This course is designed for everyone who would like to apply visualization techniques in the analysis of large biological data sets. The course provides useful background material on data visualization principles, but the focus is on methods and tools for visualization of microarray data, next-generation sequencing data, other omics data and network data.
Instructors:
Kay Nieselt, Ph.D., Integrative Transcriptomics, Center for Bioinformatics T黚ingen, University of T黚ingen
G黱ter J輍er, M.Sc., Integrative Transcriptomics, Center for Bioinformatics T黚ingen, University of T黚ingen
14:00-17:00
(SC10) NGS: Data Analysis
The explosion in demand for next-generation sequencing platforms brings with it a monumental challenge for any research group, organization or facility in analyzing the torrent of data about to be unleashed. These challenges are intensify as labs audition and integrate new platforms, expand capacity, and try to balance a growing array of projects, users and applications. This short course provides in-depth, interactive guidance on the essential do’s and don’ts in analyzing the prodigious volumes of data produced in next-generation sequencing.
*Separate registration required
