CONFERENCE SERIES: Informatics & IT
Recorded at: NGx: Sequencing Data Management
This digital course will cover real-world use cases across drug discovery & design, collaboration, next generation sequencing, proteomics, software as a service, and bioinformatics, to explore how life sciences are using cloud computing, its challenges and effectiveness, how money can be saved by an organization, and regulatory compliance.
About this Product:
4 Presentations
Over 98 slides
123 minutes
Single Copy - $345.00
Site License - $1,380.00
Molecular Modeling Research in the Cloud at Schrodinger
Peter S. Shenkin, Ph.D., Vice President, Schrödinger
Schrodinger is a leading researcher in computational molecular modeling. As such, we develop software that runs on the Cloud and we also use the Cloud for internal research, drug-discovery collaborations with commercial partners, and infrastructure needs. In this talk, we describe our experience with scientific computing on the Cloud and present the pros and cons of moving collaboration applications like e-mail, documents, and calendaring to the Cloud.
Biography: Peter S. Shenkin, Vice President, joined Schrödinger in 1999. Previously, he was the lead developer of the MacroModel molecular-modeling package at Columbia University. He received his Ph.D. in Chemistry from Princeton University in 1979. After working for Owens-Corning Fiberglass Corporation for four years, he taught and carried out research at Columbia University and Barnard College prior to joining the MacroModel group in 1992. He has published in the areas of biosequence diversity analysis, protein structure determination, implicit solvation models for molecular mechanics and fast methods for determining solvent-accessible surface areas for atoms in molecules.
Cloud Computing at U. Penn ITMAT Bioinformatics Facility
Angel Pizarro, Director, University of Pennsylvania ITMAT Bioinformatics Facility
The cloud provides a valuable tool for doing bioinformatics research, and this presentation will discuss various operational issues in using Cloud Computing for aiding and abetting high-throughput biomedical research. The focus will be "what is the simplest way to get the job done", using recent projects involving next-generation sequencing and proteomics. We will cover a specific examples of bootstrapping a system to install, configure and start a simple Ruby-based Map-Reduce system, Cloud Crowd, as well how to get the data to and from the cloud.
Biography: Angel Pizarro's undergraduate Biology training at Cornell taught him one thing: under no circumstances should he ever be allowed near fragile instrumentation or complex glassware of any sort. Lucky for him the era of high-throughput biology was just starting, bioinformatics became a buzz word, and his academic career was made better, faster and stronger with the introduction computers. Currently he leads the ITMAT Bioinformatics Facility in support of UPENN researchers conducting high-throughput microarrays, proteomics and next-generation sequencing experiments. Germane to this workshop, his facility recently completed a move of their entire infrastructure to the cloud. He'll be discussing the move and topics that are vital to anyone evaluating cloud solutions for their research.
NGS Workflows on the Cloud: From PoC to Production
David Powers (formerly of Eli Lilly, Evangelist), Senior Analyst, Business Development, Cycle Computing
In this talk we will compare and contrast real life workflows that have been moved to the cloud. We will dive into the technical implementation details to explore the workflows, dealing with data synchronization, and how we leverage cloud services in AWS to process large data. Use cases will include secondary/tertiary- analysis, data archival, and re-analysis. Comparisons between internal clusters for small/large sites, and cloud-based methods will also be reviewed.
Biography: Dave Powers has 20 years of IT experience in distributed enterprise environments with specific expertise working in large installation system administration for UNIX/Linux environments, storage architectures and HPC. A visionary leader behind the movement into cloud computing at Eli Lilly, he now serves as company evangelist and business development consultant at Cycle.
About the Conference:
CHI’s Next-Generation Sequencing Data Analysis combines unique perspectives from a variety of engineers, biostatisticians, and software developers involved in these data archiving issues, creating a common ground on which to explore how best to store, transfer, and analyze these data so that they can be applied as knowledge. This team of scientists will reference case studies as they provide a forum to discuss recent trends and issues in sequencing, enabling you to choose the best technology for your sequencing and research demands.