There are now several large-scale data commons supporting the biomedical research community and the beginnings of data ecosystems. In this talk, we discuss some of the emerging best practices around data ecosystems, as well as some of the challenges and opportunities. We also discuss some case studies of data commons and data ecosystems developing using the open source Gen3 data platform.

Multiple initiatives are currently underway for setting up large biobanks with associated clinical and molecular data. With more than 800,000 samples already collected and genotyped, the Million Veteran Program (MVP), promises a unique opportunity to perform genomic analysis at scale for meaningful interpretation of results with better confidence. This talk will discuss the infrastructure that facilitates genomic research in MVP, as well as the challenges in scaling data, analytics, security, and data governance.

No business is immune to change. This presentation will highlight how the right blend of best practices and technology can provide researchers the tools needed to facilitate and accelerate their digital transformation.

This talk discusses current cloud-based distributed computing options and presents results from a study that compared cost and performance of cloud systems and in-house deployments. It is intended not only as an evaluation of infrastructural choices, but also proposes a metric framework that can serve as a baseline for researchers and practitioners examining distributed infrastructures on cloud.

The Hutch uses EB for building software containers and all software for our computer cluster. Our software stack is published and citable and we share our work with the global community of EasyBuild users.

Join us for a lively discussion among prominent pharma leaders, and learn:

Why, when & how to implement a public Cloud for your computing needs

Challenges and opportunities when setting and managing stakeholder expectations

Critical keys to success to realize the best outcomes

To learn more about RCH Solutions, visit our Virtual Booth

Hosted by Joe Donahue, Managing Director, Life Sciences, Accenture

Participants include: 

Andreas Matern, Head of Digital Translational Medicine, Sanofi

John Quackenbush, Professor of Computational Biology and Bioinformatics; Harvard T.H. Chan School of Public Health

Seungtaek Lee, VP, Strategic Partnerships and AI RWE Head of CoE; ConcertAI

Preston Keller, PhD, MBA, President & CCO, PercayAI

Philip Payne, PhD, Becker Professor and Chief Data Scientist, Washington University in St. Louis

Most large scale analysis of clinical trial data only leverages part of the picture, ignoring unstructured data and limiting findability across all the information collected throughout multiple disparate data sources.  This roundtable will discuss leveraging a cognitive platform to combine all data from multiple sources into one unified view using a single entry point to the data.

Evaluating, optimizing and benchmarking of next generation sequencing (NGS) methods are essential for clinical, commercial and academic NGS pipelines. Optimizations for speed and accuracy often require making trade-offs relative to other constraints. Join this roundtable to discuss benchmarking strategies, trade-offs, and the value of benchmarking genomics tools and applications. 

In this presentation, we show how we are using cloud technologies for: (i) processing MS data through a cloud-based ETL pipeline for extracting features; (ii) analyzing MS data using in-house tools developed for Windows system in a cloud environment; and (iii) storing and organizing MS data and its metadata in a cloud-based Data Lake. The Data Lake allows researchers to access and explore the MS data through a convenient web interface, using metadata and data parameters, as well as the extracted data features. Finally, we present how our system uses the extracted features for automatic System Suitable Tests analysis, thus informing the researchers about the status and expected performance of the MS instruments.

Cyrus Biotechnology has developed a set of tools and research practices that allow us to rapidly develop complex molecular modeling procedures, automate the execution of those procedures and deliver them to our research team and to external customers as API based products.  This presentation will describe the architecture of cloud-native system that allows us to accomplish this as well as our approach to software engineering and scientific research.

Cloud computing allows life science researchers and organizations unprecedented access to compute capacity to improve their time to results. This session will look at cloud computing trends in life sciences and HPC in general and discuss various alternatives for cloud migration.

Learn how Illumina is enabling researchers, scientists, and informaticists to gain more insight on their genomic and multi-omic data with a new, flexible cloud-based platform. This platform allows researchers to store and manage data at scale, analyze data through custom and published workflows with high efficiency, and collaborate with users.

Biotechnology companies are facing new challenges in the amount of data that needs processing for genomics analysis. What used to be Terabytes of data is now petabytes of data and beyond. This data needs to be collected, analyzed, processed and then ultimately retained for compliance and research purposes - resulting in massive data storage and management challenges, unsolvable by legacy technology solutions. Our session will explain how to leverage new all-flash storage and hybrid-cloud solutions to make genomics analysis run quantum leaps faster than before.

How do you use data / digitization today to drive scientific discovery / product development?

What are you greatest scientific pain points / gaps that are not being met by digitization?

What kinds of outcomes do you believe digital tools could help you achieve?

Welcome to this discussion group on the growth of demand for HPC in scientific research. We are looking forward to a lively forum. We'll start by looking at three related topics:

- What events trigger demand in your organization? How has the current pandemic impacted resources?

- What could make scale and collaboration more accessible to more researchers?

- Share a recent experience of shifting workloads to manage HPC capacity.

In this session we’ll discuss how to provide researchers with performance and scale in genomics & research analytics, to drive results at a price point that’s economically viable on public & private cloud.

Storage solutions we’ve been using force bioinformaticists to make trade-offs between the capacity and low-cost of disk and the performance of flash. This results in complex tiering configurations that only deliver performance for a small slice of the data. In this session, we will review how advancements in technology enable VAST Data to revolutionize the cost of all-flash and allows bioinformatists faster analysis across larger datasets for deeper insights.