This webinar presents case studies on technologies, methodologies, and collaborations used to aggregate and harmonize data across an ecosystem to solve complex scientific problems and allow breakthrough discoveries to happen. Speakers will show novel
approaches of key drivers and innovations implemented to address issues at the intersection of science and technology. Specific themes that will be covered include data protection and visibility, building data commons and data hygiene, and artificial
intelligence and machine learning for life sciences and antibiotic discovery. Each speaker will give a presentation and at the end of the webinar there will be a moderated Q&A discussion.
- Protect and visualize your files at the scale of life sciences, with integrated search, restore, and visibility.
- Learn the data management techniques, tools, platforms, and frameworks that are proven to be effective at solving complex problems at scale.
- Understand common misconceptions regarding machine and deep learning, where it has been successfully applied in biology, and tips for when and where it's appropriate to use it.
- Learn how deep learning approaches have utility in expanding our antibiotic arsenal.
Scientific Solutions Lead, Engineering
Data Visibility and Protection at the Scale of Life Sciences
Data generation in the life sciences continues at a rapid pace. There are always risks of data loss, including hardware failures, inability of staff to access data centers,
and user error. During challenging times like these, understanding and protecting your data can save lives. Join us to see how you can protect and visualize your files at the scale of Life Sciences, with integrated search, restore, and visibility.
Adam Marko is the Scientific Solutions Lead for Igneous. He has over 15 years of experience in Research IT, supporting research in drug design, molecular diagnostics, and IT consulting. At Igneous, he turns research customers' data protection needs
into actionable IT solutions.
Director of Marketing
Building Data Ecosystems for Accelerated Scientific Discovery
Large federated data ecosystems require diverse teams that can design, build, and integrate a broad range of services to support scientific workflows. Our collaborative
team operates at the intersection of science, technology, and data to assess, implement, and teach the key capabilities and capacities modern healthcare and life science needs. Learn the data management techniques, tools, platforms, and frameworks
that are proven to be effective at solving complex problems at scale.
Adam is Director of Marketing and Innovation at BioTeam and has been a Senior Scientific Consultant at BioTeam for the past 12 years. Since 2002, BioTeam has been collaborating with and empowering clients across Pharma, Biotech, Government, and Non-profit
organizations with strategic analysis and planning, hybrid infrastructure services, and scientific data environments.
Senior Scientific Consultant for AI+HPC, The BioTeam, Inc.; former Global Alliance Manager for Genomics HPC+AI, NVIDIA
With the Power of AI Comes Great Responsibility
Artificial intelligence (AI) has taken off due to recent software and hardware advances giving rise to new tools in the scientific discovery process. From genomics to medical imaging,
most use cases come from the instrument world where "clean data " is easily obtainable. The use of these new tools has brought some anxiety outside instrument domain and questions about how data should look, how clean it should be and how to
apply to mixed data types. This talk will share common misconceptions regarding machine and deep learning, show examples of where it has been successfully applied in biology, and tips for when and where it's appropriate to use it.
Fernanda recently joined BioTeam as a Senior Scientific Consultant. She previously had a role at NVIDIA as a GPU Developer Advocate for Bioinformatics in the Healthcare group where she fostered an emerging community in AI and GPU computing. Before
NVIDIA, Fernanda held roles as an HPC Data Scientist in the Biomedical Sciences and Engineering group, and was an HPC Programmer and Training Coordinator at the Oak Ridge National Lab's Leadership Computing Facility. She participated in the CORAL
project that selected Summit as the next supercomputer to replace Titan, was co-PI of Kokkos Exascale Computing Project, served in OpenACC and OpenMP language standards and is the “inventor” of the GPU Hackathon training series. Other
interests include intersection of HPC and AI, facilitating data integration workflows, and productivity in scientific application development.
Jonathan Stokes, PhD
Laboratory of James Collins, Broad Institute of MIT and Harvard
A Deep Learning Approach to Antibiotic Discovery
To address the antibiotic-resistance crisis, we trained a deep neural network to predict new antibacterial molecules. We performed predictions on multiple chemical libraries and discovered
a molecule from the Drug Repurposing Hub – halicin – that is structurally divergent from conventional antibiotics and displays activity against a wide spectrum of pathogens. Halicin also effectively treated Clostridioides difficile and
Acinetobacter baumannii infections in mice. Deep learning approaches have utility in expanding our antibiotic arsenal. Paper: https://www.cell.com/cell/pdf/S0092-8674%2820%2930102-1.pdf;
Press Release: https://news.mit.edu/2020/artificial-intelligence-identifies-new-antibiotic-0220
Jonathan Stokes is a Banting Fellow in the laboratory of James Collins at the Broad Institute of MIT and Harvard. He received his BHSc in 2011, graduating summa cum laude, and his PhD in antimicrobial chemical biology in 2016, both from McMaster University.
His research applies a combination of chemical biology, systems biology, and machine learning approaches to develop novel antibacterial therapies with expanded capabilities over conventional antibiotics. Dr. Stokes is the recipient of numerous awards,
including the Canadian Institutes of Health Research Master’s Award, the Colin James Lyne Lock Doctoral Award, and was ranked first of just 23 elite postdoctoral scholars to be awarded the prestigious Banting Fellowship.
Allison Proffitt is a science writer with a background in biology and chemistry, research experience in cancer biology, and an expanding repertoire in biotech, AI, and battery chemistry. She serves as the editorial director for the Healthtech Publishing
media group, a growing collection of online news sites. In addition to Bio-IT World, her work has been published by Nature Biotech, Chemical & Engineering News, and the Economist Intelligence Unit. She has a bachelor’s degree in communication
of science, engineering, and technology from Vanderbilt University and a Master’s degree in science and medical writing from Johns Hopkins University.
Cost: No Cost!