August 27, 2020
10 am to 11 am EDT
Sponsored by
Webinar Description:
To understand and treat diseases, we need to understand the complex mechanisms of the underlying biological systems, and how they are affected. Protein interaction resources have proven a valuable tool
for this purpose in pharma R&D. This webinar will be centered around drug target identification facilitated by analysis of GWAS and omics data in combination with high confidence protein networks.
Learning Objectives:
- Why high-confidence protein interaction networks are an important supplement to pathways when interpreting biomedical data
- How analysis of biological networks can improve outcomes of data-driven target discovery analyses
- How you can interpret results from omics data analyses to gain biological insights
- Value of network analysis approach demonstrated through drug target identification benchmark and case study
Speakers:
Rasmus Wernersson
Scientific Director and Co-Founder
Intomics
Rasmus is co-founder and Scientific Director of Intomics A/S – one of the largest bioinformatics companies in Scandinavia, and he holds a position as external Associate Professor of Bioinformatics and Systems Biology at the Technical University
of Denmark. Rasmus has been working with Bioinformatics since the mid 1990s and has a dual background in Molecular Biology (MSc, University of Copenhagen, 1998) and software engineering (IT-D, Copenhagen University College of Engineering,
2006). Rasmus’ current research interests are centered around a network biology oriented approach to biomarker and drug target discovery.
Sara Nygaard
Global Product Manager
Intomics
Sara has 10 years of experience in applying biological interaction (PPI) network analyses to enhance performance in pharma projects within target and biomarker discovery, treatment response and drug repositioning. Now, she is dedicated to bringing
some of these tools into the hands of pharma R&D scientists, through Intomics’ inBio platform that allows for advanced data analyses and biological interpretation in the context of high confidence PPI-maps and supports collaboration
between bioinformaticians and biological scientists.
Cost: No cost!