Applying Systems Biology and Predictive Genomic Analytics on Patients with Lung Squamous Cell Carcinoma and RNA-Seq Gene Expression

Date: Monday, September 14, 2015

Time: 11am EDT (NA) / 4pm BST (UK) / 5pm CEST (EU-Central)

Duration: 60 minutes

Featured Speakers:

• Scott Marshall, Ph.D., Managing Director, Analytics, Precision for Medicine
• Jared Kohler, Ph.D., Managing Director, Analytics, Precision for Medicine
• Tobias Guennel, Ph.D., Principal, Analytics, Precision for Medicine

In an upcoming webinar on September 14, 2015, Precision for Medicine will demonstrate how smart machine learning algorithms designed to incorporate information about molecular and cellular systems can revolutionize the ability to discover complex hierarchical genomic effects driving disease pathogenesis or severity and treatment response patterns.

Precision for Medicine will present a case study using PATH™, a new cloud-based predictive genomic analytics platform, on patients with lung squamous cell carcinoma and RNA-seq gene expression. You will learn how the the power of using a novel combination of machine learning algorithms with a systems biology based approach for identifying genes and the subsequent exonic regions driving prognosis for patients with lung squamous cell carcinoma (SQCC). PATH™ will be applied on 553 lung SQCC patients with survival outcomes and RNA-Seq exon-level mRNA expression data obtained from The Cancer Genome Atlas.

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