On-Demand Webinar: Transcriptomics and Machine Learning to Improve Tumor Classification

Webinar: Performance assessment of RNA sequencing and expression arrays for transcriptome analysis in cancer research

RNA sequencing and expression arrays are transcriptomics techniques used to quantify transcribed genes and their isoforms. This presentation compares the performance of RNA-Seq versus arrays for the differential analysis of normal lung epithelium tissue and squamous cell carcinoma lung tumors.

In this webinar, Dr. Petr Nazarov will explain:

Results of platform comparison for protein-coding and long noncoding genes
Biases observed in RNA-Seq and expression array platforms
How deconvolution of transcriptomics data followed by machine learning can improve tumor classification

Speaker

Petr Nazarov, PhD
Research Scientist, Department of Oncology
Luxembourg Institute of Health

Dr. Nazarov has produced over 30 publications on biostatistics, machine learning and genomics. His recent work focuses on characterizing transcriptional variations in the peritumoral tissue environment of pancreatic cancer, as well as tumors originating from the lungs, colon, skin and brain. His current research leverages deconvolution of transcriptomic signals from heterogeneous tumors to improve cancer classification.

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For Research Use Only. Not for use in diagnostic procedures.