ATTENDEES CAN PRESENT THEIR SOLUTIONS TO EXPLORE CANCER GENOMIC DATA IN A BROAD RANGE OF APPLICATIONS SUCH AS (INCLUDING BUT NOT LIMITED):

1) Integrating Different Omics for Biomarker Discovery

2) Defining Gene Signature for Disease Progression, Survival and Treatments Response

3) Drug Discovery and Personalized Treatments

4) Characterization of Cancer Driver Genes and Mutation

5) Challenges in Machine Learning and Deep Learning in Genomics Data Classification

6) Discovering Tumor Subtypes from Genomics Data (Integrative Clustering)

To this end, participants can bring their own solutions and explore their potential, working in interdisciplinary teams or joining other participants and experts to propose ideas, proof-of-concept applications, etc.

A melanoma dataset and its associated paper from the TCGA are provided but teams are free to use data from any other type of tumors that have been made publicly available at the TCGA data portal.