Precision medicine is changing the way we understand, diagnose and treat cancer. The transformation is driven by high-throughput molecular data from patients, animal models, and large-scale experiments. In this program, we will explore how the various -omics data types can be analyzed to understand the basic biology associated with cancer onset, development, and outcomes and see how large-scale clinical trials and experiments provide an opportunity to improve precision oncology. More about the program and the schedule is found here: https://edu.t-bio.info/bioinformatics-training-precision-oncology/
Cancer biology challenges (organs, tissues, cells) Molecular factors in tumor development, growth and metastasis Clinical and Molecular Data (phenotype-genotype relationship) Associated online course/resource: https://www.ncbi.nlm.nih.gov/books/NBK20362/
From Hypothesis Testing to Data Mining Statistics and Algorithms T-BioInfo Platform and relevant analysis methods Associated online course/resource: Introduction to Bioinformatics
Processing (germline and somatic mutations) Analysis (mapping, detecting variants) Interpretation (significant and insignificant mutations, etc.) Associated online course/resource: Transcriptomics 1
Processing (mapping, quantification) Analysis (differential gene expression, factor regression analysis) Interpretation (gene ontologies and Gene Set Enrichment Analysis)
NCBI (cell lines, animal models) TCGA (patient cohorts) NCI, COSMIC (databases of mutations and interactions
Scientific Inquiry and Translational Value Example 1: Breast Cancer – classification of subtypes (cell lines) Example 2: Liver Cancer – risks and molecular factors...