Overview

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This course explores how molecular discoveries move from the biobank to the bedside, becoming validated tools doctors can actually trust. You'll see how researchers test whether a biological signal is more than a lab curiosity — proving it holds up statistically and clinically before it can guide real medical decisions. From there, you'll follow how vast biobanks of tissue and health records feed into the design of human clinical trials, where safety, ethics, and rigorous protocol shape every step from Phase 0 through Phase IV. Finally, you'll explore how researchers comb through the genome itself, sifting millions of genetic variants to find the small handful that actually cause disease and can be turned into new therapeutic targets. By the end of the course, you'll understand the full journey a discovery takes, from a raw genetic signal to a validated biomarker to an ethically sound clinical trial ready to reach patients. This course is especially useful for anyone curious about how modern medicine actually gets made, step by step, from the lab to the clinic.

Syllabus

Basic concepts of AI in bioinformatics data
- This module explores why so few promising laboratory discoveries ever become tests doctors can actually trust and use. You'll see how a measurable signal in the body earns the name "biomarker," and how it differs from a true clinical outcome versus a stand-in meant to represent one. From there, you'll follow a candidate biomarker through the staged process researchers use to prove it works reliably, including why results can shift once frozen lab samples are replaced with fresh patient specimens. By the end, you'll understand what separates a biomarker that stays a research curiosity from one that actually reaches the clinic.
Translational Medicine from Biobank research to clinical trials
- This module introduces how biobanks fuel clinical discovery through the intuitive "Recipe Box" model. Just as a recipe box stores ingredients and instructions for future use, a biobank stores biospecimens and patient data that researchers draw on to develop new treatments. The module covers what a biobank is and why it matters, how biobank data supports personalized medicine, a real-world case study tracing a biobank finding into a TMU clinical trial, and the phases and ethical foundations of clinical trials — including informed consent and lessons from the Tuskegee Syphilis Study.
How to identify the disease-causing locus in DNA sequence
- This module introduces the logic of gene mapping through the intuitive "Train Car" model. Picture two loci as passengers on a train: those seated in the same car tend to stay together as the train shuffles cars along the way, while those placed in distant cars are easily separated. This simple picture of distance and separation is what the recombination fraction (θ) actually measures. Building on this model, the module shows how family-based linkage analysis uses inheritance patterns to narrow down where a disease locus sits on a chromosome, and how association analysis and linkage disequilibrium (LD) are then used to fine-map that region down to a single causal variant. By the end of this module, learners will be able to explain what θ represents, distinguish linkage from linkage disequilibrium, and judge whether an observed marker-disease association is likely direct or indirect.

Taught by

Yi-Fan Chen

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