Ian Hong

Project

Validation of Gujral machine learning model

The Gujral model has already produced predicted data on cell viability for relevant kinase inhibitors, my role in this project is to assist in completing the validation of that regression output. 25 nonspecific kinase inhibitors with predicted impact scores reflecting “no effect”, “moderate effect”, and “potent effect” on cell viability will be tested on two human urothelial bladder cancer cell lines (COCAB1 & SW780) and three human squamous bladder cancer cell lines (COCAB11, UMUC5, & SCABER).

What I learned

I have learned that it is important to make every trial of the experiment worth it. For the amount of time and resources that go into every trial, if I make human error, that pushes back the progress of my experiment significantly.

Advice for future applicants

It is okay to be anxious and nervous during the beginning phases of experimentation. But just embrace the difficulties of research and really try to absorb as much as you can and eventually your research will start to make sense.

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