Charles Danko is an Assistant Professor at Cornell University with 13 years of experience developing computational methods to decode how DNA sequence encodes gene expression and shapes evolution, development, and disease. He combines statistical modeling and machine learning with hands-on molecular genomics—designing and analyzing next-generation sequencing assays such as GRO-seq and RNA-seq—to link transcriptional mechanisms to biological function. His work includes novel HMM-based approaches to identify transcription units and genome-wide transcription rate estimation, reflecting a rare blend of algorithm development and experimental library preparation. Trained in bioinformatics (Ph.D.) and biomedical engineering, he has a track record of producing open, reusable tools (e.g., Bioconductor packages) and translating complex data into mechanistic insight.
13 years of coding experience
6 years of employment as a software developer
Johns Hopkins University
Doctor of Philosophy (Ph.D.), Bioinformatics, Doctor of Philosophy (Ph.D.), Bioinformatics at SUNY Upstate Medical University
Contributions:468 commits, 1 push in 4 years 8 months
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