Qihang Li
Qihang Li is Ph.D. candidate in the Dept. of Computer Science and Engineering. He received B.S degree at Hangzhou Dianzi University in 2007, and M.S degree from Morehead State University in 2010. His research interests include machine learning-driven data analysis and data visualization. He has designed and programmed several visual analytics tools for bioinformatics. In 2013, his work “Observing Genomics and Phenotypical Patterns in the Developing Mouse Brain” won the 1st Place of 2013 IEEE Scientific Visualization Contest. Currently, he is focusing on the spatiotemporal pattern exploration and visualization of the developing brain.
Kelly Regan
I am an MD/PhD student and NLM CTRIP fellow at the Ohio State University. I received my BA in Biology (Immunology Specialization) from the University Chicago in 2011. My current graduate research training is in the field of Translational Biomedical Informatics. My thesis research project is focused on developing and validating computational approaches to enable drug repurposing and drug combination predictions for malignant melanoma using heterogeneous sources of high-throughput molecular “omics” and drug data.
Travis Johnson
I am a PhD candidate and NIH-NLM MIDAs fellow at the Ohio State University. I graduated from Ohio University with my BS in Environmental Plant Biology, specializing in molecular/cell biology and bioinformatics in 2014. In May 2016, I graduated with my MS in Public Health specializing in Biomedical Informatics (Thesis: Estimation of Neural Cell types in the Allen Human Brain Atlas using Murine-derived Expression Profiles). My work currently pertains to modeling and spatially mapping cell type expression profiles in the brain, RNA-Seq normalization, pseudogene homology to gene families and viral transcription in human gliomas.
Michael Sharpnack
I am an MD/PhD candidate at the Ohio State University who is broadly interested in methods that condense integrative high-dimensional datasets into biological and medical knowledge. I am currently applying and developing machine learning methods to integrative genomics and proteomics datasets to find novel biomarkers and treatments of cancer. I am specifically interested in combining transcriptomic and proteomic data to find novel biomarkers of lung cancer recurrence and progression.
I am a PhD student in the Biomedical Sciences Graduate Program and an NLM MIDAs fellow. I received my BS in Biochemistry from the University of Vermont in 2015. My current work is building towards research into preferential mutations of NRAS proteins in melanoma using publicly available data.
Yilan Liu
Yilan Liu is a Biochemistry and Applied Mathematics (Chemistry Track) dual major who is proficient is laboratory computer applications with a strong knowledge of statistical process control. Yilan Liu works on multiple projects through her research position at OSUMC using information to help nurses and practitioners better meet the needs of their patients.