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Nathan Johnson, PhD
Dr. Johnson's publications
Education Bachelor of Science in Biology, Minor in Chemistry Evangel University, Springfield MO Research Paper: “Analyzing Capsaicin Levels in Dried Aged Chili Peppers using High Performance Liquid Chromatography (HPLC)” Masters of Biomedical Sciences University of Missouri, Columbia, MO Thesis Title: “Characterization of the Rat Embryonic Stem Cell Transcriptome by RNA-Seq” Ph.D. in Bioinformatics and Computational Biology Worcester Polytechnic Institute, Worcester, MA Dissertation Title: “Leveraging Omics Data to Expand the Value and Understanding of Alternative Splicing” Research Interests Understanding the molecular mechanisms involving the dysfunctional interplay of DNA, RNA, and protein that underlie the physical observations of disease is an exceedingly complicated undertaking. Over the past decade, there have been numerous methods, such as next generation sequencing (NGS), developed to allow systems wide identification and quantification of DNA, RNA, and to a lesser extent protein. While this allows an unprecedented ability to observe, it creates data that is difficult to understand patterns by a person due to its complexity that could be used to understand a disease progression and be exploited to create solutions. However, there are methods to detect patterns in the form of Artificial Intelligence and Machine Learning. My research interests rest on the desire of using machine learning paired with bioinformatics to extrapolate patterns that lead to better understanding of molecular mechanisms within disease. For example, I have had the pleasure of using machine learning to find patterns within RNA-Seq and epigenomics for acute lymphoblastic leukemia (ALL), microRNA detection within rat iPSC liver cells, single nucleotide variation within cancer on protein binding sites, alternative splicing within diabetes, alternative splicing patterns as related to protein function, the prediction of the effect alternative splicing on protein interaction, and de novo and genome RNA-Seq analysis of alternative splicing within parasitic nematodes in soybeans. Current Projects Analyzing RNA-Seq data for BH3 profiling for tumor associated macrophages (TAMs) within breast cancer to determine the patterns relating to whether a macrophage is close to the threshold of cell death (relatively "primed" for death), or relatively far from the threshold ("unprimed"). Evaluating and developing methods to analyze CycIF data (http://lincs.hms.harvard.edu/lin-natcommun-2015/) for ovarian and breast cancer. Exploring the effects of a first in class compound which polarizes macrophages to mitigate tumor regression in a mouse model to move into Phase I Clinical Trials through a sponsored research agreement with a pharmaceutical company. Interests Outside of Lab There is an outside? (couldn’t resist) Exploring New England, remodeling our home, landscaping/gardening, reading, camping Current position Investigator in Bioinformatics and Data Science at H3 Biomedicine |