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Principal Investigator


Megha Padi

After studying biology and physics at MIT, I completed my Ph.D. in high-energy theoretical physics from Harvard. I then became excited about creating mathematical models to make sense of the large volumes of data emerging from new genomic and high-throughput technologies. After conducting postdoctoral work in computational and systems biology with John Quackenbush and Galit Lahav, I started my lab at the University of Arizona in 2018. I also lead the bioinformatics team at the University of Arizona Cancer Center.

Current members


Jiawen Yang, PhD student in Cancer Biology

After finishing my BS in clinical pharmacy and MS in pharmacology, I joined the CBIO program at the University of Arizona with enthusiasm for cancer genomics. My research is focusing on discovering carcinogenesis mechanisms through analyzing cancer genomic profiles; In the prostate cancer project, a collaboration project with the Rogers lab, I am specifically interested in studying how centrosome-loss alters genomic structure and activates oncogenic changes in prostate epithelial cells. I am also interested in investigating how transcriptional regulatory changes activate the neuroendocrine transition in Merkel cell carcinoma and lead to highly aggressive features of this tumor.


Dante Bellomo, PhD student in Cancer Biology

My research involves analyzing the genomic and epigenomic profiles of early onset Colorectal cancer.  Through identification of upregulated genes and molecular signaling networks, I aim to determine the alternative mechanisms of carcinogenesis these tumors undergo as many of them lack a mutation in the APC gene, which is very often mutated in the canonical model of later-onset Colorectal cancer.


Mireya Herrera-Herrera, PhD

In addition to managing our wet-lab operations and equipment, Mireya works on creating new cell line models of Merkel cell carcinoma and characterizing their molecular and cellular phenotypes.


Cora Ricoy, Master's student in Applied Biosciences

Cora uses WGCNA to investigate the correlation networks underlying the development of Merkel cell carcinoma and identify drivers of neuroendocrine cell fate.


Jing Han Ong, Master's student in Genetics

JingHan infers TF activity levels and identifies master regulators driving development of Merkel cell carcinoma.


Isabella Viney, PhD student in Genetics

Izzy is characterizing the development of Merkel cell carcinoma using a combination of wet-lab experiments, network simulations, and single-cell analysis.


Waldo Guzman Barrientos, Undergraduate

Waldo is majoring in Computer Science and Molecular and Cellular Biology, and is working on combining Boolean network simulations of Merkel cell carcinoma with Western Blot analysis in the lab.

Orhan Gozutok, Undergraduate

Orhan is working on Boolean network simulations of Merkel cell carcinoma.

Sarah Wolff, Undergraduate

Sarah is working on wet-lab experiments characterizing cell line models of Merkel cell carcinoma.

Baris Kerimoglu, PhD - Postdoctoral Fellow

Baris is using genomics, bioinformatics, and single-cell experiments to characterize the drivers of neuroendocrine state transition in Merkel cell carcinoma.

Former members

Chen Chen, PhD student in Biostatistics

Current Role: Postdoctoral Fellow, Harvard School of Public Health

Adam Grant, CBio PhD student

Current Role: Bioinformatician

James Lim, Postdoctoral fellow

Current Role: Bioinformatician, Monoceros

Paris Vail, Research technician

Calsey Richardson, PREP post-baccalaureate

Current Role: Biology instructor

Vivian Nguyen, undergraduate researcher

Emily Galloway, UBRP fellow

Faith Kennedy, UBRP x Data Science Fellow

Current Role: PhD student


Chen Chen, PhD student

I am a Biostatistics Ph.D. student. My research is focused on cancer omics data analysis and developing new bioinformatics tools. I am particularly interested in using network science and machine learning models to answer basic and translational biological questions, such as disease module detection, driver TF identification, drug response prediction and biomarker discovery. 

Faith Kennedy.jpg

Faith Kennedy, UBRP x Data Science Fellow

As a dual major in Molecular & Cellular Biology and Statistics & Data Science, I’m excited about mathematical applications in biology. Being at the intersection of these topics allows me to perform analyses on complex datasets, while tailoring them to specific biological problems and interpreting results with the whole system in mind. In my current project studying Merkel cell carcinoma, I’m working to identify key interactions between genes by analyzing genomic data using network analysis. My goal is to increase understanding of how this particular cancer develops and find new targets for treatment.

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