Gonzalo Lopez

Scientific Associate Director

New York, New York, United States
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Summary

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Senior
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Top School
Gonzalo Lopez is an accomplished translational bioinformatics leader with over a decade of experience applying integrative genomics, systems biology, and real-world data to oncology and precision medicine. Currently Associate Director of Oncology Data Science at Novartis, he has led discovery-to-development efforts at Bristol Myers Squibb and academic translational research as an Assistant Professor at Mount Sinai. His work spans pediatric and adult cancers, with a track record of identifying patient subgroups and novel therapeutic targets through multi-modal data and reverse translation. Trained as a PhD molecular biologist, he combines deep computational tool-building from his doctoral work with hands-on collaborative science that has produced high-impact publications and cross-institutional consortia contributions. Notably, he transitioned successfully between academia and industry, retaining a focus on clinically actionable insights that improve diagnosis and outcomes for hard-to-treat diseases.
code10 years of coding experience
job11 years of employment as a software developer
bookDoctor of Philosophy - PhD, Molecular Biology, Cum Laude, Doctor of Philosophy - PhD, Molecular Biology, Cum Laude at Universidad Autónoma de Madrid
bookMaster, Bioinformatica y Biología Computacional, Master, Bioinformatica y Biología Computacional at Universidad Complutense de Madrid
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Github Skills (3)

bioinformatics8
atlas5
bioconductor3

Programming languages (2)

RHTML

Github contributions (5)

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gonzolgarcia/svpluscnv

Dec 2019 - Feb 2020

Integrative Structural Variant analysis
Contributions:47 commits, 1 PR, 80 pushes in 2 months
bioinformaticsvariant-analysisstructural
ccbiolab/svpluscnv

Mar 2020 - Sep 2020

Integrative analysis of complex structural variants
Contributions:25 commits, 2 PRs, 35 pushes in 6 months
integrative-analysisbioinformaticsstructural-variantsstructural
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Gonzalo Lopez - Scientific Associate Director