Felipe da Veiga Leprevost

Biological Data Science & Visualization

About Me

I am a molecular biologist, and systems analyst by training with extensive hypothesis-driven research experience and strong skills in bioinformatics data analysis, data wrangling, statistical analysis, and data visualization.

I have almost twenty years of experience in wet-lab, cell biology, molecular biology, molecular parasitology, genomics, and proteomics.

My Research

My research concentrates on the area of bioinformatics, proteomics, and data integration. I am particularly interested in mass spectrometry-based proteomics, software development for proteomics, cancer proteogenomics, and transcriptomics. The computational methods and tools previously developed by my colleagues and me, such as PepExplorer, MSFragger, Philosopher, and PatternLab for Proteomics, are among the most referred proteome informatics tools and are used by hundreds of laboratories worldwide.

I am also a Proteogenomics Data Analysis Center (UM-PGDAC) member as part of the NCI’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) initiative for processing and analyzing hundreds of cancer proteomics samples. UM-PGDAC develops advanced computational infrastructure for comprehensive and global characterization of genomics, transcriptomics, and proteomics data collected from several human tumor cohorts using NCI-provided biospecimens. Since 2019 I have been working as a bioinformatics data analyst with the University of Michigan Proteomics Resource Facility, which provides state of the art capabilities in proteomics to the University of Michigan investigators, including Rogel Cancer Center investigators as Proteomics Shared Resource.


Contact

Dr. Felipe da Veiga Leprevost


Research faculty at University of Michigan Medical School
Associate faculty at the Michigan Institute for Data Science - MIDAS
Member of the Rogel Cancer Center
Biological Data Sciences • Bioinformatics • Data Analysis • Proteomics
Department of Pathology
Ann Arbror, MI, USA
felipevl@umich.edu


Curriculum Vitae

Education & Professional Experience

  • Research Faculty (since 2019)
    • University of Michigan, pathology department, Ann Arbor, USA
    • Services: Software development for computational proteomics, bioinformatics support analysis
  • Research Fellow (2015-2019)
    • University of Michigan, pathology department, Ann Arbor, USA
    • Services: Software development for computational proteomics, bioinformatics support analysis
  • Research Fellow (2014-2015)
    • Fiocruz - Laboratory for Computational and Strucutural Proteomics, Curitiba, Brazil
    • Topics: Proteomics, mass spectrometry
  • Ph.D. in Bioinformatics (2014-2015)
    • Fiocruz - Laboratory for Computational and Strucutural Proteomics, Curitiba, Brazil
    • Topics: Proteomics, mass spectrometry
    • Thesis: PepExplorer: a similarity-driven tool for analyzing de novo sequencing results
  • B.Tech in Systems Analysis & Development (2010-2014)
    • Positivo University, Curitiba, Brazil
    • Thesis: Development of a distributed system for hospital-based digital signage
  • MS in Molecular & Cellular Biology (2006-2009)
    • Fiocruz, Rio de Janeiro, RJ
    • Thesis: Characterization of genes with unknown function with expression associated to infective forms of Trypanosoma cruzi
  • Intership in Molecular Biology (2006)
    • Parana Federal University, Diagnostic Center Marcos Enrietti
    • Tasks: Cultivation and handling of Apicomplexa parasites
  • Intership in Parasitology (2005)
    • Positivo University, Curitiba, Brazil
    • Tasks: Microscopical identification of micro-parasites
  • Bsc in Biology (2003-2006)
    • Positivo University, Curitiba, Brazil
    • Thesis: Recombinant antibody production against Trypanosoma cruzi proteins by Phage Display

    Teaching

    • “Perl for Bioinfromatics”
      (Masters program in Molecular & Cellular Biology, Fiocruz , 2012–2014)

    Selected Publications

    • Gillette MA, Satpathy S, Cao S, et al. Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma. Cell. 2020;182(1):200-225.e35.

    • Clark DJ, Dhanasekaran SM, Petralia F, et al. Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma Cell. 2019;179(4):964-983.e31.

    • da Veiga Leprevost F, Haynes SE, Avtonomov DM, et al. Philosopher: a versatile toolkit for shotgun proteomics data analysis. Nat Methods. 2020;17(9):869-870.

    • Kong AT, da Veiga Leprevost F, Avtonomov DM, Mellacheruvu D, Nesvizhskii AI. MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics. Nat Methods. 2017;14(5):513-520.

    Full List of Publications

    Skills

    • Languages: Brazilian Portuguese (native), English (fluent)
    • Programming: Perl, Go, R, C#, Java, CSS, html, SQL/SQLite
    • Statistics: R (e.g. lm4, glmmTMB, CARBayesST, adehabitat, broom, tidytext, tidymodels)
    • Visualization: R (e.g. ggplot2, Shiny, plotly, echarts4r, leaflet, tmap, gganimate)
    • Markup: Markdown, R (e.g. Rmarkdown, blogdown, bookdown, xaringan), LaTeX

    Memberships & Services