Anna Plaksienko

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Academic interests

I work on high-dimensional regression (large p, small n) in the context of undirected graphical models in the case of data coming from multiple sources. During my PhD and my first postdoc period I worked on joint estimation, while currently I am focusing on direct differential network estimation. 

I am curious about omics analysis, especially multi-omics data integration. I have experience with RNA-Seq, methylation and lipidomics data. My preferred coding language is R and I enjoy teaching and science popularization.

Background

Relevant work experience
  • Postdoctoral fellow (assegno di ricerca) at the Institute of Applied Calculus of the national Research Council (Naples, Italy, July 2021 - July 2022)
Education
  • PhD in Mathematics in Natural, Social and Life Sciences (Gran Sasso Science Institute, L'Aquila, Italy, 2021)
  • BSc in Mathematics (Novosibirsk State University, Novosibirsk, Russia, 2016)
Tags: Biostatistics, Biostatistikk, graphical models, differential networks, stability selection, error control, regression, omics, R

Publications

Major contribution

Minor contribution

R packages 

  • jewel on CRAN – estimates networks of conditional dependencies from multiple classes of data
  • methyLImp2 on Bioconductor – imputes missing values in DNA methylation data. 
Published Feb. 28, 2023 11:48 AM - Last modified Jan. 16, 2025 9:59 AM

Research groups