Alla Mikheenko

Alla Mikheenko

Postdoctoral Research Fellow

University College of London

Biography

I am currently a postdoc at Pietro Fratta’s lab at University College London, focusing on applying computational methods to exploring mechanisms of neurodegeneration. My research interests also include development of novel tools and algorithms for the analysis of genomic, transcriptomic, and proteomic data.

Interests
  • Omics data analysis
  • Algorithmic bioinformatics
  • Neuroscience
  • Neurodegenerative diseases
Education

  • PhD in Bioinformatics, 2021

    Center of Algorithmic Biotechnology, Saint Petersburg State University, Russia

  • Doctor of Medicine, 2014

    Ulyanovsk State University, Russia

Skills

Programming

Proficiency: Python (Pandas, Numpy, Scikit-learn, etc), R, Bash. HTML/CSS + Javascript.

Algorithms

Algorithms and data structures, bioinformatics algorithms, algorithms design and implementation for large-scale data analysis

Machine learning

Supervised/unsupervised machine learning, ensemble methods, regularization and optimization, deep learning

Genomics

Next‐generation and long‐read genome sequencing data, metagenomics, ChIP‐seq

Transcriptomics & Proteomics

Single‐cell, spatial, bulk RNA‐Seq data. Mass-spectrometry‐based quantitative proteomics data

Miscellaneous

Git, LaTeX, cluster management systems (slurm, qsub), various bioinformatics software.

Projects

Molecular mechanisms of neurodegeneration

Investigating role of TDP-43 pathology in neurodegenerative diseases (papers in preparation)

C9orf72-related neurodegenerative diseases

Exploration of genes and pathways affected in C9orf72-mediated ALS and FTD

Preprint
Telomere-to-Telomere (T2T) consortium

High-precision read alignment algorithms developed for the first truly complete human genome assembly.

T2T main paper TandemTools paper VerityMap paper VerityMap code
Long-read RNA-seq data analysis

Development of novel tools and algorithms for long-read RNA-sequencing data

IsoQuant paper IsoQuant code Sequencing platform comparison Scripts for data analysis
Genomic data analysis

Key developer & maintainer of QUAST tool for versatile evaluation of genome assemblies

Publication Website Code

Publications

Andrey D Prjibelski, Alla Mikheenko, Anoushka Joglekar, Alexander Smetanin, Julien Jarroux, Alla L Lapidus, Hagen U Tilgner (2023). Accurate isoform discovery with IsoQuant using long reads. Nature Biotechnology.

Cite

Carmelo Milioto, Mireia Carcole, Ashling Giblin, Rachel Coneys, Olivia Attrebi, Mhoriam Ahmed, Samuel S Harris, Byung Il Lee, Mengke Yang, Raja S Nirujogi, et al (2023). PolyGR and polyPR knock-in mice reveal a conserved neuroprotective extracellular matrix signature in C9orf72 ALS/FTD neurons. bioRxiv.

Cite

Francisco J Pardo-Palacios, Dingjie Wang, Fairlie Reese, Mark Diekhans, Sı́lvia Carbonell-Sala, Brian Williams, Jane E Loveland, Maite De Maria, Matthew S Adams, Gabriela Balderrama-Gutierrez, et al (2023). Systematic assessment of long-read RNA-seq methods for transcript identification and quantification. bioRxiv.

Cite

Arang Rhie, Sergey Nurk, Monika Cechova, Savannah J Hoyt, Dylan J Taylor, Nicolas Altemose, Paul W Hook, Sergey Koren, Mikko Rautiainen, Ivan A Alexandrov, et al (2023). The complete sequence of a human Y chromosome. Nature.

Cite

Alla Mikheenko, Vladislav Saveliev, Pascal Hirsch, Alexey Gurevich (2023). WebQUAST: online evaluation of genome assemblies. Nucleic Acids Research.

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See all publications

Teaching Positions

NGS Data Analysis (2022) - Sirius University of Science and Technology, Russia
The course is designed for Master’s students with biology background. The goals of this course are to learn the essential programming skills for bioinformatics, understand NGS technology and algorithms, and use bioinformatics tools for analysis of sequencing data.
NGS Data Analysis (2022) - Sirius University of Science and Technology, Russia
Introduction to Bioinformatics (2021) - St. Petersburg State University, Russia
The course is designed for Master’s students with biology background. In this course we discuss following topics: basic bioinformatic challenges; algorithms and tools for genome assembly; analysis of DNA-seq and RNA-seq data. Students learn to work in Linux environment, install and run various bioinformatics tools.
Introduction to Bioinformatics (2021) - St. Petersburg State University, Russia