Alexey A. Sergushichev, PhD
Currently
I am a bioinformatics group leader at ITMO University, leading development of computational methods and software for omics data analysis.
Employment
2022 — now
Washington University in St. Louis, Department of Pathology & Immunology, Visiting Professor
2017 - now
ITMO University, Information Technologies and Programming Faculty, Assistant Professor
2010 - 2017
ITMO University, Information Technologies and Programming Faculty, Researcher
2013, 2015, 2017
Washington University in St. Louis, Department of Pathology & Immunology, Visiting Researcher
Education
2013-16
ITMO University Bioinformatics PhD (supervisors: Maxim Artyomov and Anatoly Shalyto)
2011-13
ITMO University MSc with honors in Computer Science
2007-11
ITMO University BSc with honors in Computer Science
Projects
FGSEA
FGSEA is an R package that implements a novel algorithm for fast gene set enrichment analysis, based on Multilevel Monte Carlo Approach. The fast algorithm allows to achieve qualitatively higher precision in calculating GSEA P-values and allows more accurate pathway prioritization. Links: R package, source code, manuscript.
Phantasus
Phantasus is a web tool designed for visual and interactive gene expression analysis. In particular, it was designed to allow going from a typical dataset to differential expression and downstream analysis in an easy and streamlined manner. For that aim, Phantasus integrates an intuitive heatmap interface with gene expression analysis tools from Bioconductor. Links: https://ctlab.itmo.ru/phantasus/, R package, source code, manuscript.
GAM/GATOM
GAM and its upgrade GATOM are methods for integrated network analysis of transcriptional and steady-state metabolomic data focused on identification of the most changing metabolic subnetworks between two conditions of interest. Links: Shiny GATOM, source code, manuscript.
Main publications
2023
D Mogilenko, A Sergushichev, MN Artyomov. Systems Immunology Approaches to Metabolism. Annual Review of Immunology, doi:10.1146/annurev-immunol-101220-031513.
A Gainullina, …, A Sergushichev, MN Artyomov, ImmGen Consortium. Network analysis of large-scale ImmGen and Tabula Muris datasets highlights metabolic diversity of tissue mononuclear phagocytes. Cell Reports, doi:10.1016/j.celrep.2023.112046.
2022
M. Kleverov, …, A Sergushichev. Phantasus: web-application for visual and interactive gene expression analysis. bioRxiv, doi:10.1101/2022.12.10.519861.
M. Emelianova, A Gainullina, …, A Sergushichev. Shiny GATOM: omics-based identification of regulated metabolic modules in atom transition networks. Nucleic Acids Research, doi:10.1093/nar/gkac427.
2021
G Korotkevich, V Sukhov, N Budin, B Shpak, MN Artyomov, A Sergushichev. Fast gene set enrichment analysis. bioRxiv, doi:10.1101/060012.
J Merlin, S Ivanov, A Dumont, A Sergushichev et al. Non-canonical glutamine transamination sustains efferocytosis by coupling redox buffering to oxidative phosphorylation. Nature Metabolism, doi:10.1038/s42255-021-00471-y.
2020
N Alexeev, J Isomurodov, V Sukhov, G Korotkevich, A Sergushichev. Markov chain Monte Carlo for active module identification problem. BMC Bioinformatics, doi:10.1186/s12859-020-03572-9.
A Gainullina, …, A Sergushichev, MN Artyomov, ImmGen Consortium. Open Source ImmGen: network perspective on metabolic diversity among mononuclear phagocytes. bioRxiv, doi:10.1101/2020.07.15.204388.
2019
L Pelgrom, T Patente, A Sergushichev et al. LKB1 expressed in dendritic cells governs the development and expansion of thymus-derived regulatory T cells. Cell Research, doi:10.1038/s41422-019-0161-8.
2018
M Bambouskova, L Gorvel, V Lampropoulou, A Sergushichev et al. Electrophilic properties of itaconate and derivatives regulate the IκBζ-ATF3 inflammatory axis. Nature, doi:10.1038/s41586-018-0052-z.
2017
TK Ulland, WM Song, SCC Huang, JD Ulrich, A Sergushichev et al. TREM2 Maintains Microglial Metabolic Fitness in Alzheimer’s Disease. Cell, doi:10.1016/j.cell.2017.07.023.
JE Isomurodov, AA Loboda, AA Sergushichev. Ranking Vertices for Active Module Recovery Problem. Algorithms for Computational Biology 2017, doi:10.1007/978-3-319-58163-7_5.
2016
MN Artyomov, A Sergushichev, JD Schilling. Integrating immunometabolism and macrophage diversity. Seminars in Immunology, doi:10.1016/j.smim.2016.10.004
V Lampropoulou, A Sergushichev et al. Itaconate Links Inhibition of Succinate Dehydrogenase with Macrophage Metabolic Remodeling and Regulation of Inflammation. Cell Metabolism, doi:10.1016/j.cmet.2016.06.004
AA Loboda, MN Artyomov, AA Sergushichev. Solving generalized maximum-weight connected subgraph problem for network enrichment analysis. Workshop on Algorithms in Bioinformatics 2016, doi:10.1007/978-3-319-43681-4_17.
AA Sergushichev et al. GAM: a web-service for integrated transcriptional and metabolic network analysis. Nucleic Acids Research, doi:10.1093/nar/gkw266
2015
EE Vincent, A Sergushichev et al.
Mitochondrial Phosphoenolpyruvate Carboxykinase Regulates Metabolic Adaptation and Enables Glucose-Independent Tumor Growth.
Molecular cell, doi:10.1016/j.molcel.2015.08.013
AK Jha, SCC Huang, A Sergushichev et al. Network integration of parallel metabolic and transcriptional data reveals metabolic modules that regulate macrophage polarization. Immunity, doi:10.1016/j.immuni.2015.02.005
2013
AV Aleksandrov, SV Kazakov, AA Sergushichev, FN Tsarev, AA Shalyto The use of evolutionary programming based on training examples for the generation of finite state machines for controlling objects with complex behavior. Journal of Computer and Systems Sciences International, doi:10.1134/S1064230713020020
2011
A Alexandrov, A Sergushichev, S Kazakov, F Tsarev.
Genetic algorithm for induction of finite automata with continuous and discrete output actions.
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, doi:10.1145/2001858.2002089