Author

Leyla A. Garibova

Russian Academy of SciencesORCID 0000-0002-3250-4524Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 3 Approach:experimental assay· 2 Organism:human· 2 Research Focus:software / tool· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Organism:E. coli· 1

Frequent Co-Authors

Mark V. IvanoviD· 3 shared Mikhail V. GorshkoviD· 3 shared Daria D. EmekeevaiD· 2 shared Elizaveta M. KazakovaiD· 2 shared Irina A. TarasovaiD· 2 shared Valeriy I. PostoenkoiD· 2 shared Alexey A. NazaroviD· 1 shared Alexey V. TretyakoviD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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3 shared papersBioinformatics

Mark V. IvanovORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

msallsearchpy: Universal Search Engine with Enhanced Performance for High-Flow Quantitative LC-MS Proteomics

Mark V. Ivanov, Leyla A. Garibova, Daria D. Emekeeva, Valeriy I. Postoenko, Elizaveta M. Kazakova, Андрей Александрович Шелепчиков, Alexey V. Tretyakov, Irina A. Tarasova, Mikhail V. Gorshkov

The paper introduces msallsearchpy, a search engine for high-flow quantitative LC-MS proteomics, showing improved identification and quantification performance over existing methods.

bioRxiv · Oct 22, 2026 · PreprintBioinformatics

Study on the mechanism of action of the Pt(IV) complex with lonidamine ligands by ultrafast chemical proteomics

Ekaterina A.. Imaikina, Ivan I. Fedorov, Daria D. Emekeeva, Elizaveta M. Kazakova, Leyla A. Garibova, Mark V. Ivanov, Ilya A. Shutkov, Alexey A. Nazarov, Mikhail V. Gorshkov, Irina A. Tarasova

This study investigates the mechanism of action of a Pt(IV) complex with lonidamine ligands using chemical proteomics in ovarian cancer cells, revealing its impact on glucose metabolism.

ACS Pharmacology & Translational Science · Mar 28, 2025Peer-reviewedPharmacology & Toxicology

IQMMA: an efficient MS1 intensity extraction using multiple feature detection algorithms for DDA proteomics

Valeriy I. Postoenko, Leyla A. Garibova, Lev I. Levitsky, Julia A. Bubis, Mikhail V. Gorshkov, Mark V. Ivanov

IQMMA improves protein quantitation in DDA proteomics by integrating multiple feature detection algorithms to extract more accurate MS1 intensities.

bioRxiv · Feb 3, 2023 · PreprintBioinformatics