Author

Olexander Moskalenko

University of Florida

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Assay:metabolomics· 2 Approach:statistical model· 2 Organism:C. elegans· 1 Research Focus:dimensionality reduction· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Alison M. MorseiD· 2 shared Ana ConesaiD· 2 shared Francisco HuertasiD· 2 shared Lauren M. McIntyreiD· 2 shared Coleen Tara MurphyiD· 1 shared Danielle E. MoriD· 1 shared Gary Wright MilleriD· 1 shared Marta LlansolaiD· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersNeuroscience

Alison M. MorseORCID

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2 papers

Recent·Most cited

GAIT-GM integrative cross-omics analyses reveal cholinergic defects in a C. elegans model of Parkinson's disease

Danielle E. Mor, Francisco Huertas, Alison M. Morse, Rachel L. Kaletsky, Coleen Tara Murphy, Vrinda Kalia, Gary Wright Miller, Olexander Moskalenko, Ana Conesa, Lauren M. McIntyre

The paper introduces GAIT-GM, a Galaxy tool for multi-omics analysis, and finds a link between branched-chain amino acid metabolism and cholinergic neuron defects in a C. elegans Parkinson's disease model.

bioRxiv · Jul 16, 2021 · PreprintNeuroscience

GAIT-GM: Galaxy tools for modeling metabolite changes as a function of gene expression

Lauren M. McIntyre, Francisco Huertas, Olexander Moskalenko, Marta Llansola, Vicente Felipo, Alison M. Morse, Ana Conesa

GAIT-GM provides Galaxy tools for integrating gene expression and metabolomics data through pathway-based analysis and flexible modeling of metabolite changes.

bioRxiv · Dec 25, 2020 · PreprintBioinformatics