Author

Ivan V. Gregoretti

Cell Signaling Technology (United States)ORCID 0000-0001-6965-2494Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Neuroscience· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 3 Approach:statistical model· 3 Assay:bulk RNA-seq· 2 Organism:human· 2 Assay:scRNA-seq· 2 Assay:ATAC-seq· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1

Frequent Co-Authors

Claire M. Simpson· 3 shared Sasha L. TkacheviD· 3 shared Tyler M. LevyiD· 3 shared Darya Yu. OrlovaiD· 2 shared Devon James EddinsiD· 2 shared Eliver GhosniD· 2 shared Evgeniy Tabatsky· 2 shared Majd ArissiD· 2 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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Curved chords = mutual co-authorship

3 shared papersBioinformatics

Claire M. Simpson

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

NeurosciencebioRxivPreprintMay 24, 2026

Brain shuttle target expression levels vary by individual, not by brain region, disease, age, or sex

Ana Raquel Santa-Maria, Sanjid Shahriar, Vasanth Chandrasekhar…·James R. Gorman

The paper shows brain shuttle target expression varies between individuals but not by brain region, disease, age, or sex.

DOI 10.64898/2026.05.21.726908

𝕏 PostBluesky

BioinformaticsbioRxivPreprintFeb 6, 2025

Cell signaling pathways discovery from multi-modal data

Changhan He, Claire M. Simpson, Ian Cossentino…·Darya Yu. Orlova

The paper introduces Incytr, a method for discovering cell signaling pathways from multi-omics data, demonstrating its application in disease contexts and showing its utility for drug discovery and understanding cell communication.

3 citations

humanbulk RNA-seq

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BioinformaticsGigaSciencePeer-reviewedJan 1, 2025

Lifting the curse from high dimensional data: Automated projection pursuit clustering for the variety of biological data modalities

Claire M. Simpson, Evgeniy Tabatsky, Zainab Rahil…·Darya Yu. Orlova

The paper introduces APP, a clustering method that reduces high-dimensional biological data to lower dimensions to improve clustering performance across multiple data types.

10 citations

bulk RNA-seqproteomics

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