Author

Mahya Mehrmohamadi

University of TehranORCID 0000-0002-6681-0810Unclaimed ORCID profile · follow to get notified of new preprints

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Mahya Mehrmohamadi1 paper

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 1 Approach:Bayesian inference· 1 Research Focus:cell type annotation· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Hannie Yousefabadi· 1 shared Mahdi AnvariiD· 1 shared Niloofar TorkiiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

3 top collaborators · 1 mutual co-author link

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1 shared paperBioinformatics

Hannie Yousefabadi

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 4, 2026

The Segmentome: a novel representation of the DNA methylome identified by a Bayesian HMM framework

Mahdi Anvari, Niloofar Torki, Mahya Mehrmohamadi

The paper introduces the segmentome, a DNA methylome representation using a Bayesian HMM, and shows it can group cell types and identify cell-of-origin in DNA samples.

DOI 10.64898/2026.11.01.763464

humanDNA methylation

𝕏 PostBluesky

BioinformaticsPLoS Computational BiologyPeer-reviewedOct 5, 2026

Bioactivity-Driven Prediction of Antibacterial Synergy Using Machine Learning Models

Hannie Yousefabadi, Mahya Mehrmohamadi

This paper develops a machine learning framework to predict antibacterial synergy using multi-level bioactivity features and demonstrates its performance under rigorous cross-validation.

1 citation

bacteria (other)machine learning (classical)

𝕏 PostBluesky