Author

M. Edrisi

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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Cancer Biology· 4

Signature Assays, Organisms & Methods

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Organism:human· 4 Assay:whole-genome sequencing· 4 Approach:deep learning· 3 Approach:statistical model· 3 Research Focus:cell type annotation· 2 Research Focus:clustering· 2 Approach:Bayesian inference· 1 Research Focus:differential expression· 1

Frequent Co-Authors

H. Ogilvie· 4 shared L. Nakhleh· 4 shared D. Posada· 1 shared H. Zafar· 1 shared M. Li· 1 shared M. Valecha· 1 shared S. Chowdary· 1 shared S. Robledo· 1 shared

Activity by Year

2022-2022 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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4 shared papersCancer Biology

H. Ogilvie

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4 papers

Recent·Most cited

MaCroDNA: Accurate integration of single-cell DNA and RNA data for a deeper understanding of tumor heterogeneity

M. Edrisi, X. Huang, H. Ogilvie, L. Nakhleh

MaCroDNA integrates single-cell DNA and RNA data to better understand tumor heterogeneity, showing improved accuracy and speed over existing methods.

bioRxiv · Aug 21, 2022 · PreprintCancer Biology

MoTERNN: Classifying the Mode of Cancer Evolution Using Recursive Neural Networks

M. Edrisi, H. Ogilvie, M. Li, L. Nakhleh

This paper introduces MoTERNN, a recursive neural network that classifies cancer evolution modes from phylogenetic trees into four categories using simulated and real single-cell DNA sequencing data.

bioRxiv · Aug 21, 2022 · PreprintCancer Biology

Phylovar: Towards scalable phylogeny-aware inference of single-nucleotide variations from single-cell DNA sequencing data

M. Edrisi, M. Valecha, S. Chowdary, S. Robledo, H. Ogilvie, D. Posada, H. Zafar, L. Nakhleh

Phylovar improves scalability and accuracy of SNV detection in scDNAseq data by leveraging phylogenetic information, outperforming existing methods in speed and precision.

bioRxiv · Jan 16, 2022 · PreprintCancer Biology

NestedBD: Bayesian Inference of Phylogenetic Trees From Single-Cell DNA Copy Number Profile Data Under a Birth-Death Model

Y. Liu, M. Edrisi, H. Ogilvie, L. Nakhleh

This paper introduces NestedBD, a Bayesian method for inferring phylogenetic trees from single-cell DNA copy number data under a birth-death model, showing improved accuracy over existing methods.

bioRxiv · Jan 16, 2022 · PreprintCancer Biology