Author

Kimberly MacKay

University of SaskatchewanORCID 0000-0001-6417-725XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Research Focus:dimensionality reduction· 3 Assay:Hi-C· 3 Organism:yeast· 3 Approach:statistical model· 2 Approach:graph neural network· 1 Approach:optimal transport· 1 Research Focus:variant calling· 1

Frequent Co-Authors

ANTHONY J. KUSALIKiD· 3 shared Christopher H. EskiwiD· 1 shared Mats CarlssoniD· 1 shared

Activity by Year

2018-2020 · peak 2/yr

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3 top collaborators · 2 mutual co-author links

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3 shared papersBioinformatics

ANTHONY J. KUSALIKORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJan 28, 2020

StoHi-C: Using t-Distributed Stochastic Neighbor Embedding (t-SNE) to predict 3D genome structure from Hi-C Data

Kimberly MacKay, ANTHONY J. KUSALIK

StoHi-C uses t-SNE to predict 3D genome structures from Hi-C data, improving the clarity of fission yeast genomic organization principles.

2 citations

𝕏 PostBluesky

BioinformaticsbioRxivPreprintAug 16, 2018

SonHi-C: a set of non-procedural approaches for predicting 3D genome organization from Hi-C data

Kimberly MacKay, Mats Carlsson, ANTHONY J. KUSALIK

The paper introduces non-procedural methods for 3D genome reconstruction from Hi-C data, showing they can accurately model fission yeast genome structure.

DOI 10.1101/392407

𝕏 PostBluesky

BioinformaticsBMC Research NotesPeer-reviewedJun 29, 2018

GrapHi-C: Graph-based visualization of Hi-C Datasets

Kimberly MacKay, ANTHONY J. KUSALIK, Christopher H. Eskiw

The paper develops a graph-based visualization method for Hi-C datasets to better represent 3D genomic organization, showing improved insights into genome structure changes in a fission yeast mutant.

11 citations

𝕏 PostBluesky