Author

Nathaniel T. Hawkins

Michigan State UniversityORCID 0000-0002-7193-4113Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Approach:machine learning (classical)· 1 Assay:scRNA-seq· 1 Approach:statistical model· 1

Frequent Co-Authors

Anna YannakopoulosiD· 1 shared Anthony SzedlakiD· 1 shared Arjun KrishnaniD· 1 shared Carlo PiermarocchiiD· 1 shared Giovanni PaternostroiD· 1 shared Jiayin WangiD· 1 shared Lindsay A. GuareiD· 1 shared Marc MaldaveriD· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 16 mutual co-author links

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1 shared paperBioinformatics

Anna YannakopoulosORCID

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2 papers

Recent·Most cited

Systematic tissue annotations of -omics samples by modeling unstructured metadata

Nathaniel T. Hawkins, Marc Maldaver, Anna Yannakopoulos, Lindsay A. Guare, Arjun Krishnan

The paper develops an NLP-ML approach to annotate -omics samples with tissue and cell-type labels using free-text metadata, outperforming existing methods and demonstrating biological relevance.

bioRxiv · May 10, 2021 · PreprintBioinformatics

Polled Digital Cell Sorter (p-DCS): Automatic identification of hematological cell types from single cell RNA-sequencing clusters

Sergii Domanskyi, Anthony Szedlak, Nathaniel T. Hawkins, Jiayin Wang, Giovanni Paternostro, Carlo Piermarocchi

The paper introduces a tool for automatically assigning cell types to scRNA-seq clusters using a voting algorithm based on molecular markers, validated on bone marrow data from the Human Cell Atlas.

BMC Bioinformatics · Jul 1, 2019Peer-reviewedBioinformatics