Author

Laura H. Tung

Carnegie Mellon University

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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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:bulk RNA-seq· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:long-read sequencing· 1

Frequent Co-Authors

Carl KingsfordiD· 2 shared Mingfu ShaoiD· 1 shared

Activity by Year

2019-2021 · peak 1/yr

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2 top collaborators · 1 mutual co-author link

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2 shared papersBioinformatics

Carl KingsfordORCID

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2 papers

Recent·Most cited

BioinformaticsBioinformaticsPeer-reviewedApr 30, 2021

Practical selection of representative sets of RNA-seq samples using a hierarchical approach

Laura H. Tung, Carl Kingsford

The paper introduces a hierarchical method to select representative RNA-seq samples from large databases, achieving significant runtime and memory reductions while maintaining performance comparable to direct methods.

3 citations

bulk RNA-seqstatistical model

𝕏 PostBluesky

BioinformaticsGenome biologyPeer-reviewedDec 1, 2019

Quantifying the Benefit Offered by Transcript Assembly on Single-Molecule Long Reads

Laura H. Tung, Mingfu Shao, Carl Kingsford

This paper evaluates how transcript assembly improves transcriptome analysis using long-read sequencing, showing Scallop-LR identifies more known transcripts and novel isoforms than Iso-Seq Analysis.

23 citations

humanmouse

𝕏 PostBluesky