Author

G. Yazgı Tütüncü

Centre National de la Recherche ScientifiqueORCID 0000-0002-9363-6141Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Göknur GineriD· 2 shared Necla KoçhaniD· 2 shared Gordon K. SmythiD· 1 shared Luke C. GandolfoiD· 1 shared

Activity by Year

2019-2020 · peak 1/yr

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4 top collaborators · 6 mutual co-author links

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2 shared papersBioinformatics

Göknur GinerORCID

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2 papers

Recent·Most cited

BioinformaticsExpert Systems with ApplicationsPeer-reviewedNov 2, 2020

A new local covariance matrix estimation for the classification of gene expression profiles in RNA-Seq data

Necla Koçhan, G. Yazgı Tütüncü, Göknur Giner

This paper introduces a local covariance matrix estimation method for RNA-Seq data classification, showing improved performance over traditional methods.

9 citations

bulk RNA-seqstatistical model

𝕏 PostBluesky

BioinformaticsPeerJPeer-reviewedDec 18, 2019

qtQDA: quantile transformed quadratic discriminant analysis for high-dimensional RNA-seq data

Necla Koçhan, G. Yazgı Tütüncü, Gordon K. Smyth…·Göknur Giner

The paper introduces qtQDA, a classification method for RNA-seq data that uses quantile transformation and regularized QDA, showing good performance on real datasets.

8 citations

bulk RNA-seqstatistical model

𝕏 PostBluesky