Author

Mustafa Coşkun

Abdullah Gül UniversityORCID 0000-0003-4805-1416Unclaimed 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:drug response / drug discovery· 2 Approach:graph neural network· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:contrastive learning· 1 Research Focus:protein design· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Mehmet KoyutürkiD· 3 shared Filipa Blasco Tavares Pereira LopesiD· 1 shared Mark R. ChanceiD· 1 shared Pınar Kubilay TolunayiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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3 shared papersBioinformatics

Mehmet KoyutürkORCID

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3 papers

Recent·Most cited

BioinformaticsJournal of Computational BiologyPeer-reviewedOct 9, 2026

scProfiterole: Clustering of Single-Cell Proteomic DataUsing Graph Contrastive Learning via Spectral Filters

Mustafa Coşkun, Filipa Blasco Tavares Pereira Lopes, Pınar Kubilay Tolunay…·Mehmet Koyutürk

The paper introduces scProfiterole, a framework for clustering single-cell proteomic data using graph contrastive learning with spectral filters, showing improved cell type identification.

DOI 10.1177/15578666261491608

proteomicsgraph neural network

𝕏 PostBluesky

BioinformaticsbioRxivPreprintNov 5, 2021

Multiplex Embedding of Biological Networks Using Topological Similarity of Different Layers

Mustafa Coşkun, Mehmet Koyutürk

This paper introduces a method to embed biological networks by considering topological similarity across layers, improving drug repositioning and target prediction accuracy.

DOI 10.1101/2021.11.05.467392

statistical modeldrug response / drug discovery

𝕏 PostBluesky

BioinformaticsbioRxivPreprintNov 14, 2020

Proximity Measures as Graph Convolution Matrices for Link Prediction in Biological Networks

Mustafa Coşkun, Mehmet Koyutürk

The paper evaluates node similarity measures as convolution matrices in GCN-based methods for link prediction in biomedical networks, showing significant improvements in performance.

3 citations

graph neural networkstatistical model

𝕏 PostBluesky