Author

Malik Yousef

Zefat Academic CollegeORCID 0000-0001-8780-6303Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Burcu Bakır-GüngöriD· 2 shared Bahjat F. QaqishiD· 1 shared Cihan KuzudisliiD· 1 shared Jens AllmeriD· 1 shared Yasin İnaliD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 6 mutual co-author links

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2 shared papersBioinformatics

Burcu Bakır-GüngörORCID

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2 papers

Recent·Most cited

BioinformaticsPeerJ Computer SciencePeer-reviewedFeb 7, 2025

RCE-IFE: Recursive Cluster Elimination with Intra-cluster Feature Elimination

Cihan Kuzudisli, Burcu Bakır-Güngör, Bahjat F. Qaqish, Malik Yousef

RCE-IFE reduces feature set size and improves model performance by recursively eliminating low-scoring feature clusters and intra-cluster features in a supervised setting.

10 citations

statistical modeldimensionality reduction

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BioinformaticsbioRxivPreprintMar 30, 2024

G-S-M: A Comprehensive Framework for Integrative Feature Selection in Omics Data Analysis and Beyond

Malik Yousef, Jens Allmer, Yasin İnal, Burcu Bakır-Güngör

The paper introduces G-S-M, a framework for integrative feature selection that combines machine learning and prior knowledge to identify discriminative feature groups for medical applications.

15 citations

humanproteomics

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