Author

Zohaib Atif

Gwangju Institute of Science and TechnologyORCID 0000-0002-0299-3857Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:bulk RNA-seq· 2 Approach:deep learning· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Brhanu F. ZnabuiD· 3 shared Jackfin K C· 1 shared Pradeep Devkota· 1 shared Rediet Habtamu Alemu· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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3 shared papersBioinformatics

Brhanu F. ZnabuORCID

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3 papers

Recent·Most cited

A Reproducible MFASS Benchmark of Splice-Disruption Predictors Reveals a Shared Exon-Interior Blind Spot

Brhanu F. Znabu, Zohaib Atif, Pradeep Devkota, Rediet Habtamu Alemu, Jackfin K C

The paper benchmarks four splice-disruption predictors using experimental data, finding Pangolin performs best and identifying a shared blind spot in exon interiors.

bioRxiv · Jul 26, 2026 · PreprintBioinformatics

NativeReady: an open benchmark and sequence-based triage model for native mass spectrometry suitability

Brhanu F. Znabu, Zohaib Atif

NativeReady provides a benchmark and sequence-based model to predict native mass spectrometry suitability, achieving an AUC of 0.869 with cluster-aware cross-validation.

bioRxiv · May 6, 2026 · PreprintBioinformatics

Interpretable Deep Learning-Based Multi-Omics Integrationfor Prognosis in Hepatocellular Carcinoma

Brhanu F. Znabu, Zohaib Atif

The paper develops an interpretable deep learning framework for multi-omics survival prediction in HCC, achieving better performance than existing models and identifying biologically relevant features.

bioRxiv · Apr 5, 2026 · PreprintBioinformatics