Author

Anubhav Kaphle

Commonwealth Scientific and Industrial Research OrganisationORCID 0000-0002-1972-6819Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 1 Genetic & Genomic Medicine· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:machine learning (classical)· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:drug response / drug discovery· 1 Research Focus:eQTL / molecular QTL mapping· 1 Research Focus:fine-mapping· 1

Frequent Co-Authors

Brendan HoskingiD· 2 shared Denis C. BaueriD· 2 shared Natalie A. TwineiD· 2 shared Roc ReguantiD· 2 shared Yatish JainiD· 2 shared Anne H. KleiniD· 1 shared Franco L. SimonettiiD· 1 shared Hawlader Abdullah Al-MamuniD· 1 shared

Activity by Year

2021-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersCancer Biology

Brendan HoskingORCID

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3 papers

Recent·Most cited

Machine Learning-Driven Discovery of Synergistic Protein Interactions Identifies ATL3 as a Putative Biomarker for Cancer Drug Response

Priya Ramarao-Milne, Anubhav Kaphle, Roc Reguant, Anne H. Klein, Michael J. Kuiper, Brendan Hosking, Julika Wenzel, Hawlader Abdullah Al-Mamun, Lujain Elazab, Qing Zhong, Roger R. Reddel, Laurence Wilson, Yatish Jain, Natalie A. Twine, Denis C. Bauer

The paper introduces synerOmics, a machine learning framework to identify synergistic protein interactions, finding ATL3 as a biomarker for lapatinib resistance in breast cancer.

bioRxiv · Nov 5, 2025 · PreprintCancer Biology

Optimizing UK Biobank Cloud Based Research Analysis Platform to Fine Map Coronary Artery Disease Loci in Whole Genome Sequencing Data

Letitia M.F. Sng, Anubhav Kaphle, Mitchell J. O’Brien, Brendan Hosking, Roc Reguant, Johan W. H. Verjans, Yatish Jain, Natalie A. Twine, Denis C. Bauer

The paper fine maps CAD loci in UK Biobank whole genome sequencing data using PolyFun and ML tools, showing improved sensitivity over traditional methods and demonstrating cost and speed benefits of cloud-based analysis.

Scientific Reports · Mar 25, 2025Peer-reviewedGenetic & Genomic Medicine

Reverse regression increases power for detecting trans-eQTLs

Saikat Banerjee, Franco L. Simonetti, Kira E. Detrois, Anubhav Kaphle, Raktim Mitra, Rahul Nagial, Johannes Söding

The paper introduces Tejaas, a method for detecting trans-eQTLs by reverse regression, identifying 18851 unique trans-eQTLs across 49 tissues and showing enrichment in regulatory regions.

Genome biology · May 6, 2021Peer-reviewedGenetics