Author

Ketevan Chkhaidze

Institute of Cancer Research

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Andrea SottorivaiD· 2 shared Benjamin WerneriD· 2 shared Giulio CaravagnaiD· 2 shared Marc J. WilliamsiD· 2 shared Timon HeideiD· 2 shared Trevor A. GrahamiD· 2 shared Ahmet AcariD· 1 shared Chris P. BarnesiD· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Andrea SottorivaORCID

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2 papers

Recent·Most cited

Model-based tumor subclonal reconstruction

Giulio Caravagna, Timon Heide, Marc J. Williams, Luis Zapata, Daniel Nichol, Ketevan Chkhaidze, William C. H. Cross, George D. Cresswell, Benjamin Werner, Ahmet Acar, Louis Chesler, Chris P. Barnes, Guido Sanguinetti, Trevor A. Graham, Andrea Sottoriva

This paper introduces a model-based subclonal reconstruction method that integrates evolutionary theory with machine learning to improve accuracy in tumor subclonal analysis.

Nature Genetics · Sep 1, 2020Peer-reviewedBioinformatics

Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data

Ketevan Chkhaidze, Timon Heide, Benjamin Werner, Marc J. Williams, Weini Huang, Giulio Caravagna, Trevor A. Graham, Andrea Sottoriva

This paper shows that spatial tumour structure affects mutation patterns in sequencing data and introduces a framework to account for these effects in cancer genomic analysis.

PLoS Computational Biology · Jul 29, 2019Peer-reviewedBioinformatics