Author

I. G. Walker

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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Cancer Biology· 2 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Research Focus:drug response / drug discovery· 2 Organism:human· 2 Assay:proteomics· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

M. A. Chapman· 3 shared G. S. Anderson· 2 shared J. P. Roy· 2 shared A. Aubareda· 1 shared G. L. Smith· 1 shared J. A. Guerrero· 1 shared

Activity by Year

2023-2023 · peak 3/yr

Co-Author Collaboration Network

6 top collaborators · 9 mutual co-author links

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3 shared papersCancer Biology

M. A. Chapman

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Cell surface proteomics reveal a strategy for targeting myeloma through combinatorial targeting of TNFRSF8 and TMPRSS11E

G. S. Anderson, I. G. Walker, J. P. Roy, M. A. Chapman

The paper identifies AND-gate antigen combinations for myeloma targeting using proteomics and evaluates a dual-target CAR T-cell strategy.

bioRxiv · Apr 4, 2023 · PreprintCancer Biology

Targeting Myeloma Essential Genes using NOT Gated CAR- T Cells, a computational approach.

I. G. Walker, J. P. Roy, G. S. Anderson, J. A. Guerrero, M. A. Chapman

The paper explores using NOT-gated CAR-T cells to target essential but non-specific proteins in myeloma, showing that the transferrin receptor can be safely targeted with this approach.

bioRxiv · Apr 4, 2023Cancer Biology

A machine learning approach to predict drug-induced autoimmunity using transcriptional data.

G. L. Smith, I. G. Walker, A. Aubareda, M. A. Chapman

This paper uses an ensemble machine learning approach to predict drug-induced autoimmunity from transcriptional data, identifying dysregulated cell cycling as a potential mechanism.

bioRxiv · Apr 4, 2023 · PreprintPharmacology & Toxicology