Author

Heiko Enderling

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

Biology Disciplines

Click to filter author papers

Cancer Biology· 4 Systems Biology· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 4 Approach:experimental assay· 3 Research Focus:cancer & tumor microenvironment· 2 Research Focus:cell signaling & trafficking· 2 Research Focus:drug response / drug discovery· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:deep learning· 1

Frequent Co-Authors

Jan Poleszczuk· 3 shared Rachel Walker· 2 shared Aleksandra Karolak· 1 shared Amir Shahmoradi· 1 shared Daniel Abate-Daga· 1 shared Fiona Macfarlane· 1 shared Frederik Ziebell· 1 shared Jan T Poleszczuk· 1 shared

Activity by Year

2015-2016 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersCancer Biology

Jan Poleszczuk

Mutual co-authors in cluster

Author profile →

6 papers

Recent·Most cited

Enhancing synergy of CAR T cell therapy and oncolytic virus therapy for pancreatic cancer.

Rachel Walker, Pedro E. Navas, Samuel H. Friedman, Simona Galliani, Aleksandra Karolak, Fiona Macfarlane, Robert Noble, Jan Poleszczuk, Shonagh Russell, Katarzyna A. Rejniak, Amir Shahmoradi, Frederik Ziebell, Jason Brayer, Daniel Abate-Daga, Heiko Enderling

This study evaluates how combining oncolytic virus therapy with CAR T cell therapy can improve pancreatic cancer treatment using mathematical models.

bioRxiv · May 30, 2016 · PreprintCancer Biology

Agent-based modeling of cancer stem cell driven solid tumor growth

Jan T Poleszczuk, Paul Macklin, Heiko Enderling

The paper describes a lattice-based agent-based model of cancer stem cell driven tumor growth using computational modeling.

Methods in Molecular Biology · Apr 5, 2016Peer-reviewedSystems Biology

From concept to clinic: mathematically informed immunotherapy

Rachel Walker, Heiko Enderling

This paper reviews the application of mathematical modeling in immunotherapy to understand and predict cancer treatment outcomes.

Current Problems in Cancer · Jan 1, 2016Peer-reviewedCancer Biology

Cancer stem cell plasticity as tumor growth promoter and catalyst of population collapse

Jan Poleszczuk, Heiko Enderling

This study investigates how varying rates of cancer stem cell plasticity affect tumor growth and treatment response using an agent-based model and in silico trials.

Stem Cells International · Jan 1, 2016Peer-reviewedCancer Biology

Integrating experimental data to calibrate quantitative cancer models

Heiko Enderling

The paper demonstrates how to integrate experimental data to calibrate quantitative cancer models, focusing on cell cycle distributions and proliferation rates in tumor hierarchies.

bioRxiv · Nov 17, 2015 · PreprintCancer Biology

Vectorization techniques for efficient agent-based model simulations of tumor growth

Jan Poleszczuk, Heiko Enderling

This paper demonstrates how vectorization techniques can significantly improve the computational efficiency of agent-based models simulating tumor growth.

bioRxiv · Nov 17, 2015 · PreprintSystems Biology