Author

K. Takacs

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

Evolutionary Biology· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:experimental assay· 2 Research Focus:host-pathogen & immune response· 2 Organism:human· 2 Research Focus:clustering· 1 Research Focus:gene regulatory network inference· 1 Organism:mouse· 1 Approach:statistical model· 1 Research Focus:synaptic & neural circuits· 1

Frequent Co-Authors

F. Samu· 2 shared S. Szamado· 2 shared A. Paccanaro· 1 shared A. Uren· 1 shared B. Iadarola· 1 shared B. J. Bolt· 1 shared G. Dharmalingam· 1 shared G. Tan· 1 shared

Activity by Year

2017-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 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

2 shared papersEvolutionary Biology

F. Samu

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Condition-dependent trade-offs maintain honest signaling: A laboratory experiment

S. Szamado, F. Samu, K. Takacs

This study conducts a human laboratory experiment to test whether condition-dependent signaling trade-offs or equilibrium signal costs maintain honest communication, finding trade-offs have a greater impact.

bioRxiv · Oct 1, 2019 · PreprintEvolutionary Biology

Scarce and directly beneficial reputations support cooperation

F. Samu, S. Szamado, K. Takacs

This study investigates how reputation systems support cooperation in social dilemmas, finding that scarcity and non-direct benefit earning enhance reputation credibility.

bioRxiv · Oct 1, 2019Evolutionary Biology

Tracking Subclonal Mutation Frequencies Throughout Lymphomagenesis Identifies Cancer Drivers in Mouse Models of Lymphoma.

P. Webster, J. C. Dawes, H. Dewchand, K. Takacs, B. Iadarola, B. J. Bolt, J. J. Caceres, J. Kaczor, L. Game, T. Adejumo, J. Elliott, K. Naresh, G. Tan, G. Dharmalingam, A. Paccanaro, A. Uren

The paper tracks subclonal mutation frequencies in mouse lymphoma models to identify cancer drivers and demonstrates negative selection of potentially deleterious mutations.

bioRxiv · Jun 29, 2017Cancer Biology