Author

T. Pfeiffer

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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Biochemistry· 1 Ecology· 1 Physiology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Approach:statistical model· 2 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell signaling & trafficking· 1 Assay:cryo-EM· 1 Assay:electrophysiology· 1 Research Focus:host-pathogen & immune response· 1 Organism:human· 1

Frequent Co-Authors

A. K. Scharf· 1 shared A. Rainish· 1 shared A. Roulin· 1 shared A.-L. Harrison· 1 shared B. Koeck· 1 shared B.-U. Meyburg· 1 shared C. H. Fleming· 1 shared C. M. Tonra· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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Curved chords = mutual co-authorship

1 shared paperEcology

A. K. Scharf

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Intracellular binding pocket revealed in the human bitter taste receptor TAS2R14

L. Peri, D. Matzov, D. R. Huxley, A. Rainish, F. Fierro, L. Sapir, T. Pfeiffer, L. Waterloo, H. Huebner, D. Weikert, Y. Peleg, P. Gmeiner, P. Mccormick, M. Y. Niv, M. Shalev-Benami

The paper reveals the cryo-EM structure of hTAS2R14 bound to FFA and gustducin, showing dual binding pockets and supporting a dual binding mode for FFA.

bioRxiv · Apr 10, 2024Biochemistry

The Ca2+-gated Cl- channel TMEM16A amplifies capillary pericyte contraction reducing cerebral blood flow after ischemia

N. Korte, Z. Ilkan, C. Pearson, T. Pfeiffer, P. Singhal, J. Rock, H. Sethi, D. Gill, D. Attwell, P. Tammaro

This study shows that TMEM16A in pericytes amplifies capillary constriction and reduces cerebral blood flow after ischemia, suggesting it as a therapeutic target for stroke and related disorders.

bioRxiv · Feb 3, 2022 · PreprintPhysiology

A comprehensive framework for handling location error in animal tracking data

C. H. Fleming, J. Drescher-Lehman, M. J. Noonan, T. S. B. Akre, D. J. Brown, M. M. Cochrane, N. Dejid, V. DeNicola, C. S. DePerno, J. N. Dunlop, N. P. Gould, A.-L. Harrison, J. Hollins, H. Ishii, Y. Kaneko, , J. M. Calabrese

This paper introduces a framework for handling location error in animal tracking data, showing that error-model selection improves analysis accuracy across various tracking devices and species.

bioRxiv · Jun 12, 2020 · PreprintEcology