Author

Q. A. E. Peter

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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Biophysics· 4

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Research Focus:protein folding & dynamics· 3 Assay:proteomics· 2 Research Focus:cell signaling & trafficking· 1 Research Focus:host-pathogen & immune response· 1 Approach:machine learning (classical)· 1 Approach:microscopy & imaging analysis· 1

Frequent Co-Authors

M. M. Schneider· 3 shared T. P. J. Knowles· 3 shared T. W. Herling· 3 shared C. M. Dobson· 2 shared F.-U. Hartl· 2 shared G. Krainer· 2 shared K. L. Saar· 2 shared A. Bracher· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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3 shared papersBiophysics

M. M. Schneider

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Author profile →

4 papers

Recent·Most cited

Thermodynamic profiles for co-translational trigger factor function

T. W. Herling, A. M. E. Cassaignau, A. S. Wentink, Q. A. E. Peter, P. C. Kumar, T. Kartanas, M. M. Schneider, L. D. Cabrita, J. Christodoulou, T. P. J. Knowles

This study identifies the thermodynamic mechanisms underlying trigger factor binding to ribosomes and nascent chains during co-translational protein synthesis.

bioRxiv · Aug 23, 2023 · PreprintBiophysics

Single-molecule digital sizing of proteins in solution

G. Krainer, R. P. B. Jacquat, M. M. Schneider, T. J. Welsh, J. Fan, Q. A. E. Peter, E. A. Andrzejewska, G. Sneideriene, M. A. Czekalska, H. Ausserwoeger, L. Chai, W. E. Arter, K. L. Saar, T. W. Herling, T. M. Franzmann, , T. P. J. Knowles

This paper introduces smMDS, a method for digital sizing of proteins in solution, enabling sensitive and accurate measurement of protein sizes and interactions.

bioRxiv · Jul 12, 2023Biophysics

Machine learning aided top-down protein identification on a microfluidic platform

Y. Zhang, M. Wright, K. L. Saar, P. Challa, A. S. Morgunov, Q. A. E. Peter, S. Devenish, C. M. Dobson, T. P. J. Knowles

This paper demonstrates a microfluidic platform that generates multidimensional protein fingerprints, enabling high-accuracy classification using machine learning, even when single-dimensional classification fails.

bioRxiv · Nov 14, 2020 · PreprintBiophysics

The Hsc70 Disaggregation Machinery RemovesMonomer Units Directly from α-Synuclein FibrilEnds

M. M. Schneider, S. Gautam, T. W. Herling, E. Andrzejwska, G. Krainer, A. M. Miller, Q. A. E. Peter, F. S. Ruggeri, M. Vendruscolo, A. Bracher, C. M. Dobson, F.-U. Hartl, T. Knowles

This study shows the Hsc70-DnaJB1-Apg2 chaperone system removes monomer units directly from α-synuclein fibril ends, reversing aggregation without intermediate fragmentation.

bioRxiv · Nov 2, 2020Biophysics