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Xiaohui Qu
Researcher at Memorial Sloan Kettering Cancer Center
Publications - 15
Citations - 861
Xiaohui Qu is an academic researcher from Memorial Sloan Kettering Cancer Center. The author has contributed to research in topics: RNA & Translation (biology). The author has an hindex of 9, co-authored 15 publications receiving 813 citations. Previous affiliations of Xiaohui Qu include University of Chicago & University of California, Berkeley.
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Nanometer-localized multiple single-molecule fluorescence microscopy.
TL;DR: This paper demonstrates nanometer-localized multiple single-molecule (NALMS) fluorescence microscopy by using both centroid localization and photobleaching of the single fluorophores to validate the NALMS microscopy approach.
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The ribosome uses two active mechanisms to unwind messenger RNA during translation
Xiaohui Qu,Jin-Der Wen,Jin-Der Wen,Laura Lancaster,Harry F. Noller,Carlos Bustamante,Ignacio Tinoco +6 more
TL;DR: It is found that the translation rate of identical codons at the decoding centre is greatly influenced by the GC content of folded structures at the mRNA entry site, and force applied to the ends of the hairpin to favour its unfolding significantly speeds translation.
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Ribosomal protein S1 unwinds double-stranded RNA in multiple steps
TL;DR: It is demonstrated that S1 promotes RNA unwinding by binding to the single-stranded RNA formed transiently during the thermal breathing of the RNA base pairs and that S2 dissociation results in RNA rezipping, and that a multistep scheme greatly expedites S1 unwinding of an RNA structure compared to a single-step mode.
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Single-molecule nonequilibrium periodic Mg2+-concentration jump experiments reveal details of the early folding pathways of a large RNA
TL;DR: The capability of interrogating nonequilibrium steady-state RNA conformations and the adjustable period of [Mg2+]-jump cycles makes it possible to probe regions of the free energy landscape that are infrequently sampled in equilibrium or single-jump measurements.
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Numerical and Theoretical Studies of Noise Effects in the Kauffman Model
TL;DR: In this paper, the authors analyzed the stochastic dynamics of the Kauffman model evolving under the influence of noise and showed that different models exhibit a similar behavior, even when the structure of their basins of attraction is quite different.