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Daniel Z Wu
Researcher at University of Pennsylvania
Publications - 5
Citations - 54
Daniel Z Wu is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Aurora B kinase & Kinetochore microtubule. The author has an hindex of 2, co-authored 5 publications receiving 31 citations.
Papers
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Journal ArticleDOI
Reversible Control of Protein Localization in Living Cells Using a Photocaged-Photocleavable Chemical Dimerizer
TL;DR: This work presents a novel chemical inducer of protein dimerization that can be rapidly turned on and off using single pulses of light at two orthogonal wavelengths and demonstrates the utility of this molecule by controlling peroxisome transport and mitotic checkpoint signaling in living cells.
Journal ArticleDOI
Tension promotes kinetochore-microtubule release by Aurora B kinase.
Geng-Yuan Chen,Fioranna Renda,Huaiying Zhang,Alper Gokden,Daniel Z Wu,David M. Chenoweth,Alexey Khodjakov,Michael A. Lampson +7 more
TL;DR: In this article, the authors show that tension is a signal inducing distinct error-correction pathways, with release or depolymerization being advantageous for typical errors characterized by high or low tension, respectively.
Book ChapterDOI
Photoactivatable trimethoprim-based probes for spatiotemporal control of biological processes.
TL;DR: This chapter describes the synthesis and application of chemi-optogenetic probes for spatiotemporal control of protein proximity, a technique in which two proteins of interest are brought together by the presence of a small molecule to induce a biological effect.
Book ChapterDOI
Reversible optogenetic control of protein function and localization.
TL;DR: An optogenetic platform that provides reversible control over dimerization of genetically tagged proteins using orthogonal wavelengths of light is described and photoactivation and photo-reversal of protein localization and transport are demonstrated.
Posted ContentDOI
Tension promotes kinetochore-microtubule release in response to Aurora B activity
Geng-Yuan Chen,Fioranna Renda,Huaiying Zhang,Alper Gokden,Daniel Z Wu,David M. Chenoweth,Alexey Khodjakov,Michael A. Lampson +7 more
TL;DR: It is proposed that tension is a signal inducing distinct error-correction mechanisms, with release or depolymerization advantageous for typical errors characterized by high or low tension, respectively.