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Chris Sander

Researcher at Harvard University

Publications -  730
Citations -  273726

Chris Sander is an academic researcher from Harvard University. The author has contributed to research in topics: Large Hadron Collider & Protein structure. The author has an hindex of 178, co-authored 713 publications receiving 233287 citations. Previous affiliations of Chris Sander include Purdue University & University of Leeds.

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BioPAX - Biological Pathways Exchange Language Level 2, Version 1.0 Documentation

TL;DR: The scope of BioPAX is expanded to include representation of molecular binding interactions, protein post-translational modifications, basic experimental descriptions, and hierarchical pathways, which will increase access to and uniformity of pathway data from varied sources, thus increasing the efficiency of computational pathway research.
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A comparison of structural and dynamic properties of different simulation methods applied to SH3

TL;DR: The "essential dynamics" method proved to be a powerful tool for the comparison of large concerted atomic motions in SH3 and identified methods of simulation that yielded significantly different dynamic properties compared to the full solvent simulation.
Journal ArticleDOI

Measurement of the W-boson mass in pp collisions at root s = 7 TeV with the ATLAS detector (vol 78, 110, 2018)

Morad Aaboud, +2832 more
TL;DR: In this paper, it has been shown that Figure 30 shows the 68% and 99% confidence-level contours for the W boson and top quark mass measurements, instead of the 66% and 95% confidence level contours, as stated in the legend.
Journal ArticleDOI

Measurement of light-by-light scattering and search for axion-like particles with 2.2 nb$^{-1}$ of Pb+Pb data with the ATLAS detector

Georges Aad, +2996 more
TL;DR: In this article, a measurement of light-by-light scattering based on Pb+Pb collision data recorded by the ATLAS experiment during Run 2 of the LHC is described.
Proceedings Article

Decision Support System for the Evolutionary Classification of Protein Structures

TL;DR: The semiautomatic prototype system significantly enhances the efficiency of unifying families of functionally related proteins in spite of long evolutionary distances.