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Institution

Technische Universität Darmstadt

EducationDarmstadt, Germany
About: Technische Universität Darmstadt is a education organization based out in Darmstadt, Germany. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 17316 authors who have published 40619 publications receiving 937916 citations. The organization is also known as: Darmstadt University of Technology & University of Darmstadt.


Papers
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Journal ArticleDOI
TL;DR: It is proposed that NHEJ initially attempts to repair DSBs and, if rapid rejoining does not ensue, then resection occurs promoting repair by HR, and novel roles for ATM in regulating DSB end resection are identified.
Abstract: DNA non-homologous end joining (NHEJ) and homologous recombination (HR) function to repair DNA double-strand breaks (DSBs) in G2 phase with HR preferentially repairing heterochromatin-associated DSBs (HC-DSBs). Here, we examine the regulation of repair pathway usage at two-ended DSBs in G2. We identify the speed of DSB repair as a major component influencing repair pathway usage showing that DNA damage and chromatin complexity are factors influencing DSB repair rate and pathway choice. Loss of NHEJ proteins also slows DSB repair allowing increased resection. However, expression of an autophosphorylation-defective DNA-PKcs mutant, which binds DSBs but precludes the completion of NHEJ, dramatically reduces DSB end resection at all DSBs. In contrast, loss of HR does not impair repair by NHEJ although CtIP-dependent end resection precludes NHEJ usage. We propose that NHEJ initially attempts to repair DSBs and, if rapid rejoining does not ensue, then resection occurs promoting repair by HR. Finally, we identify novel roles for ATM in regulating DSB end resection; an indirect role in promoting KAP-1-dependent chromatin relaxation and a direct role in phosphorylating and activating CtIP.

449 citations

Journal ArticleDOI
TL;DR: Evaluating the performance of several state-of-the-art heuristics from the literature on the basis of a standard set of test instances and point out to the most promising procedures is presented.

445 citations

Journal ArticleDOI
TL;DR: In this article, a 1.97 +/- 0.04 M-circle dot neutron star was observed to have sub-and supranuclear densities, which constrain the equation of state of neutron-rich matter.
Abstract: Microscopic calculations of neutron matter based on nuclear interactions derived from chiral effective field theory, combined with the recent observation of a 1.97 +/- 0.04 M-circle dot neutron star, constrain the equation of state of neutron-rich matter at sub-and supranuclear densities. We discuss in detail the allowed equations of state and the impact of our results on the structure of neutron stars, the crust-core transition density, and the nuclear symmetry energy. In particular, we show that the predicted range for neutron star radii is robust. For use in astrophysical simulations, we provide detailed numerical tables for a representative set of equations of state consistent with these constraints.

445 citations

Journal ArticleDOI
25 May 2000-Nature
TL;DR: This work has imaged the ATP synthase from leaf chloroplasts by using atomic force microscopy and, surprisingly, finds that its turbine has 14 subunits, arranged in a cylindrical ring.
Abstract: ATP synthases are enzymes that can work in two directions to catalyse either the synthesis or breakdown of ATP, and they constitute the smallest rotary motors in biology The flow of protons propels the rotation1 of a membrane-spanning complex of identical protein subunits, the number of which determines the efficiency of energy conversion This proton-powered turbine is predicted to consist of 12 subunits2,3,4, based on data for Escherichia coli5 The yeast mitochondrial enzyme, however, has only 10 subunits6 We have imaged the ATP synthase from leaf chloroplasts by using atomic force microscopy and, surprisingly, find that its turbine has 14 subunits, arranged in a cylindrical ring

443 citations

Proceedings Article
03 Dec 2007
TL;DR: A method which uses Maximum Margin Matrix Factorization and optimizes ranking instead of rating is presented and gives very good ranking scores and scales well on collaborative filtering tasks.
Abstract: In this paper, we consider collaborative filtering as a ranking problem. We present a method which uses Maximum Margin Matrix Factorization and optimizes ranking instead of rating. We employ structured output prediction to optimize directly for ranking scores. Experimental results show that our method gives very good ranking scores and scales well on collaborative filtering tasks.

442 citations


Authors

Showing all 17627 results

NameH-indexPapersCitations
Yang Gao1682047146301
Herbert A. Simon157745194597
Stephen Boyd138822151205
Jun Chen136185677368
Harold A. Mooney135450100404
Bernt Schiele13056870032
Sascha Mehlhase12685870601
Yuri S. Kivshar126184579415
Michael Wagner12435154251
Wolf Singer12458072591
Tasawar Hayat116236484041
Edouard Boos11675764488
Martin Knapp106106748518
T. Kuhl10176140812
Peter Braun-Munzinger10052734108
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023135
2022624
20212,462
20202,585
20192,609
20182,493