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Alexander Sherstnev

Researcher at University of Dundee

Publications -  67
Citations -  15343

Alexander Sherstnev is an academic researcher from University of Dundee. The author has contributed to research in topics: Large Hadron Collider & Quantum chromodynamics. The author has an hindex of 33, co-authored 63 publications receiving 14205 citations. Previous affiliations of Alexander Sherstnev include University of Cambridge & GlaxoSmithKline.

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The CMS experiment at the CERN LHC

S. Chatrchyan, +3175 more
TL;DR: The Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) at CERN as mentioned in this paper was designed to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1)
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Herwig++ Physics and Manual

TL;DR: Herwig++ as mentioned in this paper is a general-purpose Monte Carlo event generator for the simulation of hard lepton-lepton, leptonhadron and hadron-hadron collisions, with special emphasis on the correct description of radiation from heavy particles.
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Herwig++ Physics and Manual

TL;DR: Herwig++ as mentioned in this paper is a general-purpose Monte Carlo event generator for the simulation of hard lepton-lepton, leptonhadron and hadron-hadron collisions, together with a number of important hard scattering processes.
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CMS physics technical design report, volume II: Physics performance

G. L. Bayatian, +2063 more
- 01 Jun 2007 - 
TL;DR: In this article, the authors present a detailed analysis of the performance of the Large Hadron Collider (CMS) at 14 TeV and compare it with the state-of-the-art analytical tools.
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How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use?

TL;DR: For future RNA-seq experiments, results suggest that at least six biological replicates should be used, rising to at least 12 when it is important to identify SDE genes for all fold changes, and if fewer than 12 replicates are used, a superior combination of true positive and false positive performances makes edgeR and DESeq2 the leading tools.