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Jennifer A. Smith

Researcher at University of Michigan

Publications -  977
Citations -  94283

Jennifer A. Smith is an academic researcher from University of Michigan. The author has contributed to research in topics: Large Hadron Collider & Standard Model. The author has an hindex of 131, co-authored 862 publications receiving 83025 citations. Previous affiliations of Jennifer A. Smith include National Institutes of Health & Imperial College London.

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Search for high-mass diphoton resonances in proton-proton collisions at 13 TeV and combination with 8 TeV search

Vardan Khachatryan, +2297 more
- 10 Apr 2017 - 
TL;DR: In this article, the authors acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MOST, and NSFC (China); COLCIEN-CIAS (Colombia); DAE and DST (India); IPM (Iran); S
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Searches for electroweak neutralino and chargino production in channels with Higgs, Z, and W bosons in pp collisions at 8 TeV

Vardan Khachatryan, +2135 more
- 21 Nov 2014 - 
TL;DR: In this article, the electroweak pair production of neutralinos and charginos, leading to decay channels with Higgs, Z, and W bosons and undetected lightest SUSY particles (LSPs) is presented.
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Searches for new physics using the tt̄ invariant mass distribution in pp collisions at √s=8 TeV

S. Chatrchyan, +2207 more
TL;DR: In this paper, anomalous top quark-antiquark production is studied based on pp collisions at 8 TeV. The observed ttbar invariant mass spectrum is found to be compatible with the standard model prediction.
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Pleiotropic genes for metabolic syndrome and inflammation.

Aldi T. Kraja, +72 more
TL;DR: Investigation of large data evidence concludes that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part ofmetabolic syndrome correlated genetic architecture.
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Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

Xihao Li, +77 more
- 24 Aug 2020 - 
TL;DR: STAAR is a powerful rare variant association test that incorporates variant functional categories and complementary functional annotations using a dynamic weighting scheme based on annotation principal components and is scalable for analyzing large whole-genome sequencing studies.