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- Aad, G, et al.
(author)
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Search for Higgs Boson Pair Production in the γγbb[over ¯] Final State Using pp Collision Data at sqrt[s]=8 TeV from the ATLAS Detector.
- 2015
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In: Physical Review Letters. - 1079-7114. ; 114:8
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Journal article (peer-reviewed)abstract
- Searches are performed for resonant and nonresonant Higgs boson pair production in the γγbb[over ¯] final state using 20 fb^{-1} of proton-proton collisions at a center-of-mass energy of 8 TeV recorded with the ATLAS detector at the CERN Large Hadron Collider. A 95% confidence level upper limit on the cross section times branching ratio of nonresonant production is set at 2.2 pb, while the expected limit is 1.0 pb. The difference derives from a modest excess of events, corresponding to 2.4 standard deviations from the background-only hypothesis. The limit observed in the search for a narrow X→hh resonance ranges between 0.7 and 3.5 pb as a function of the resonance mass.
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- Aad, G, et al.
(author)
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Searches for scalar leptoquarks in pp collisions at [Formula: see text] = 8 TeV with the ATLAS detector.
- 2016
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044. ; 76
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Journal article (peer-reviewed)abstract
- Searches for pair-produced scalar leptoquarks are performed using 20 fb[Formula: see text] of proton-proton collision data provided by the LHC and recorded by the ATLAS detector at [Formula: see text] TeV. Events with two electrons (muons) and two or more jets in the final state are used to search for first (second)-generation leptoquarks. The results from two previously published ATLAS analyses are interpreted in terms of third-generation leptoquarks decaying to [Formula: see text] and [Formula: see text] final states. No statistically significant excess above the Standard Model expectation is observed in any channel and scalar leptoquarks are excluded at 95 % CL with masses up to [Formula: see text] 1050 GeV for first-generation leptoquarks, [Formula: see text] 1000 GeV for second-generation leptoquarks, [Formula: see text] 625 GeV for third-generation leptoquarks in the [Formula: see text] channel, and 200 [Formula: see text] 640 GeV in the [Formula: see text] channel.
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- Campbell, PJ, et al.
(author)
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Pan-cancer analysis of whole genomes
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Journal article (peer-reviewed)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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