scispace - formally typeset
Search or ask a question
Institution

University of Trento

EducationTrento, Italy
About: University of Trento is a education organization based out in Trento, Italy. It is known for research contribution in the topics: Population & Context (language use). The organization has 10527 authors who have published 30978 publications receiving 896614 citations. The organization is also known as: Universitá degli Studi di Trento & Universita degli Studi di Trento.


Papers
More filters
Journal ArticleDOI
Damian Smedley1, Syed Haider2, Steffen Durinck3, Luca Pandini4, Paolo Provero5, Paolo Provero4, James E. Allen6, Olivier Arnaiz7, Mohammad Awedh8, Richard Baldock9, Giulia Barbiera4, Philippe Bardou10, Tim Beck11, Andrew Blake, Merideth Bonierbale12, Anthony J. Brookes11, Gabriele Bucci4, Iwan Buetti4, Sarah W. Burge6, Cédric Cabau10, Joseph W. Carlson13, Claude Chelala14, Charalambos Chrysostomou11, Davide Cittaro4, Olivier Collin15, Raul Cordova12, Rosalind J. Cutts14, Erik Dassi16, Alex Di Genova17, Anis Djari10, Anthony Esposito18, Heather Estrella18, Eduardo Eyras19, Eduardo Eyras20, Julio Fernandez-Banet18, Simon A. Forbes1, Robert C. Free11, Takatomo Fujisawa, Emanuela Gadaleta14, Jose Manuel Garcia-Manteiga4, David Goodstein13, Kristian Gray6, José Afonso Guerra-Assunção14, Bernard Haggarty9, Dong Jin Han21, Byung Woo Han21, Todd W. Harris22, Jayson Harshbarger, Robert K. Hastings11, Richard D. Hayes13, Claire Hoede10, Shen Hu23, Zhi-Liang Hu24, Lucie N. Hutchins, Zhengyan Kan18, Hideya Kawaji, Aminah Keliet10, Arnaud Kerhornou6, Sunghoon Kim21, Rhoda Kinsella6, Christophe Klopp10, Lei Kong25, Daniel Lawson6, Dejan Lazarevic4, Ji Hyun Lee21, Thomas Letellier10, Chuan-Yun Li25, Pietro Liò26, Chu Jun Liu25, Jie Luo6, Alejandro Maass17, Jérôme Mariette10, Thomas Maurel6, Stefania Merella4, Azza M. Mohamed8, François Moreews10, Ibounyamine Nabihoudine10, Nelson Ndegwa27, Céline Noirot10, Cristian Perez-Llamas19, Michael Primig28, Alessandro Quattrone16, Hadi Quesneville10, Davide Rambaldi4, James M. Reecy24, Michela Riba4, Steven Rosanoff6, Amna A. Saddiq8, Elisa Salas12, Olivier Sallou15, Rebecca Shepherd1, Reinhard Simon12, Linda Sperling7, William Spooner29, Daniel M. Staines6, Delphine Steinbach10, Kevin R. Stone, Elia Stupka4, Jon W. Teague1, Abu Z. Dayem Ullah14, Jun Wang25, Doreen Ware29, Marie Wong-Erasmus, Ken Youens-Clark29, Amonida Zadissa6, Shi Jian Zhang25, Arek Kasprzyk4, Arek Kasprzyk8 
TL;DR: The latest version of the BioMart Community Portal comes with many new databases that have been created by the ever-growing community and comes with better support and extensibility for data analysis and visualization tools.
Abstract: The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

664 citations

Journal ArticleDOI
TL;DR: A robust precision cancer care platform that integrates whole-exome sequencing with a living biobank that enables high-throughput drug screens on patient-derived tumor organoids is described, which promotes the discovery of novel therapeutic approaches that can be assessed in clinical trials and provides personalized therapeutic options where standard clinical options have been exhausted.
Abstract: Precision medicine is an approach that takes into account the influence of individuals' genes, environment, and lifestyle exposures to tailor interventions. Here, we describe the development of a robust precision cancer care platform that integrates whole-exome sequencing with a living biobank that enables high-throughput drug screens on patient-derived tumor organoids. To date, 56 tumor-derived organoid cultures and 19 patient-derived xenograft (PDX) models have been established from the 769 patients enrolled in an Institutional Review Board-approved clinical trial. Because genomics alone was insufficient to identify therapeutic options for the majority of patients with advanced disease, we used high-throughput drug screening to discover effective treatment strategies. Analysis of tumor-derived cells from four cases, two uterine malignancies and two colon cancers, identified effective drugs and drug combinations that were subsequently validated using 3-D cultures and PDX models. This platform thereby promotes the discovery of novel therapeutic approaches that can be assessed in clinical trials and provides personalized therapeutic options for individual patients where standard clinical options have been exhausted.Significance: Integration of genomic data with drug screening from personalized in vitro and in vivo cancer models guides precision cancer care and fuels next-generation research. Cancer Discov; 7(5); 462-77. ©2017 AACR.See related commentary by Picco and Garnett, p. 456This article is highlighted in the In This Issue feature, p. 443.

653 citations

Journal ArticleDOI
TL;DR: In this article, a detailed description of the analysis used by the CMS Collaboration in the search for the standard model Higgs boson in pp collisions at the LHC, which led to the observation of a new boson.
Abstract: A detailed description is reported of the analysis used by the CMS Collaboration in the search for the standard model Higgs boson in pp collisions at the LHC, which led to the observation of a new boson. The data sample corresponds to integrated luminosities up to 5.1 inverse femtobarns at sqrt(s) = 7 TeV, and up to 5.3 inverse femtobarns at sqrt(s) = 8 TeV. The results for five Higgs boson decay modes gamma gamma, ZZ, WW, tau tau, and bb, which show a combined local significance of 5 standard deviations near 125 GeV, are reviewed. A fit to the invariant mass of the two high resolution channels, gamma gamma and ZZ to 4 ell, gives a mass estimate of 125.3 +/- 0.4 (stat) +/- 0.5 (syst) GeV. The measurements are interpreted in the context of the standard model Lagrangian for the scalar Higgs field interacting with fermions and vector bosons. The measured values of the corresponding couplings are compared to the standard model predictions. The hypothesis of custodial symmetry is tested through the measurement of the ratio of the couplings to the W and Z bosons. All the results are consistent, within their uncertainties, with the expectations for a standard model Higgs boson.

643 citations

01 Jan 2013
TL;DR: In this paper, the authors proposed a method to improve the performance of the beamforming process in the Materials Research Science and Engineering Centers (Program) (DMR-1121107)
Abstract: National Science Foundation (U.S.). Materials Research Science and Engineering Centers (Program) (DMR-1121107)

642 citations

Journal ArticleDOI
TL;DR: This work investigates the low energy excitations of a dilute atomic Bose gas confined in a harmonic trap of frequency and interacting with repulsive forces and predicts the dispersion law of the noninteracting harmonic oscillator model.
Abstract: We investigate the low energy excitations of a dilute atomic Bose gas confined in a harmonic trap of frequency ${\ensuremath{\omega}}_{0}$ and interacting with repulsive forces. The dispersion law $\ensuremath{\omega}\phantom{\rule{0ex}{0ex}}=\phantom{\rule{0ex}{0ex}}{\ensuremath{\omega}}_{0}({2n}^{2}+2n\ensuremath{\ell}+3n+\ensuremath{\ell}{)}^{1/2}$ for the elementary excitations is obtained for large numbers of atoms in the trap, to be compared with the prediction $\ensuremath{\omega}\phantom{\rule{0ex}{0ex}}=\phantom{\rule{0ex}{0ex}}{\ensuremath{\omega}}_{0}(2n+\ensuremath{\ell})$ of the noninteracting harmonic oscillator model. Here $n$ is the number of radial nodes and $\ensuremath{\ell}$ is the orbital angular momentum. The effects of the kinetic energy pressure are estimated using a sum rule approach. Results are also presented for deformed traps and attractive forces.

630 citations


Authors

Showing all 10758 results

NameH-indexPapersCitations
Yi Chen2174342293080
Jie Zhang1784857221720
Richard B. Lipton1762110140776
Jasvinder A. Singh1762382223370
J. N. Butler1722525175561
Andrea Bocci1722402176461
P. Chang1702154151783
Bradley Cox1692150156200
Marc Weber1672716153502
Guenakh Mitselmakher1651951164435
Brian L Winer1621832128850
J. S. Lange1602083145919
Ralph A. DeFronzo160759132993
Darien Wood1602174136596
Robert Stone1601756167901
Network Information
Related Institutions (5)
ETH Zurich
122.4K papers, 5.1M citations

94% related

University of Maryland, College Park
155.9K papers, 7.2M citations

93% related

University of California, Santa Barbara
80.8K papers, 4.6M citations

93% related

Sapienza University of Rome
155.4K papers, 4.3M citations

92% related

Centre national de la recherche scientifique
382.4K papers, 13.6M citations

92% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023158
2022340
20212,402
20202,286
20192,130
20181,943