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Institution

University of Milano-Bicocca

EducationMilan, Italy
About: University of Milano-Bicocca is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Population & Blood pressure. The organization has 8972 authors who have published 22322 publications receiving 620484 citations. The organization is also known as: Università degli Studi di Milano-Bicocca & Universita degli Studi di Milano-Bicocca.


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Journal ArticleDOI
12 Dec 2013-Nature
TL;DR: This study explores the transcriptional interactomes of three mouse cells of progressive lineage commitment and sets the stage for the full-scale dissection of spatial and temporal genome structures and their roles in orchestrating development.
Abstract: A chromatin interaction analysis with paired-end tagging (ChIA-PET) approach is used to delineate chromatin interactions mediated by RNA polymerase II in several different stem-cell populations; putative long-range promoter–enhancer interactions are inferred, indicating that linear juxtaposition does not necessarily guide enhancer target selection and prevalent cell-specific enhancer usage. Gene transcription requires dynamic chromatin connectivity between promoters bound by RNA polymerase II and their corresponding distal-acting enhancers. In this paper the authors use the ChIA-PET (chromatin interaction analysis with paired-end tagging) approach to delineate chromatin interactions mediated by RNA polymerase II in embryonic stem cells, neural stem cells and neurosphere progenitor cells. Putative enhancer–promoter interactions can be inferred, and many enhancers associate with promoters located beyond their nearest active genes, indicating that linear juxtaposition does not necessarily guide enhancer target selection. This work illustrates the possible importance of underlying chromatin structures in nuclear function. In multicellular organisms, transcription regulation is one of the central mechanisms modelling lineage differentiation and cell-fate determination1. Transcription requires dynamic chromatin configurations between promoters and their corresponding distal regulatory elements2. It is believed that their communication occurs within large discrete foci of aggregated RNA polymerases termed transcription factories in three-dimensional nuclear space3. However, the dynamic nature of chromatin connectivity has not been characterized at the genome-wide level. Here, through a chromatin interaction analysis with paired-end tagging approach3,4,5 using an antibody that primarily recognizes the pre-initiation complexes of RNA polymerase II6, we explore the transcriptional interactomes of three mouse cells of progressive lineage commitment, including pluripotent embryonic stem cells7, neural stem cells8 and neurosphere stem/progenitor cells9. Our global chromatin connectivity maps reveal approximately 40,000 long-range interactions, suggest precise enhancer–promoter associations and delineate cell-type-specific chromatin structures. Analysis of the complex regulatory repertoire shows that there are extensive colocalizations among promoters and distal-acting enhancers. Most of the enhancers associate with promoters located beyond their nearest active genes, indicating that the linear juxtaposition is not the only guiding principle driving enhancer target selection. Although promoter–enhancer interactions exhibit high cell-type specificity, promoters involved in interactions are found to be generally common and mostly active among different cells. Chromatin connectivity networks reveal that the pivotal genes of reprogramming functions are transcribed within physical proximity to each other in embryonic stem cells, linking chromatin architecture to coordinated gene expression. Our study sets the stage for the full-scale dissection of spatial and temporal genome structures and their roles in orchestrating development.

446 citations

Journal ArticleDOI
M. Bicer1, H. Duran Yildiz1, I. Yildiz2, G. Coignet3, Marco Delmastro3, Theodoros Alexopoulos4, Christophe Grojean, Stefan Antusch5, Tanaji Sen6, Hong-Jian He7, K. Potamianos8, Sigve Haug9, Asunción Moreno, Arno Heister10, Veronica Sanz11, Guillelmo Gomez-Ceballos12, Markus Klute12, Marco Zanetti12, Lian-Tao Wang13, Mogens Dam14, Celine Boehm15, Nigel Glover15, Frank Krauss15, Alexander Lenz15, Michael Syphers16, Christos Leonidopoulos17, Vitaliano Ciulli, P. Lenzi, Giacomo Sguazzoni, Massimo Antonelli, Manuela Boscolo, Umberto Dosselli, O. Frasciello, C. Milardi, G. Venanzoni, Mikhail Zobov, J.J. van der Bij18, M. De Gruttola19, D. W. Kim20, Michail Bachtis21, A. Butterworth21, C. Bernet21, Cristina Botta21, Federico Carminati21, A. David21, L. Deniau21, David D'Enterria21, Gerardo Ganis21, Brennan Goddard21, Gian F. Giudice21, Patrick Janot21, John Jowett21, Carlos Lourenco21, L. Malgeri21, Emilio Meschi21, Filip Moortgat21, Pasquale Musella21, J. A. Osborne21, Luca Perrozzi21, Maurizio Pierini21, Louis Rinolfi21, A. De Roeck21, Juan Rojo21, G. Roy21, Andrea Sciabà21, A. Valassi21, C. S. Waaijer21, Jorg Wenninger21, H. K. Woehri21, Frank Zimmermann21, A. Blondel22, Michael Koratzinos22, Philippe Mermod22, Yasar Onel23, R. Talman24, E. Castaneda Miranda25, Eugene Bulyak, D. Porsuk, Dmytro Kovalskyi26, Sanjay Padhi26, Pietro Faccioli, John Ellis27, Mario Campanelli28, Yang Bai29, M. Chamizo, Robert Appleby30, Hywel Owen30, H. Maury Cuna31, C. Gracios32, German Ardul Munoz-Hernandez32, Luca Trentadue33, E. Torrente-Lujan34, S. Wang35, David Bertsche36, A. V. Gramolin37, Valery I. Telnov37, Marumi Kado38, P. Petroff38, Patrizia Azzi, Oreste Nicrosini, Fulvio Piccinini, Guido Montagna39, F. Kapusta38, S. Laplace38, W. Da Silva38, Nectaria A. B. Gizani40, Nathaniel Craig41, Tao Han42, Claudio Luci43, Barbara Mele43, Luca Silvestrini43, Marco Ciuchini, R. Cakir44, R. Aleksan, Fabrice Couderc, Serguei Ganjour, Eric Lancon, Elizabeth Locci, P. Schwemling, M. Spiro, C. Tanguy, Jean Zinn-Justin, Stefano Moretti45, M. Kikuchi46, Haruyo Koiso46, Kazuhito Ohmi46, Katsunobu Oide46, G. Pauletta47, Roberto Ruiz de Austri48, Maxime Gouzevitch38, Subhasis Chattopadhyay49 
TL;DR: In this article, the authors present a first appraisal of the salient features of the TLEP physics potential, to serve as a baseline for a more extensive design study, and present a combination of TLEp and the VHE-LHC offers, for a great cost effectiveness, the best precision and the best search reach of all options presently on the market.
Abstract: The discovery by the ATLAS and CMS experiments of a new boson with mass around 125 GeV and with measured properties compatible with those of a Standard-Model Higgs boson, coupled with the absence of discoveries of phenomena beyond the Standard Model at the TeV scale, has triggered interest in ideas for future Higgs factories. A new circular e+e- collider hosted in a 80 to 100 km tunnel, TLEP, is among the most attractive solutions proposed so far. It has a clean experimental environment, produces high luminosity for top-quark, Higgs boson, W and Z studies, accommodates multiple detectors, and can reach energies up to the t-tbar threshold and beyond. It will enable measurements of the Higgs boson properties and of Electroweak Symmetry-Breaking (EWSB) parameters with unequalled precision, offering exploration of physics beyond the Standard Model in the multi-TeV range. Moreover, being the natural precursor of the VHE-LHC, a 100 TeV hadron machine in the same tunnel, it builds up a long-term vision for particle physics. Altogether, the combination of TLEP and the VHE-LHC offers, for a great cost effectiveness, the best precision and the best search reach of all options presently on the market. This paper presents a first appraisal of the salient features of the TLEP physics potential, to serve as a baseline for a more extensive design study.

445 citations

Journal ArticleDOI
TL;DR: The median concentration of dioxin in fathers in this study is about 20 times the estimated average concentration of TCDD currently found in human beings in industrialised countries, which could have important public-health implications.

444 citations

Journal ArticleDOI
13 Aug 2010-Science
TL;DR: This work approximated the sensitivity of terrestrial ecosystem respiration to air temperature (Q10) across 60 FLUXNET sites with the use of a methodology that circumvents confounding effects, and suggests a less pronounced climate–carbon cycle feedback than suggested by current carbon cycle climate models.
Abstract: The respiratory release of CO 2 from the land surface is a major flux in the global carbon cycle, antipodal to photosynthetic CO 2 uptake. Understanding the sensitivity of respiratory processes to temperature is central for quantifying the climate–carbon cycle feedback. Here, we approximate the sensitivity of terrestrial ecosystem respiration to air temperature ( Q 10 ) across 60 FLUXNET sites using a methodology that circumvents confounding effects. Contrary to previous findings, our results suggest that Q 10 is independent of mean annual temperature, does not differ among biomes, and is confined to values around 1.4 (±0.1). The strong relation between photosynthesis and respiration, instead, is highly variable among sites. Overall, the results partly explain a less pronounced climate–carbon cycle feedback than suggested by current carbon cycle climate models.

443 citations

Proceedings ArticleDOI
10 May 2008
TL;DR: This paper presents GK-tail, a technique to automatically generate extended finite state machines (EFSMs) from interaction traces, and shows that EFSMs include details that are not captured by either Boolean expressions or (classic) FSM alone, and allow for more accurate analysis and verification than separate models, even if considered jointly.
Abstract: Dynamic analysis of software systems produces behavioral models that are useful for analysis, verification and testing. The main techniques for extracting models of functional behavior generate either models of constraints on data, usually in the form of Boolean expressions, or models of interactions between components, usually in the form of finite state machines. Both data and interaction models are useful for analyzing and verifying different aspects of software behavior, but none of them captures the complex interplay between data values and components interactions. Thus related analysis and testing techniques can miss important information. In this paper, we focus on the generation of models of relations between data values and component interactions, and we present GK-tail, a technique to automatically generate extended finite state machines (EFSMs) from interaction traces. EFSMs model the interplay between data values and component interactions by annotating FSM edges with conditions on data values. We show that EFSMs include details that are not captured by either Boolean expressions or (classic) FSM alone, and allow for more accurate analysis and verification than separate models, even if considered jointly.

439 citations


Authors

Showing all 9226 results

NameH-indexPapersCitations
Carlo Rovelli1461502103550
Giuseppe Mancia1451369139692
Marco Bersanelli142526105135
Teruki Kamon1422034115633
Marco Colonna13951271166
M. I. Martínez134125179885
A. Mennella13246393236
Roberto Salerno132119783409
Federico Ferri132137689337
Marco Paganoni132143888482
Arabella Martelli131131884029
Sandra Malvezzi129132684401
Andrea Massironi129111578457
Marco Pieri129128582914
Cristina Riccardi129162791452
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023173
2022349
20212,468
20202,253
20191,905
20181,706