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Institution

University of Warsaw

EducationWarsaw, Poland
About: University of Warsaw is a education organization based out in Warsaw, Poland. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 20832 authors who have published 56617 publications receiving 1185084 citations. The organization is also known as: Uniwersytet Warszawski & Warsaw University.


Papers
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Journal ArticleDOI
TL;DR: The 3DEpiLoop algorithm predicts three-dimensional chromatin looping interactions within topologically associating domains (TADs) from one-dimensional epigenomics and transcription factor profiles using the statistical learning.
Abstract: This study aims to understand through statistical learning the basic biophysical mechanisms behind three-dimensional folding of epigenomes. The 3DEpiLoop algorithm predicts three-dimensional chromatin looping interactions within topologically associating domains (TADs) from one-dimensional epigenomics and transcription factor profiles using the statistical learning. The predictions obtained by 3DEpiLoop are highly consistent with the reported experimental interactions. The complex signatures of epigenomic and transcription factors within the physically interacting chromatin regions (anchors) are similar across all genomic scales: genomic domains, chromosomal territories, cell types, and different individuals. We report the most important epigenetic and transcription factor features used for interaction identification either shared, or unique for each of sixteen (16) cell lines. The analysis shows that CTCF interaction anchors are enriched by transcription factors yet deficient in histone modifications, while the opposite is true in the case of RNAP II mediated interactions. The code is available at the repository https://bitbucket.org/4dnucleome/3depiloop .

1,241 citations

Journal ArticleDOI
TL;DR: In this article, a measurement of the spin asymmetry and determination of the structure function g1 in deep inelastic muon-proton scattering was carried out for the first time.

1,240 citations

Journal ArticleDOI
TL;DR: In this article, a modified oscillator model is used to calculate the nuclear potential energy surfaces as a function of deformations. And the average behavior of the surface is normalized to that of a liquid drop through the employment of a generalized Strutinsky prescription, and a synthesis of the single-particle model and the liquid-drop model is obtained.

1,231 citations

Journal ArticleDOI
B. P. Abbott1, R. Abbott1, T. D. Abbott2, Sheelu Abraham3  +1271 moreInstitutions (145)
TL;DR: In 2019, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9 and the Virgo detector was also taking data that did not contribute to detection due to a low SINR but were used for subsequent parameter estimation as discussed by the authors.
Abstract: On 2019 April 25, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9. The Virgo detector was also taking data that did not contribute to detection due to a low signal-to-noise ratio, but were used for subsequent parameter estimation. The 90% credible intervals for the component masses range from to if we restrict the dimensionless component spin magnitudes to be smaller than 0.05). These mass parameters are consistent with the individual binary components being neutron stars. However, both the source-frame chirp mass and the total mass of this system are significantly larger than those of any other known binary neutron star (BNS) system. The possibility that one or both binary components of the system are black holes cannot be ruled out from gravitational-wave data. We discuss possible origins of the system based on its inconsistency with the known Galactic BNS population. Under the assumption that the signal was produced by a BNS coalescence, the local rate of neutron star mergers is updated to 250-2810.

1,189 citations

Journal ArticleDOI
B. P. Abbott1, Richard J. Abbott1, T. D. Abbott2, Matthew Abernathy3  +978 moreInstitutions (112)
TL;DR: The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers as discussed by the authors.
Abstract: The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers. In this paper we present full results from a search for binary black hole merger signals with total masses up to 100M⊙ and detailed implications from our observations of these systems. Our search, based on general-relativistic models of gravitational wave signals from binary black hole systems, unambiguously identified two signals, GW150914 and GW151226, with a significance of greater than 5σ over the observing period. It also identified a third possible signal, LVT151012, with substantially lower significance, which has a 87% probability of being of astrophysical origin. We provide detailed estimates of the parameters of the observed systems. Both GW150914 and GW151226 provide an unprecedented opportunity to study the two-body motion of a compact-object binary in the large velocity, highly nonlinear regime. We do not observe any deviations from general relativity, and place improved empirical bounds on several high-order post-Newtonian coefficients. From our observations we infer stellar-mass binary black hole merger rates lying in the range 9−240Gpc−3yr−1. These observations are beginning to inform astrophysical predictions of binary black hole formation rates, and indicate that future observing runs of the Advanced detector network will yield many more gravitational wave detections.

1,172 citations


Authors

Showing all 21191 results

NameH-indexPapersCitations
Alexander Malakhov139148699556
Emmanuelle Perez138155099016
Piotr Zalewski135138889976
Krzysztof Doroba133144089029
Hector F. DeLuca133130369395
Krzysztof M. Gorski132380105912
Igor Golutvin131128288559
Jan Krolikowski131128983994
Michal Szleper130123882036
Anatoli Zarubin129120486435
Malgorzata Kazana129117581106
Artur Kalinowski129116281906
Predrag Milenovic129118581144
Marcin Konecki128117879392
Karol Bunkowski128119279455
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023176
2022619
20212,880
20203,208
20193,130
20183,164