Zobrazeno 1 - 10
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pro vyhledávání: '"Amaral, Luis A. Nunes"'
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Externí odkaz:
http://arxiv.org/abs/2409.00104
Publikováno v:
Phys. Rev. E 103, 022320 (2021)
Many systems of scientific interest can be conceptualized as multipartite networks. Examples include the spread of sexually transmitted infections, scientific collaborations, human friendships, product recommendation systems, and metabolic networks.
Externí odkaz:
http://arxiv.org/abs/2103.00027
Autor:
Alves, Luiz G. A., Aleta, Alberto, Rodrigues, Francisco A., Moreno, Yamir, Amaral, Luis A. Nunes
Publikováno v:
New Journal of Physics 23, 013043 (2020)
Tremendous advances have been made in our understanding of the properties and evolution of complex networks. These advances were initially driven by information-poor empirical networks and theoretical analysis of unweighted and undirected graphs. Rec
Externí odkaz:
http://arxiv.org/abs/1902.00716
Akademický článek
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How to quantify the impact of a researcher's or an institution's body of work is a matter of increasing importance to scientists, funding agencies, and hiring committees. The use of bibliometric indicators, such as the h-index or the Journal Impact F
Externí odkaz:
http://arxiv.org/abs/1511.00716
Publikováno v:
Phys. Rev. E 91, 062703 -- Published 8 June 2015
High-throughput experimental techniques and bioinformatics tools make it possible to obtain reconstructions of the metabolism of microbial species. Combined with mathematical frameworks such as flux balance analysis, which assumes that nutrients are
Externí odkaz:
http://arxiv.org/abs/1507.01463
Akademický článek
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Autor:
Lancichinetti, Andrea, Sirer, M. Irmak, Wang, Jane X., Acuna, Daniel, Körding, Konrad, Amaral, Luís A. Nunes
Much of human knowledge sits in large databases of unstructured text. Leveraging this knowledge requires algorithms that extract and record metadata on unstructured text documents. Assigning topics to documents will enable intelligent search, statist
Externí odkaz:
http://arxiv.org/abs/1402.0422
Autor:
Duch, Jordi, Zeng, Xiao Han T., Sales-Pardo, Marta, Radicchi, Filippo, Otis, Shayna, Woodruff, Teresa K., Amaral, Luis A. Nunes
Publikováno v:
PLoS ONE 7(12): e51332
Many studies demonstrate that there is still a significant gender bias, especially at higher career levels, in many areas including science, technology, engineering, and mathematics (STEM). We investigated field-dependent, gender-specific effects of
Externí odkaz:
http://arxiv.org/abs/1212.3320
Publikováno v:
Science 325 (5948): 1696-1700 (2009)
Identifying and modeling patterns of human activity has important ramifications in applications ranging from predicting disease spread to optimizing resource allocation. Because of its relevance and availability, written correspondence provides a pow
Externí odkaz:
http://arxiv.org/abs/0909.4724