P
Pedro Miramontes
Researcher at National Autonomous University of Mexico
Publications - 62
Citations - 848
Pedro Miramontes is an academic researcher from National Autonomous University of Mexico. The author has contributed to research in topics: Coprime integers & Cancer. The author has an hindex of 11, co-authored 62 publications receiving 789 citations. Previous affiliations of Pedro Miramontes include Université de Montréal & Leipzig University.
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On the Evolution of the Single-Subunit RNA Polymerases
Nicolas Cermakian,Tatsuya M. Ikeda,Pedro Miramontes,Bernd Lang,Michael W. Gray,Robert Cedergren +5 more
TL;DR: It is suggested that the origin of the ancestral ssRNAP gene closely paralleled in time the introduction of mitochondria into eukaryotic cells through a eubacterial endosymbiosis.
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Universality of rank-ordering distributions in the arts and sciences.
Gustavo Martínez-Mekler,Roberto Alvarez Martínez,Manuel Beltrán del Río,Ricardo Mansilla,Pedro Miramontes,Germinal Cocho +5 more
TL;DR: A universal behavior of the way in which elements of a system are distributed according to their rank with respect to a given property is uncovered, valid for the full range of values, regardless of whether or not a power law has previously been suggested.
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On the behavior of journal impact factor rank-order distribution
TL;DR: In this paper, an empirical law for the rank-order behavior of journal impact factors is found, and a two-exponent Lotkaian Informetrics is proposed to find extremely good fittings outperforming other rankorder models.
Posted Content
On the Behavior of Journal Impact Factor Rank-Order Distribution
TL;DR: An empirical law for the rank-order behavior of journal impact factors is found and a two-exponent Lotkaian Informetrics is proposed, which is based on the results of an extensive data base on impact factors.
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Fitting Ranked Linguistic Data with Two-Parameter Functions
TL;DR: This paper compares several two-parameter models, including Beta function, Yule function, Weibull function—all can be framed as a multiple regression in the logarithmic scale—in their fitting performance of several ranked linguistic data, such as letter frequencies, word-spacings, and word frequencies.