2024-03-28T22:39:56Zhttp://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/229242021-06-23T10:10:42Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
Barragán, Sandra
author
Peddada, Shyamal
author
2013
Analysis of angular data has a long history with well-developed theory and methodology documented in several books [cf. Fisher (1993), Mardia and Jupp (2000)]. Most of the theory have been developed several decades ago. However, in recent years, and motivated by the applications, there has been a reawaked interest in drawing inferences regarding angular parameters. In particular, in the biology field to analyze periodic patterns of gene expressions. These patterns show the contribution of the genes in oscillatory biological processes, such as the cell-cycle, the circadian clock or the metabolic cycle. The time to peak expression (known as the phase angle) of such a gene can be mapped onto a unit circle and is an angular parameter.
http://uvadoc.uva.es/handle/10324/22924
Estimating and testing circular orders for cell cycle genes expression data
oai:uvadoc.uva.es:10324/229252021-06-23T10:10:43Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Barragán, Sandra
author
Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
Peddada, Shyamal
author
2013
In recent years there has been considerable interest in drawing inferences regarding order relationships among angular parameters. In particular, in biology the interest is to understand genes participating in cell cycle across multiple species and whether they are functionally conserved. The time to peak expression, known as phase angle, of such a gene can be mapped onto a unit circle. Biologists are not only interested in estimating the phase
angles but in determining the relative order of expression of various genes. The final aim is to know whether the order of peak expression among cell cycle genes is conserved evolutionarily across species. These questions are challenging due to large variability among studies and to the circular nature of the data. A methodology to find the underlying circular order in a population is presented. We also propose a solution for the problem of testing equality of circular orders among two or more populations. Unbalanced samples and differences in distributions are taken into consideration. The proposed methodology is illustrated by analyzing data sets from three species: Schizosaccharomyces Pombe, Schizosaccharomyces Cerevisiae and Humans. As a result a set of genes is presented where the circular order is conserved across these three species.
http://uvadoc.uva.es/handle/10324/22925
Inference on circular orders with application to cell cycle gene expression data
oai:uvadoc.uva.es:10324/229262021-06-23T10:10:45Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Rueda Sabater, María Cristina
author
Ugarte Martínez, María Dolores
author
Fernández Militino, Ana
author
2013
In some diseases it is well-known that a unimodal mortality pattern exists. A clear example in developed countries is breast cancer, where mortality increased sharply until the nineties and then decreased. This clear unimodal pattern is not necessarily generalizable to all regions within a country. In this work, we develop statistical tests to check if this unimodality persists within regions using order restricted inference. The same methodology will be also used to provide change-points within regions as well as con dence intervals. Results will be illustrated using age-speci c breast cancer mortality data from Spain in the period 1975-2005.
http://uvadoc.uva.es/handle/10324/22926
Testing for unimodality in mortality trends
oai:uvadoc.uva.es:10324/229272021-06-23T10:10:46Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
Barragán, Sandra
author
2014
In this talk we deal with the problem of obtaining a Circular Order on a set of n items using angular values from p heterogeneous data sets. The problem resembles the classical problem of determining the true order or ranks among n objects using the ranks assigned by p independent judges. Although there exist a huge literature in ranking aggregation for Euclidean data, the problem is unexplored in the circular setting, where the Euclidean methods cannot be directly applied due to the underlying geometry of the circle. We consider two original proposals.
http://uvadoc.uva.es/handle/10324/22927
Two proposals for circular ordering aggregation
oai:uvadoc.uva.es:10324/229282021-06-23T10:10:47Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Larriba González, Yolanda
author
Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
2015
Identification of periodic patterns in gene expression data is important for studying the regulation mechanism of the circadian system. The information available is often given only by one or two cycles. Consequently, the number of observations is not enough to fit certain models, such as Fourier's models, properly. Some authors have already developed procedures or algorithms among which the JTK\_Cycle algorithm is the most popular one.
We propose a new method to identify cyclic gene expressions based on circular order restricted inference. Validation of the method is made through real data sets and simulations. Moreover, we compare the results obtained by the method with other detecting methods developed in the literature.
http://uvadoc.uva.es/handle/10324/22928
A new method for identification of cyclic circadian genes using circular isotonic regression.
oai:uvadoc.uva.es:10324/229342021-06-23T10:10:49Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
dc
Larriba González, Yolanda
author
Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
2015
Identification of periodic patterns in gene expression data is important for studying the regulation mechanism of the circadian system. However, the information available is often given by one or two cycles. Consequently, the number of observations is not enough to fit certain models, such as Fourier´s models. Some authors have yet developed procedures or algorithms among which is the JTK_Cycle Algorithm.
We propose a new method to address this question based on order restricted inference. Which allows to determine, in terms of an euclidean or circular order, if the gene expression given is or not cyclic.
Validation of the method is made by evaluating of real data sets and simulations. Moreover, we compare the results obtained by the method with others detecting methods developed in the literature, mainly with the JTK_Cycle Algorithm.
http://uvadoc.uva.es/handle/10324/22934
A new method for circadian gene identification using order restricted inference
oai:uvadoc.uva.es:10324/229302021-06-23T10:10:48Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
Barragán, Sandra
author
Mardia, Kanti
author
Peddada, Shyamal
author
2015
This work is motivated by a problem encountered in Molecular Biology where researchers are interested in correlating angular data from two oscillatory systems. The observations are the time to peak expression (also known as phase angle) of periodic genes under two different conditions (dose levels, organs or even species). In particular, we deal here with expression data from genes participating in the cell-cycle. Cell-biologists are often interested in drawing inferences regarding the phase angle of cell-cycle genes since they are considered to be associated with the gene’s biological function (Jensen et al 2006).
http://uvadoc.uva.es/handle/10324/22930
Circular Isotone Regression with Application to cell-cycle Biology
oai:uvadoc.uva.es:10324/229332021-06-23T10:10:49Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
dc
Larriba González, Yolanda
author
Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
2015
Identification of periodic patterns in gene expression data is important for studying the regulation mechanism of the circadian system. The information available is often given only by one or two cycles. Consequently, the number of observations is not enough to fit certain models, such as Fourier's models, properly. Some authors have already developed procedures or algorithms among which the JTK\_Cycle algorithm is the most popular one.
We propose a new method to identify cyclic gene expressions based on circular order restricted inference. Validation of the method is made through real data sets and simulations. Moreover, we compare the results obtained by the method with other detecting methods developed in the literature.
http://uvadoc.uva.es/handle/10324/22933
A new method for identification of cyclic circadian genes using circular isotonic regression.
oai:uvadoc.uva.es:10324/229352021-06-23T10:10:51Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
dc
Larriba González, Yolanda
author
Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
Peddada, Shyamal
author
2016
The determination of rhythmic signals in oscillatory systems, such as cell cycle or circadian clock, is essential for biologists to know which genes
are associated to the system. While there are several procedures available for this task in the literature, none of them is satisfactory enough. One of
the reasons for this is the absence of a good definition of rhythmic signal. We propose a new definition of rhythmic signal using order restrictions
and taking into account the needs of the biologists, and an algorithm based on order restricted inference and conditional tests to detect and classify
the signals in different groups. We test the algorithm in simulations and with real databases from circadian clock, and compare it with the most
usual methods available showing its good performance.
http://uvadoc.uva.es/handle/10324/22935
Detection of rhythmic signals in Oscillatory Systems using order Restricted Inference
oai:uvadoc.uva.es:10324/229362021-06-23T10:10:52Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
dc
Larriba González, Yolanda
author
Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
Peddada, Shyamal
author
2016
High-throughput microarray technologies are a widely used research tool in gene expression analysis. A large variety of preprocessing methods
for raw intensity measures is available to establish gene expression values. Normalization is the key stage in preprocessing methods, since it
removes systematic variations in microarray data. Then, the choice of the normalization strategy can make a substantial impact to the final results.
Additionally, we have observed that the identification of rhythmic circadian genes depends not only on the normalization strategy but also on
the rhythmicity detection algorithm employed. We analyze three different rhythmicity detection algorithms. On the one hand, JTK and RAIN
which are widely extended among biologists. On the other hand, ORIOS, a novel statistical methodology which heavily relies on Order Restricted
Inference and that we propose to detect rhythmic signal for Oscillatory Systems. Results on the determination of circadian rhythms are compared
using artificial microarray data and publicly available circadian data bases.
http://uvadoc.uva.es/handle/10324/22936
Influence of microarray normalization strategies and rhythmicity detection algorithms to detect circadian rhythms
oai:uvadoc.uva.es:10324/229372021-06-23T10:10:53Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
dc
Larriba González, Yolanda
author
Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
Peddada, Shyamal
author
2016
Microarrays are a widely used research tool in gene expression analysis. A large variety
of preprocessing methods for raw intensity measures is available to establish gene expression values. Normalization is the key stage in preprocessing methods, since
it removes systematic variations in microarray data. Then, the subsequent analyses
may be highly dependent on normalization strategy employed. Our research focuses
on detecting rhythmic signals in measured circadian gene expressions. We have observed
that rhythmicity detection depends not only upon the rhythmicity detection
algorithm but also upon the normalization strategy employed. We analyze the effects
of well-known normalization strategies in literature within three different rhythmicity
detection algorithms; JTK, RAIN and our recently proposal ORI, a novel statistical
methodology based on Order Restricted Inference. The results obtained are compared
using artificial microarray data and publicly available circadian data bases.
http://uvadoc.uva.es/handle/10324/22937
Evaluation of microarray normalization strategies to detect cyclic circadian genes.
oai:uvadoc.uva.es:10324/229382021-06-23T10:10:54Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Larriba González, Yolanda
author
Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
Peddada, Shyamal
author
2016
The study of biological rhythms is receiving a lot of attention in the literature in
recent years. At the core of this research lies the methodological problem of how to
detect rhythmic signals in measured data. Night and day, or dark and light patterns
impact on human health in many different ways. For this reason, researchers are
studying the effect of sleep on the circadian clock in human body during various stages
of life. Important components of this clock are the circadian genes which have rhythmic
expression overtime with phases suitably matching the night and day. Consequently,
the identification of rhythmic signals is a problem of considerable interest for biologists.
In this work, we develop a novel statistical procedure to detect rhythmic signals in
oscillatory systems based on Order Restricted Inference (ORI). This methodology is
tested both on simulations and on real data bases. Moreover the obtained results are
compared with the most widely extended rhythmicity detection algorithms in literature.
http://uvadoc.uva.es/handle/10324/22938
A new method for detection of rhythmic signals in oscillatory systems
oai:uvadoc.uva.es:10324/259452021-06-23T10:10:55Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Fernández Temprano, Miguel Alejandro
author
2017
Circular-circular models, used for situations where a circular response is to be predicted using another circular variable, are frequent in the circular statistics literature as they appear in many practical situations. One of these is that of trying to relate the peak expressions of cell-cycle genes coming from two different species with possibly di erent cell phase lengths.
Several different models have been considered for these situations. Some of them, such as those in Downs and Mardia (2002), Rueda et al. (2009), Di Marzio et al. (2013) or Rueda et al. (2016), will be described in the talk. We will see that it is not easy to compare and select among them as some involve non-standard features. To overcome this problem, we propose a selection criteria based on the work by Ye (1998) for the Euclidean setting. We will check the performance of this criterion for the aforementioned cell-cycle data.
Advances in Directional Statistics (ADISTA 2017). Roma Tre University, Rome, Italy. p.11
http://uvadoc.uva.es/handle/10324/25945
Model selection for circular-circular models
oai:uvadoc.uva.es:10324/259472021-06-23T10:10:56Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Larriba González, Yolanda
author
2017
Many biological processes, such as cell cycle, circadian clock or menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit periodic patterns over time. Modelling these rhythms is a challenge in literature since usually the sampling density is low, the number of periods is generally two and the underlying signals adopt a wide range of temporal patterns, see Larriba et al. (2016). Several authors proposed parametric functions of time, such as the sinusoidal function, to model these signals. However these parametric functions might be too rigid for data derived from cell-cycle or circadian clock.
Among these, a common shape of interest to a biologist is the circular up-down-up signal with a unique peak (U) and a unique trough (L) within each period. The shape of these signals is entirely described by mathematical inequalities among their components which allow to establish a relationship between the euclidean and the circular space using circular isotonic regression. In this work we state this connection between the euclidean and the circular
space based on circular isotonic regression, formulate the ML isotonic regression estimator under circular up-down-up constraints and assess its computational advantages to calculate the circular isotonic regression estimator (CIRE), see Rueda et al. (2009). Results are shown both on simulations and on real data.
Advances in Directional Statistics (ADISTA 2017). Roma Tre University, Rome, Italy, p.46
http://uvadoc.uva.es/handle/10324/25947
Modelling biological rhythms using order restricted inference
oai:uvadoc.uva.es:10324/259482021-06-23T10:10:57Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
dc
Larriba González, Yolanda
author
Rueda Sabater, María Cristina
author
Fernández Temprano, Miguel Alejandro
author
Peddada, Shyamal
author
2017
Microarray gene expression data are extremely noisy. Normalization is widely regarded as an essential step before data analysis to remove systematic variations while maintaining biological signals of interest. However, the choice of normalization may substantially impact the detection of rhythmic genes in oscillatory systems. We introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes robust with respect to the normalization choice.
IV Congreso de Jóvenes Investigadores en Diseño de Experimentos y Bioestadística. Salamanca: Universidad de Salamanca, 2017
http://uvadoc.uva.es/handle/10324/25948
A normalization-robust bootstrap-based rhythmicity measure to detect rhythmic genes in oscillatory systems
oai:uvadoc.uva.es:10324/353182021-07-15T08:54:54Zcom_10324_1151com_10324_931com_10324_894com_10324_1170col_10324_1280col_10324_1369
00925njm 22002777a 4500
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San José Alonso, Julio Francisco
author
Platón, Luis
author
Mata Crespo, Raquel
author
Guijarro Rubio, A.
author
Martínez Cabero, M. A.
author
2016
Las políticas energéticas exigen mejorar la eficiencia energética del sector servicios, que en el año 2014 supuso un 10,7 % del consumo de energía primaria de España.Los Centros sanitarios en España suponen el 6,8 % del consumo del sector servicios y en términos económicos supone un gasto cercano a los 700 millones de euros.
La mejora en la eficiencia energética de un hospital se consigue con la implementación de Medidas de Mejora de la Eficiencia Energética (MMEE). Las MMEE deben producir una reducción en el consumo de energía primaria del hospital,y dichoahorro se debe poder cuantificar. En este sentido, el Protocolo Internacional de Medida y Verificación (IPMVP) establece cuatro opciones para su cuantificación: A) Verificación aislada de la MMEE, medición de parámetros clave. B) Verificación aislada las MMEE, medición de todos los parámetros. C) Verificación de toda la instalación y D) Simulación calibrada.
Este artículo se centra en la opción C) verificación de toda la instalación, que consisteen obtener un modelo matemático que representala línea base de consumo de gas natural del hospital, partiendo del histórico de consumos del hospital, como estos modelos son validados estadísticamente y como se comprueba su bondad de ajuste para ser empleados en el ámbito energético mediante el cumplimiento de parámetros de calidad establecidos en el IPMVP.
- Coeficiente de determinación R2> 0,75.
- Coeficiente de variación CV < 0,2
- Sesgo < 0,005%
Los modelos permiten, al comparar los consumos energéticos reales con los estimados, detectar posibles consumos anómalos y evaluar el impacto de lasposibles MMEE.
Pedro Blanes, Antonio de. XXXIV Seminario de Ingeniería Hospitalaria. Congreso Nacional. Alicante: Asociación Española de Ingeniería Hospitalaria, 2016
http://uvadoc.uva.es/handle/10324/35318
Hospitales-Consumo de energía
Política energética
Validación estadística y criterios a considerar en la obtención de los modelos que representan la línea base de consumo de gas natural en Hospitales
oai:uvadoc.uva.es:10324/387482021-06-23T10:11:00Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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Torres Díaz, Raúl Andrés
author
Álvarez Esteban, Pedro César
author
Peña, Nicolás
author
2019
Air transportation growth is a reality described by different sources (e.g. The World Bank [1], the latest Eurocontrol report [2]). One essential initiative required to improve air traffic capacity while maintaining or increasing safety is to introduce predictive analytics that enable a dynamic adaptation of airline operations in a preemptive manner to an ever changing environment. An important part of this task is to model airport operations and plan accordingly. Particularly runway usage and/or configuration are important aspects of these operations. For example, prior knowledge of runway usage could improve flight plan optimizers outputs. Of course, to create any model or predictor, ground truth data is required. However most of the time, detailed information about runway historical usage/configuration is inaccessible, unreliable or it belongs to national ATC services providers. Then, thinking on a high-scale forecast methodology there is an important drawback given the lack of a feasible target for most of the airports. Thus, the goal of this work is to introduce an accessible, easy to implement algorithm that allows historical reconstruction of runway usage/configuration for any airport based on data transmitted from aircrafts through either Radar or ADS-B technologies, even when the track data is not consistent. We study the quality of the assessment performed by the two outputs of the algorithm: 1) Measuring runway usage accuracy in comparison to the report given by the Spanish ATC service provider (ENAIRE) for each flight landing to or taking off from two Spanish airports, Madrid-Barajas and Barcelona-El Prat, during October 2016. 2) Comparing the Netherlands-Schiphol runway configuration reported by the Netherlands airspace regulator (LVNL) for three different months: February, April and August 2018. The results provide values above 97% of accuracy for both types of assessment.
2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC), San Diego, California, EEUU
http://uvadoc.uva.es/handle/10324/38748
An Algorithm to Determine Airport Runway Usage/Configuration Based on Aircraft Trajectories
oai:uvadoc.uva.es:10324/405422021-06-23T10:11:01Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
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González Arteaga, María Teresa
author
Andrés Calle, Rocío de
author
2017
A non-traditional approach about the measurement of agents’ preference stability is introduced. This contribution focus on measuring preference consensus at different moments under the assumption of considering the following evaluations: approved, undecided and disapproved. To this aim, the concept of
preference stability measure is defined as well as a particular one, the sequential preference stability measure, taking into account any two successive time moments. Finally and in order to
highlight the good behaviour of novel measures, some properties are also provided.
Electronic ISSN: 1558-4739
http://uvadoc.uva.es/handle/10324/40542
10.1109/FUZZ-IEEE.2017.8015465
New approach to measure preference stability
oai:uvadoc.uva.es:10324/648952024-01-23T20:05:18Zcom_10324_1151com_10324_931com_10324_894col_10324_1280
00925njm 22002777a 4500
dc
Rodríguez del Tío, María Pilar
author
Hidalgo Alonso, Santiago
author
Palacios Picos, Andrés
author
2012
In this paper we study the level of mathematics anxiety that students in the first grade of Statistics degrees experience. We analize the relation between this construct and other factors such as gender, degrees profile (Bussines, Mathematics or General) and the mathematics subject studied in the previous year. The results show that female students have more mathematics anxiety than male students in groups determinated by the two already mention factors, which show a higher level of anxiety. This groups belong to the Bussines profile and to students who studied the previous year the subject "Mathematics for Social Sciences".
Castro, AE (Castro, AE). Baeza, Spain, 2012, p.469-478
978-84-695-4466-2
https://uvadoc.uva.es/handle/10324/64895
MATHEMATICS ANXIETY IN STATISTICS UNDERGRADUATES