Browsing by Author "Eyheramendy Duerr, Susana"

Now showing 1 - 20 of 22
  • Thumbnail Image
    Item
    A GROUND-BASED OPTICAL TRANSMISSION SPECTRUM OF WASP-6b
    (2013) Jordán Colzani, Andrés Cristóbal; Espinoza Pérez, Néstor; Rabus, Markus; Eyheramendy Duerr, Susana; Sing, David K.; Desert, Jean Michel; Bakos, Gaspar A.; Fortney, Jonathan J.; López Morales, Mercedes Pierre F. L. Maxted.
  • Thumbnail Image
    Item
    A machine learned classifier for RR Lyrae in the VVV survey
    (2016) Elorrieta López, Felipe; Eyheramendy Duerr, Susana; Jordán Colzani, Andrés Cristóbal; Dekany, Istvan; Catelan, Márcio; Angeloni, Rodolfo; Alonso, J.; Contreras, R.; Gran, F.; Hajdu, G.; Espinoza, N.; Saito, R.; Minniti, D.
  • Thumbnail Image
    Item
    A meta-analysis of gene expression signatures of blood pressure and hypertension
    (2015) Huan, Tianxiao; Esko, Tõnu; Peters, Marjolein J.; Pilling, Luke C.; Schramm, Katharina; Schurmann, Claudia; Chen, Brian H.; Liu, Chunyu; Joehanes, Roby; Eyheramendy Duerr, Susana
  • Thumbnail Image
    Item
    A Near-infrared RR Lyrae Census along the Southern Galactic Plane: The Milky Way's Stellar Fossil Brought to Light
    (2018) Dekany, Istvan; Hajdu, Gergely; Grebel, Eva K.; Catelan, Márcio; Elorrieta López, Felipe; Eyheramendy Duerr, Susana; Majaess, Daniel; Jordán Colzani, Andrés Cristóbal
  • Thumbnail Image
    Item
    A Polygenic Risk Score Suggests Shared Genetic Architecture of Voice Break With Early Markers of Pubertal Onset in Boys
    (2020) Lardone, María C.; Busch, Alexander S.; Santos Martín, José Luis; Miranda, José Patricio; Eyheramendy Duerr, Susana; Pereira, Ana; Juul, Anders; Almstrup, Kristian; Mericq, Verónica; José Patricio, Miranda
  • Thumbnail Image
    Item
    Adaptation to Extreme Environments in an Admixed Human Population from the Atacama Desert
    (2019) Vicuña, Lucas; Fernández, Mario I.; Vial, Cecilia; Valdebenito, Patricio; Chaparro, Eduardo; Espinoza, Karena; Ziegler, Annemarie; Bustamante, Alberto; Eyheramendy Duerr, Susana
  • Thumbnail Image
    Item
    An autoregressive model for irregular time series of variable stars
    (2016) Eyheramendy Duerr, Susana; Elorrieta López, Felipe; Palma M., Wilfredo
  • Thumbnail Image
    Item
    An irregular discrete time series model to identify residuals with autocorrelation in astronomical light curves
    (2018) Eyheramendy Duerr, Susana; Elorrieta López, Felipe; Palma M., Wilfredo
  • Thumbnail Image
    Item
    APOA5 Q97X Mutation Identified through homozygosity mapping causes severe hypertriglyceridemia in a Chilean consanguineous family
    (2012) Dussaillant, Catalina; Serrano Larrea, Valentina; Maiz Gurruchaga, Manuel Alberto; Eyheramendy Duerr, Susana; Cataldo Bascuñan, Luis Rodrigo; Smalley Meylan, Susan Valerie; Rigotti Rivera, Attilio; Rubio, Lorena.; Lagos Arévalo, Carlos Fernando; Santos Martín, José Luis
    Abstract Background Severe hypertriglyceridemia (HTG) has been linked to defects in LPL, APOC2, APOA5, LMF1 and GBIHBP1 genes. However, a number of severe HTG cases are probably caused by as yet unidentified mutations. Very high triglyceride plasma levels (>112 mmol/L at diagnosis) were found in two sisters of a Chilean consanguineous family, which is strongly suggestive of a recessive highly penetrant mutation. The aim of this study was to determine the genetic locus responsible for the severe HTG in this family. Methods We carried out a genome-wide linkage study with nearly 300,000 biallelic markers (Illumina Human CytoSNP-12 panel). Using the homozygosity mapping strategy, we searched for chromosome regions with excess of homozygous genotypes in the affected cases compared to non-affected relatives. Results A large homozygous segment was found in the long arm of chromosome 11, with more than 2,500 consecutive homozygous SNP shared by the proband with her affected sister, and containing the APOA5/A4/C3/A1 cluster. Direct sequencing of the APOA5 gene revealed a known homozygous nonsense Q97X mutation (p.Gln97Ter) found in both affected sisters but not in non-affected relatives nor in a sample of unrelated controls. Conclusion The Q97X mutation of the APOA5 gene in homozygous status is responsible for the severe hypertriglyceridemia in this family. We have shown that homozygosity mapping correctly pinpointed the genomic region containing the gene responsible for severe hypertriglyceridemia in this consanguineous Chilean family.
  • Thumbnail Image
    Item
    Classification and modeling of time series of astronomical data
    (2018) Elorrieta López, Felipe; Eyheramendy Duerr, Susana; Pontificia Universidad Católica de Chile. Facultad de Matemáticas
    We are living in the era of Big Data, where several tools have been developed to deal with large amount of data. These technological advances have allowed the rise of the astronomical surveys. These surveys are capable to take observations from the sky and from them generate information ready to be analyzed. Among the observations available there are light curves of astronomical objects, such as, variable stars, transients or supernovae. Generally, the light curves are irregularly measured in time, since it is not always possible to get observational data from optical telescopes. This issue makes the light curves analysis an interesting statistical challenge, because there are few statistical tools to analyze irregular time series. In addition, due to the large amount of light curves available in each survey, automated processes are also required to analyze all the information efficiently. Consequently, in this thesis two goals are addressed: the classification of the light curves from the implementation of data mining algorithms and the temporal modeling of them. Regarding the classification of light curves, our contribution was to develop a classifier for RR Lyrae variable stars in the Vista Variables in the Via Lactea (VVV) nearin frared survey. It is important to detect RR-Lyraes since they are essential to build a three-dimensional map of the Galactic bulge. In this work, the focus is on RRab type ab (i.e., fundamental-mode pulsators). The final classifier is built following eight key steps that include the choice of features, training set, selection of aperture, and family of classifiers. The best classification performance was obtained by the AdaBoost classifier which achieves an harmonic mean between false positives and false negatives of ≈ 7%. The performance is estimated using cross validation and through the comparison with two independent data sets that were classified by human experts. The classifier implemented has already made it possible to identify some RRab in the outer bulge and the southern galactic disk areas of the VVV. In addition, I worked on modeling light curves. I develop new models to fit irregularly spaced time series. Currently there are few tools to model this type of time series. One example is the Continuous Autoregressive model of order one, CAR(1), however some assumptions must be satisfied in order to use this model. A new alternative to fit irregular time series, that we call the irregular autoregressive model (IAR model), is proposed. The IAR model is a discrete representation of the CAR(1) model which provide more flexibility, since it is not limited by Gaussian time series. However, both the CAR(1) and IAR model are only able to estimate positive autocorrelations. In order to fit negatively correlated irregular time series a Complex irregular autoregressive model (CIAR model) was also developed. For both models maximum likelihood estimation procedures are proposed. Furthermore, the finite sample performance of the parameters estimation is assessed by Monte Carlo simulations. Finally, for both models some applications are proposed on astronomical data. Applications include the detection of multiperiodic variable stars and the verification of the correct estimation of the parameters in models commonly used to fit astronomical light curves.
  • Thumbnail Image
    Item
    Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function
    (2016) Pattaro, Cristian; Teumer, Alexander; Gorski, Mathias; Chu, Audrey Y.; Mijatovic, Vladan; Garnaas, Maija; Tin, Adrienne; Sorice, Rosella; Li, Yong; Eyheramendy Duerr, Susana; Taliun, Daniel; Olden, Matthias; Foster, Meredith; Yang, Qiong; Chen, Ming-HueI; Pers, Tune H.
  • Thumbnail Image
    Item
    Genetic structure characterization of Chileans reflects historical immigration patterns
    (2015) Eyheramendy Duerr, Susana; Martínez, Felipe I.; Manevy, Federico; Vial, Cecilia; Repetto, Gabriela M.
  • No Thumbnail Available
    Item
    Genome-Wide Association Mapping With Longitudinal Data
    (2012) Furlotte, Nicholas A.; Eskin, Eleazar; Eyheramendy Duerr, Susana
  • Thumbnail Image
    Item
    Mapping the outer bulge with RRab stars from the VVV Survey
    (2016) Gran Merino, Felipe Eduardo; Minniti, D.; Saito, R.; Zoccali, Manuela; Gonzalez, O.; Navarrete, C.; Catelan, Márcio; Contreras, R.; Elorrieta López, Felipe; Eyheramendy Duerr, Susana; Jordán Colzani, Andrés Cristóbal
  • Thumbnail Image
    Item
    Sentiment analysis and prediction of events in TWITTER
    (IEEE, 2015) Montesinos, Lucas; Rodríguez, Juan Pablo; Orchard, Marcos; Eyheramendy Duerr, Susana
    Sentiment analysis, also known as opinion mining, is a mechanism for understanding the natural disposition that people possess towards a specific topic. This type of information is very valuable for certain industries - digital marketing companies use sentiment analysis to track the public's mood about a particular product, the view of elected authorities in a given country, or to explain sports allegiances, among many other goals. A common approach to sentiment analysis consists of systematically reviewing content from websites, especially social networks like Facebook, Twitter, and Google+, and using an algorithm to determine the opinions of the masses. For this work, the main body of analysis came from the "Twittersphere." On the Twitter platform, users send 140-character messages to the social network as a means of expressing their viewpoints on certain issues. These messages, or "tweets," are then shown in the user's homepage. Twitter is used widely in Chile. This work analyzed the public's opinions on the presidential primaries for the Alliance political party between Andres Allamand "Renovación Nacional" (RN) and Pablo Longueira from "Union Democrata Independiente" (UDI) using information collected from Twitter in that country. After gathering all relevant data, researchers used sentiment analysis to predict the outcome of the primaries. This data identified citizens who were in favor (positive) of either Allamand or Longueira and people who were against (negative) any political party or persuasion. Researchers designed a dictionary algorithm to aid in these predictions. This was comprised of certain positive and negative words, which, when applied to the Twitter data, was able to determine the polarity of the message: positive, negative, and/or neutral. In addition, an exponential function was used for analyzing the distance between the words, which is useful to gather opinions where both candidates are mentioned, identifying polarity for each of them separately. Later, a score was assigned to each Twitter user. Those cumulative scores were ultimately used to predict the way those given users would vote in the primary elections.
  • Thumbnail Image
    Item
    Simultaneous Modeling of Disease Status and Clinical Phenotypes To Increase Power in Genome-Wide Association Studies
    (2017) Bilow, Michael; Crespo, Fernando; Pan, Zhicheng; Eskin, Eleazar; Eyheramendy Duerr, Susana
  • Thumbnail Image
    Item
    THE ACS FORNAX CLUSTER SURVEY. XI. CATALOG OF GLOBULAR CLUSTER CANDIDATES
    (2015) Jordán Colzani, Andrés Cristóbal; Peng, Eric W.; Blakeslee, John P.; Cote, Patrick; Eyheramendy Duerr, Susana; Ferrarese, Laura
  • Thumbnail Image
    Item
    The ACS Virgo Cluster Survey XVI. Selection Procedure and Catalogs of Globular Cluster Candidates
    (2009) Jordán Colzani, Andrés Cristóbal; Eyheramendy Duerr, Susana
  • Thumbnail Image
    Item
    The Next Generation Virgo Cluster Survey (NGVS). XXXI. The Kinematics of Intracluster Globular Clusters in the Core of the Virgo Cluster
    (2018) Longobardi, Alessia; Peng, Eric W.; Cote, Patrick; Mihos, J. Christopher; Ferrarese, Laura; Puzia, Thomas H.; Lancon, Ariane; Zhang, Hong-Xin; Munoz, Roberto P.; Blakeslee, John P.; Guhathakurta, Puragra; Durrell, Patrick R.; Sanchez-Janssen, Ruben; Toloba, Elisa; Jordán Colzani, Andrés Cristóbal; Eyheramendy Duerr, Susana; Cuillandre, Jean-Charles; Gwyn, Stephen D. J.; Boselli, Alessandro; Duc, Pierre-Alain; Liu, Chengze; Alamo-Martinez, Karla; Powalka, Mathieu; Lim, Sungsoon
  • Thumbnail Image
    Item
    The VVV Templates Project Towards an automated classification of VVV light-curves I. Building a database of stellar variability in the near-infrared
    (2014) Angeloni, Rodolfo; Contreras, R.; Catelan, Márcio; Dekany, Istvan; Gran Merino, Felipe Eduardo; Alonso García, J.; Hempel, Maren; Navarrete Silva, Camila Andrea; Andrews, H.; Beamin, J.; Berger Silva, Christian; Espinoza, N.; Eyheramendy Duerr, Susana; Hajdu, G.; Hempel, A.; Ita, Y.; Jordán Colzani, Andrés Cristóbal; Minniti, D.; Townsend, B.