Browsing by Subject "Statistical analysis"

Now showing 1 - 11 of 11

Open Access
Accounting for parameter uncertainty in large-scale stochastic simulations with correlated inputs
(Institute for Operations Research and the Management Sciences (I N F O R M S), 2011) Biller, B.; Corlu, C. G.
This paper considers large-scale stochastic simulations with correlated inputs having normal-to-anything (NORTA) distributions with arbitrary continuous marginal distributions. Examples of correlated inputs include processing times of workpieces across several workcenters in manufacturing facilities and product demands and exchange rates in global supply chains. Our goal is to obtain mean performance measures and confidence intervals for simulations with such correlated inputs by accounting for the uncertainty around the NORTA distribution parameters estimated from finite historical input data. This type of uncertainty is known as the parameter uncertainty in the discrete-event stochastic simulation literature. We demonstrate how to capture parameter uncertainty with a Bayesian model that uses Sklar's marginal-copula representation and Cooke's copula-vine specification for sampling the parameters of the NORTA distribution. The development of such a Bayesian model well suited for handling many correlated inputs is the primary contribution of this paper. We incorporate the Bayesian model into the simulation replication algorithm for the joint representation of stochastic uncertainty and parameter uncertainty in the mean performance estimate and the confidence interval. We show that our model improves both the consistency of the mean line-item fill-rate estimates and the coverage of the confidence intervals in multiproduct inventory simulations with correlated demands.
Open Access
Discovering modulators of gene expression
(Oxford University Press, 2010-09-01) Babur, Özgün; Demir, Emek; Gönen, M.; Sander, C.; Doğrusöz, Uğur
Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein-protein interactions and transcription factor-target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes. © The Author(s) 2010. Published by Oxford University Press.
Open Access
Distribution of aortic mechanical prosthetic valve closure sound model parameters on the surface of the chest
(Institute of Electrical and Electronics Engineers, 1995-04) Baykal, A.; İder, Y. Z.; Köymen, Hayrettin
It has been previously proposed that heart valve closure sounds can be modeled by a sum of decaying sinusoids, based on the hypothesis that the heart cavity, heart walls, major vessels, and other structures in the chest constitute a frequency selective linear acoustic system and this system is excited by the rapidly decelerating valve occluder. In this study, distribution of the parameters of this model for the second heart sound is investigated. For this purpose, heart sounds of 10 patients who have a St. Jude-type bileaflet mechanical heart valve prosthesis in aortic position are recorded. Recordings are performed at 12 different locations on the surface of the chest. To reliably assign representative parameters to each recording site, signal averaging, model order selection, and a special filtration technique are employed. The results of the analyses are discussed in relation to the above hypothesis on the heart sound generation mechanism. It is observed that site-to-site variation of frequencies of modes does not exceed the accuracy limit of proposed analysis method, but energies of these modes vary on the surface of the chest, and as a result of statistical analysis, it appears that energy of some modes are significantly different between two recording sites.
Open Access
Estimation of a change point in a hazard function based on censored data
(Springer New York LLC, 2003) Gijbels, I.; Gürler, Ü.
The hazard function plays an important role in reliability or survival studies since it describes the instantaneous risk of failure of items at a time point, given that they have not failed before. In some real life applications, abrupt changes in the hazard function are observed due to overhauls, major operations or specific maintenance activities. In such situations it is of interest to detect the location where such a change occurs and estimate the size of the change. In this paper we consider the problem of estimating a single change point in a piecewise constant hazard function when the observed variables are subject to random censoring. We suggest an estimation procedure that is based on certain structural properties and on least squares ideas. A simulation study is carried out to compare the performance of this estimator with two estimators available in the literature: an estimator based on a functional of the Nelson-Aalen estimator and a maximum likelihood estimator. The proposed least squares estimator turns out to be less biased than the other two estimators, but has a larger variance. We illustrate the estimation method on some real data sets.
Open Access
Extremely skewed X-chromosome inactivation patterns in women with recurrent spontaneous abortion
(Wiley-Blackwell Publishing Asia, 2006) Bagislar, S.; Ustuner, I.; Cengiz, B.; Soylemez, F.; Akyerli, C. B.; Ceylaner, S.; Ceylaner, G.; Acar, A.; Ozcelik, T.
Background: The role of extremely skewed X-chromosome inactivation (XCI) has been questioned in the pathogenesis of recurrent spontaneous abortion (RSA) but the results obtained were conflicting. Aims: We therefore investigated the XCI patterns in peripheral blood DNA obtained from 80 patients who had RSA and 160 age-matched controls. Methods: Pregnancy history, age, karyotype, and disease information was collected from all subjects. The methylation status of a highly polymorphic cytosine-adenine-guanine repeat in the androgen-receptor (AR) gene was determined by use of methylation-sensitive restriction enzyme HpaII and polymerase chain reaction. Results: Skewed XCI (> 8 5% skewing) was observed in 13 of the 62 patients informative for the AR polymorphism (20.9%), and eight of the 124 informative controls (6.4%) (P = 0.0069; χ 2 test). More importantly, extremely skewed XCI, defined as > 90% inactivation of one allele, was present in 11 (17.7%) patients, and in only two controls (P = 0.0002; χ 2 test). Conclusions: These results support the interpretation that disturbances in XCI mosaicism may be involved in the pathogenesis of RSA.
Open Access
A hybrid classification model for digital pathology using structural and statistical pattern recognition
(Institute of Electrical and Electronics Engineers, 2013) Ozdemir, E.; Gunduz-Demir, C.
Cancer causes deviations in the distribution of cells, leading to changes in biological structures that they form. Correct localization and characterization of these structures are crucial for accurate cancer diagnosis and grading. In this paper, we introduce an effective hybrid model that employs both structural and statistical pattern recognition techniques to locate and characterize the biological structures in a tissue image for tissue quantification. To this end, this hybrid model defines an attributed graph for a tissue image and a set of query graphs as a reference to the normal biological structure. It then locates key regions that are most similar to a normal biological structure by searching the query graphs over the entire tissue graph. Unlike conventional approaches, this hybrid model quantifies the located key regions with two different types of features extracted using structural and statistical techniques. The first type includes embedding of graph edit distances to the query graphs whereas the second one comprises textural features of the key regions. Working with colon tissue images, our experiments demonstrate that the proposed hybrid model leads to higher classification accuracies, compared against the conventional approaches that use only statistical techniques for tissue quantification. © 2012 IEEE.
Open Access
Investigation of litosphere-ionosphere coupling using total electron content
(IEEE, 2009) Karatay, S.; Arıkan, F.; Arıkan, Orhan
In this study, the relation between Total Electron Content (TEC) estimates obtained from GPS and the earthquakes is examined. Five earthquakes between 2003-2008 occured in Japan with different properties and China earthquake in May 2008 are chosen for the purpose. The 15-days period before and after the registered earthquakes are considered for the basis of this investigation. Also the TEC in computed for each GPS station for the time periods including Ionosphere quiet and disturbed days not without any serious earthquake in the region. For the statistical analysis, the cross correlation function (CC) which is used in the literature before, and the Kullback-Leibler Divergence (KLD) with L2-Norm (L2N) methods which are used for the first time in this context, are applied to the data sets. The computed values for CC, KLD and L2N are compared for both between different GPS stations where available and between consecutive days for the time periods in the data set. With CC analysis, the anomalies existed in the earthquake time intervals are also observed for the quiet days data set. For the earthquakes with scale larger than 6, the possibilities of generating an alarm signal is more likely with a future detailed comperative study of the estimated TEC nearby GPS station estimates in space and time.
Open Access
An investigation of the weights of pattern 1907 bayonets made in the UK around the First World War period
(Routledge, 2017) Ballard, J. M.; Bennett, J.
The standard issue bayonet of the British Army immediately preceding and during the First World War was the Pattern 1907. This was manufactured at different times and in varying numbers during that period by one official body, the Royal Small Arms Factory at Enfield, and by five private contractors. These bayonets were made according to published official specifications issued by the War Department and based on a ‘pattern example’ provided by the Royal Small Arms Factory. The specifications indicate, inter alia, the quality of metal used in making the bayonets, methods of inspection and proofing, and the required maximum and minimum weight range of the completed bayonet. However, examination of a series of these bayonets in a private collection suggested that their weights varied considerably from the mid-point values of the allowed weight ranges in the original and amended specifications (16.5 oz. and 17 oz., respectively). To establish if this was a common feature among this class of bayonet as opposed to a chance factor, the weights of other surviving Pattern 1907 bayonets were determined and compared to establish the degree of variance from the official specifications as originally set out by the Royal Small Arms Factory. Seventy-six percent of the 142 bayonets surveyed were found to be above the mid-point of the allowed weight range given in the amended manufacturing specifications, with many being at the upper end of the allowed range. This is a statistically unusual result. It is speculated that the target weight may have been deliberately set higher by the individual manufacturers to eliminate the possibility of rejection of any underweight bayonets by the Royal Small Arms Factory inspectors and so a refusal of acceptance and payment for the work
Open Access
Investigation of total electron content variability due to seismic and geomagnetic disturbances in the ionosphere
(Wiley-Blackwell Publishing, 2010-10-20) Karatay S.; Arikan, F.; Arıkan, Orhan
Variations in solar, geomagnetic, and seismic activity can cause deviations in the ionospheric plasma that can be detected as disturbances in both natural and man-made signals. Total electron content (TEC) is an efficient means for investigating the structure of the ionosphere by making use of GPS receivers. In this study, TEC data obtained for eight GPS stations are compared with each other using the cross-correlation coefficient (CC), symmetric Kullback-Leibler distance (KLD), and L2 norm (L2N) for quiet days of the ionosphere, during severe geomagnetic storms and strong earthquakes. It is observed that only KLD and L2N can differentiate the seismic activity from the geomagnetic disturbance and quiet ionosphere if the stations are in a radius of 340 km. When TEC for each station is compared with an average quiet day TEC for all periods using CC, KLD, and L2N, it is observed that, again, only KLD and L2N can distinguish the approaching seismicity for stations that are within 150 km radius to the epicenter. When the TEC of consecutive days for each station and for all periods are compared, it is observed that CC, KLD, and L2N methods are all successful in distinguishing the geomagnetic disturbances. Using sliding-window statistical analysis, moving averages of daily TEC with estimated variance bounds are also obtained for all stations and for all days of interest. When these bounds are compared with each other for all periods, it is observed that CC, KLD, and L2N are successful tools for detecting ionospheric disturbances.
Open Access
mESAdb: microRNA expression and sequence analysis database
(Oxford University Press, 2011) Kaya, Koray D.; Karakülah, G.; Yakıcıer, Cengiz M.; Acar, Aybar C.; Konu, Özlen
MicroRNA expression and sequence analysis database (http://konulab.fen. bilkent.edu.tr/mirna/) (mESAdb) is a regularly updated database for the multivariate analysis of sequences and expression of microRNAs from multiple taxa. mESAdb is modular and has a user interface implemented in PHP and JavaScript and coupled with statistical analysis and visualization packages written for the R language. The database primarily comprises mature microRNA sequences and their target data, along with selected human, mouse and zebrafish expression data sets. mESAdb analysis modules allow (i) mining of microRNA expression data sets for subsets of microRNAs selected manually or by motif; (ii) pair-wise multivariate analysis of expression data sets within and between taxa; and (iii) association of microRNA subsets with annotation databases, HUGE Navigator, KEGG and GO. The use of existing and customized R packages facilitates future addition of data sets and analysis tools. Furthermore, the ability to upload and analyze user-specified data sets makes mESAdb an interactive and expandable analysis tool for microRNA sequence and expression data.
Open Access
Strain-and region-specific gene expression profiles in mouse brain in response to chronic nicotine treatment
(Wiley-Blackwell Publishing, 2008) Wang, J.; Gutala, R.; Hwang, Y. Y.; Kim J. -M.; Konu, O.; Ma, J. Z.; Li, M. D.
A pathway-focused complementary DNA microarray and gene ontology analysis were used to investigate gene expression profiles in the amygdala, hippocampus, nucleus accumbens, prefrontal cortex (PFC) and ventral tegmental area of C3H/HeJ and C57BL/6J mice receiving nicotine in drinking water (100 μg/ml in 2% saccharin for 2 weeks). A balanced experimental design and rigorous statistical analysis have led to the identification of 3.5-22.1% and 4.1-14.3% of the 638 sequence-verified genes as significantly modulated in the aforementioned brain regions of the C3H/HeJ and C57BL/6J strains, respectively. Comparisons of differential expression among brain tissues showed that only a small number of genes were altered in multiple brain regions, suggesting presence of a brain region-specific transcriptional response to nicotine. Subsequent principal component analysis and Expression Analysis Systematic Explorer analysis showed significant enrichment of biological processes both in C3H/HeJ and C57BL/6J mice, i.e. cell cycle/proliferation, organogenesis and transmission of nerve impulse. Finally, we verified the observed changes in expression using real-time reverse transcriptase polymerase chain reaction for six representative genes in the PFC region, providing an independent replication of our microarray results. Together, this report represents the first comprehensive gene expression profiling investigation of the changes caused by nicotine in brain tissues of the two mouse strains known to exhibit differential behavioral and physiological responses to nicotine.