Search results for "Probability."
showing 10 items of 3396 documents
A Dirichlet Autoregressive Model for the Analysis of Microbiota Time-Series Data
2021
Growing interest in understanding microbiota dynamics has motivated the development of different strategies to model microbiota time series data. However, all of them must tackle the fact that the available data are high-dimensional, posing strong statistical and computational challenges. In order to address this challenge, we propose a Dirichlet autoregressive model with time-varying parameters, which can be directly adapted to explain the effect of groups of taxa, thus reducing the number of parameters estimated by maximum likelihood. A strategy has been implemented which speeds up this estimation. The usefulness of the proposed model is illustrated by application to a case study.
Genome-scale analysis of evolutionary rate and selection in a fast-expanding Spanish cluster of HIV-1 subtype F1.
2018
Abstract This work is aimed at assessing the presence of positive selection and/or shifts of the evolutionary rate in a fast-expanding HIV-1 subtype F1 transmission cluster affecting men who have sex with men in Spain. We applied Bayesian coalescent phylogenetics and selection analyses to 23 full-coding region sequences from patients belonging to that cluster, along with other 19 F1 epidemiologically-unrelated sequences. A shift in the overall evolutionary rate of the virus, explained by positively selected sites in the cluster, was detected. We also found one substitution in Nef (H89F) that was specific to the cluster and experienced positive selection. These results suggest that fast tran…
Toward a direct and scalable identification of reduced models for categorical processes.
2017
The applicability of many computational approaches is dwelling on the identification of reduced models defined on a small set of collective variables (colvars). A methodology for scalable probability-preserving identification of reduced models and colvars directly from the data is derived—not relying on the availability of the full relation matrices at any stage of the resulting algorithm, allowing for a robust quantification of reduced model uncertainty and allowing us to impose a priori available physical information. We show two applications of the methodology: (i) to obtain a reduced dynamical model for a polypeptide dynamics in water and (ii) to identify diagnostic rules from a standar…
Identifying Prognostic SNPs in Clinical Cohorts: Complementing Univariate Analyses by Resampling and Multivariable Modeling
2016
Clinical cohorts with time-to-event endpoints are increasingly characterized by measurements of a number of single nucleotide polymorphisms that is by a magnitude larger than the number of measurements typically considered at the gene level. At the same time, the size of clinical cohorts often is still limited, calling for novel analysis strategies for identifying potentially prognostic SNPs that can help to better characterize disease processes. We propose such a strategy, drawing on univariate testing ideas from epidemiological case-controls studies on the one hand, and multivariable regression techniques as developed for gene expression data on the other hand. In particular, we focus on …
Melanoma-Nevus Discrimination Based on Image Statistics in Few Spectral Channels
2016
The purpose of this paper is to offer a method for discrimination of cutaneous melanoma from benign nevus, founded on analysis of skin lesion image. At the core of method is calculation of mean and standard deviation of pixel optical density values for a few narrow spectral bands. Calculated values are compared with discriminating thresholds derived from a set of images of benign nevi and melanomas with known diagnosis. Classification is done applying weighted majority rule to results of thresholding. Verification against the available multispectral images of 32 melanomas and 94 benign nevi has shown that the method using three spectral bands provided zero false negative and four false posi…
Intermittent targeted therapies and stochastic evolution in patients affected by chronic myeloid leukemia
2016
Front line therapy for the treatment of patients affected by chronic myeloid leukemia (CML) is based on the administration of tyrosine kinase inhibitors, namely imatinib or, more recently, axitinib. Although imatinib is highly effective and represents an example of a successful molecular targeted therapy, the appearance of resistance is observed in a proportion of patients, especially those in advanced stages. In this work, we investigate the appearance of resistance in patients affected by CML, by modeling the evolutionary dynamics of cancerous cell populations in a simulated patient treated by an intermittent targeted therapy. We simulate, with the Monte Carlo method, the stochastic evolu…
The best strategy for RAS wild-type metastatic colorectal cancer patients in first-line treatment: A classic and Bayesian meta-analysis
2018
Background: At present, there is uncertainty on the best systemic treatment in first-line setting for RAS wild-type (WT) metastatic colorectal cancer (mCRC) patients. Indeed, several chemotherapy and biologics combinations showed an improvement on survival. We performed a systematic review with a pair-wise and bayesan meta-analysis to rank the best strategy for these patients. Methods: A systematic literature search through March 2017 was performed to evaluate the association between several treatment combinations and overall survival (OS), progression-free survival (PFS), overall response rate (ORR) and toxicity rate (TR) in RAS WT mCRC patients. Data were extracted from studies and pooled…
Generalized Molecular Descriptors Derived From Event-Based Discrete Derivative.
2016
In the present study, a generalized approach for molecular structure characterization is introduced, based on the relation frequency matrix (F) representation of the molecular graph and the subsequent calculation of the corresponding discrete derivative (finite difference) over a pair of elements (atoms). In earlier publications (22- 24), an unique event, named connected subgraphs, (based on the Kier-Hall's subgraphs) was systematically employed for the computation of the matrix F. The present report is a generalization of this notion, in which eleven additional events are introduced, classified in three categories, namely, topological (terminal paths, vertex path incidence, quantum subgrap…
Statistical characterization of deviations from planned flight trajectories in air traffic management
2016
Understanding the relation between planned and realized flight trajectories and the determinants of flight deviations is of great importance in air traffic management. In this paper we perform an in depth investigation of the statistical properties of planned and realized air traffic on the German airspace during a 28 day periods, corresponding to an AIRAC cycle. We find that realized trajectories are on average shorter than planned ones and this effect is stronger during night-time than daytime. Flights are more frequently deviated close to the departure airport and at a relatively large angle to destination. Moreover, the probability of a deviation is higher in low traffic phases. All the…
Newly Digitized Database Reveals the Lives and Families of Forced Migrants from Finnish Karelia
2017
Studies on displaced persons often suffer from a lack of data on the long-term effects of forced migration. A register created during 1960s and published as a book series ‘Siirtokarjalaisten tie’ in 1970 documented the lives of individuals who fled the southern Karelian district of Finland after its first and second occupation by the Soviet Union in 1940 and 1944. To realize the potential value of these data for scientific research, we have recently scanned the register using optical character recognition (OCR) software, and developed proprietary computer code to extract these data. Here we outline the steps involved in the digitization process, and present an overview of the Migration Kare…