On Locally Dyadic Stationary Processes

We introduce the concept of local dyadic stationarity, to account for non-stationary time series, within the framework of Walsh-Fourier analysis. We define and study the time varying dyadic ARMA models (tvDARMA). It is proven that the general tvDARMA process can be approximated locally by either a tvDMA and a tvDAR process.Comment: 27 pages, 2 figure

Whole genome scanning of a Mediterranean basin hotspot collection provide new insights into olive tree biodiversity and biology

Olive tree (Olea europaea L. subsp. europaea var. europaea) is one of the most important species of the Mediterranean region and one of the most ancient species domesticated. The availability of whole genome assemblies and annotations of olive tree cultivars and oleaster (O. europaea subsp. europaea var. sylvestris) has contributed to a better understanding of genetic and genomic differences between olive tree cultivars. However, compared to other plant species there is still a lack of genomic resources for olive tree popula-tions that span the entire Mediterranean region. In the present study we developed the most complete genomic variation map and the most comprehensive catalog/resource of molecular variation to date for 89 olive tree genotypes originating from the entire Mediterranean basin, revealing the genetic diversity of this commercially significant crop tree and explaining the divergence/similarity among different variants. Addi-tionally, the monumental ancient tree ‘Throuba Naxos’ was studied to characterize the potential origin or routes of olive tree domestication. Several candidate genes known to be associated with key agronomic traits, including olive oil quality and fruit yield, were uncovered by a selective sweep scan to be under selection pressure on all olive tree chromosomes. To further exploit the genomic and phenotypic resources obtained from the current work, genome-wide association analyses were performed for 23 morphological and two agronomic traits. Significant associations were detected for eight traits that provide valuable candidates for fruit tree breeding and for deeper understanding of olive tree biology.info:eu-repo/semantics/publishedVersio

Different spectra of recurrent gene mutations in subsets of chronic lymphocytic leukemia harboring stereotyped B-cell receptors.

We report on markedly different frequencies of genetic lesions within subsets of chronic lymphocytic leukemia patients carrying mutated or unmutated stereotyped B-cell receptor immunoglobulins in the largest cohort (n=565) studied for this purpose. By combining data on recurrent gene mutations (BIRC3, MYD88, NOTCH1, SF3B1 and TP53) and cytogenetic aberrations, we reveal a subset-biased acquisition of gene mutations. More specifically, the frequency of NOTCH1 mutations was found to be enriched in subsets expressing unmutated immunoglobulin genes, i.e. #1, #6, #8 and #59 (22-34%), often in association with trisomy 12, and was significantly different (P<0.001) to the frequency observed in subset #2 (4%, aggressive disease, variable somatic hypermutation status) and subset #4 (1%, indolent disease, mutated immunoglobulin genes). Interestingly, subsets harboring a high frequency of NOTCH1 mutations were found to carry few (if any) SF3B1 mutations. This starkly contrasts with subsets #2 and #3 where, despite their immunogenetic differences, SF3B1 mutations occurred in 45% and 46% of cases, respectively. In addition, mutations within TP53, whilst enriched in subset #1 (16%), were rare in subsets #2 and #8 (both 2%), despite all being clinically aggressive. All subsets were negative for MYD88 mutations, whereas BIRC3 mutations were infrequent. Collectively, this striking bias and skewed distribution of mutations and cytogenetic aberrations within specific chronic lymphocytic leukemia subsets implies that the mechanisms underlying clinical aggressiveness are not uniform, but rather support the existence of distinct genetic pathways of clonal evolution governed by a particular stereotyped B-cell receptor selecting a certain molecular lesion(s

Theory of inhomogeneous Markov systems of high order

In the current dissertation we are defining and founding the inhomogeneous Markov system of high order, which takes into consideration the fact that the transition of a member depends not only on its present state but also on the states in which the member was during the preceding time moments, let be the number. In this respect, we introduce the superficial razor cut mixture transition distribution model. We examine the asymptotic behavior of the system, under assumptions easily met in practice. We prove that asymptotically the marginal probability distribution converges, to the respective marginal probability distribution of the first order homogeneous Markov chain. We also determine the asymptotic behavior of the expected population structure and that of the relative expected population structure for the inhomogeneous Markov system of high order. We continue by examining the variability of the state sizes of the inhomogeneous Markov system and their relation with the respective variability for the N.H.M.S. of first order. We also determine the asymptotic behavior of the variability of the state sizes, under assumptions easily met in practice. Finally, we determine the relationship satisfied by the join probabilities of the inhomogeneous Markov chain of lag and provide the conditions under which we have a unique solution. We examine the structure of the autocorrelations and prove that they satisfy a system of linear equations, which is analogue with the one by Yule-Walker in time series.Στην παρούσα διατριβή θεμελιώνουμε το μη ομογενές Μαρκοβιανό Σύστημα ανώτερης τάξης, το οποίο λαμβάνει υπόψη το γεγονός ότι εν γένει η μετάβαση ενός μέλους εξαρτάται όχι μόνο από το παρόν, αλλά και από τις καταστάσεις στις οποίες βρέθηκε κατά τις προηγούμενες χρονικές στιγμές, έστω το πλήθος. Στα πλαίσια αυτού του συστήματος εισάγουμε το μη ομογενές επιφανειακής τομής μίξης μοντέλο κατανομής μετάβασης. Διερευνούμε την ασυμπτωτική συμπεριφορά του συστήματος, κάτω από συγκεκριμένες συνθήκες οι οποίες είναι εύκολο να συναντηθούν στην πράξη και αποδεικνύουμε ότι ασυμπτωτικά η περιθώρια κατανομή του, συγκλίνει σε αυτήν της πρώτης τάξης ομογενούς Μαρκοβιανής Αλυσίδας. Στη συνέχεια, προσδιορίζουμε την ασυμπτωτική συμπεριφορά της αναμενόμενης πληθυσμιακής δομής και της αναμενόμενης σχετικής πληθυσμιακής δομής του μη ομογενούς Μαρκοβιανού Συστήματος ανώτερης τάξης. Κατόπιν διερευνούμε τη μεταβλητότητα των μεγεθών των καταστάσεων του μη ομογενούς Μαρκοβιανού Συστήματος και τη συνδέουμε με την αντίστοιχη του Μ.Ο.Μ.Σ. πρώτης τάξης και προσδιορίζουμε την ασυμπτωτική συμπεριφορά της, σύμφωνα με προϋποθέσεις που μπορεί εύκολα να συναντηθούν στην πράξη. Αποδεικνύουμε τη σχέση που ικανοποιούν οι από κοινού πιθανότητες των πραγματώσεων της μη ομογενούς Μαρκοβιανής Αλυσίδας υστέρησης και δίνουμε τις συνθήκες υπό τις οποίες εξασφαλίζεται μοναδική λύση. Εξετάζουμε τη δομή των αυτοσυσχετίσεών τους και αποδεικνύουμε ότι ικανοποιούν ένα σύστημα γραμμικών εξισώσεων, παρόμοιο με αυτό των Yule-Walker των χρονικών σειρών

Could Causal Discovery in Proteogenomics Assist in Understanding Gene&ndash;Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model

Genome-wide transcriptome analysis is a method that produces important data on plant biology at a systemic level. The lack of understanding of the relationships between proteins and genes in plants necessitates a further thorough analysis at the proteogenomic level. Recently, our group generated a quantitative proteogenomic atlas of 15 sweet cherry (Prunus avium L.) cv. &lsquo;Tragana Edessis&rsquo; tissues represented by 29,247 genes and 7584 proteins. The aim of the current study was to perform a targeted analysis at the gene/protein level to assess the structure of their relation, and the biological implications. Weighted correlation network analysis and causal modeling were employed to, respectively, cluster the gene/protein pairs, and reveal their cause&ndash;effect relations, aiming to assess the associated biological functions. To the best of our knowledge, this is the first time that causal modeling has been employed within the proteogenomics concept in plants. The analysis revealed the complex nature of causal relations among genes/proteins that are important for traits of interest in perennial fruit trees, particularly regarding the fruit softening and ripening process in sweet cherry. Causal discovery could be used to highlight persistent relations at the gene/protein level, stimulating biological interpretation and facilitating further study of the proteogenomic atlas in plants

Cigarette Smoking Promotes Infection of Cervical Cells by High-Risk Human Papillomaviruses, but not Subsequent E7 Oncoprotein Expression

Persistent cervical infection with high-risk human papillomaviruses (hrHPVs) is a necessary, but not sufficient, condition for the development of cervical cancer. Therefore, there are other co-factors facilitating the hrHPV carcinogenic process, one of which is smoking. To assess the effect of smoking on high-risk (hr) HPV DNA positivity and on the expression of HPV E7 oncoprotein, as a surrogate of persistent hrHPV infection, we used data from women recruited for the PIPAVIR project, which examined the role of E7 protein detection in cervical cancer screening. Women were tested for hrHPV DNA, using Multiplex Genotyping (MPG), and E7 protein, using a novel sandwich ELISA method, and gave information on their smoking habits. Among 1473 women, hrHPV prevalence was 19.1%. The odds ratio (OR) for hrHPV positivity of smokers compared to non-smokers was 1.785 (95% confidence intervals (CI): 1.365–2.332, p &lt; 0.001). The ORs for E7 positivity, concerning hrHPV positive women, ranged from 0.720 to 1.360 depending on the E7 detection assay used, but this was not statistically significant. Smoking increases the probability of hrHPV infection, and smoking intensity is positively associated to this increase. Smoking is not related to an increased probability of E7 protein positivity for hrHPV positive women

Studying the Cohesion Evolution of Genes Related to Chronic Lymphocytic Leukemia Using Semantic Similarity in Gene Ontology and Self-Organizing Maps

A significant body of work on biomedical text mining is aimed at uncovering meaningful associations between biological entities, including genes. This has the potential to offer new insights for research, uncovering hidden links between genes involved in critical pathways and processes. Recently, high-throughput studies have started to unravel the genetic landscape of chronic lymphocytic leukemia (CLL), the most common adult leukemia. CLL displays remarkable clinical heterogeneity, likely reflecting its underlying biological heterogeneity which, despite all progress, still remains insufficiently characterized and understood. This paper deploys an ontology-based semantic similarity combined with self-organizing maps for studying the temporal evolution of cohesion among CLL-related genes and the extracted information. Three consecutive time periods are considered and groups of genes are derived therein. Our preliminary results indicated that our proposed gene groupings are meaningful and that the temporal dimension indeed impacted the gene cohesion, leaving a lot of room for further promising investigations