A simulated annealing-based maximum-margin clustering algorithm

© 2018 Wiley Periodicals, Inc. Maximum-margin clustering is an extension of the support vector machine (SVM) to clustering. It partitions a set of unlabeled data into multiple groups by finding hyperplanes with the largest margins. Although existing algorithms have shown promising results, there is no guarantee of convergence of these algorithms to global solutions due to the nonconvexity of the optimization problem. In this paper, we propose a simulated annealing-based algorithm that is able to mitigate the issue of local minima in the maximum-margin clustering problem. The novelty of our algorithm is twofold, ie, (i) it comprises a comprehensive cluster modification scheme based on simulated annealing, and (ii) it introduces a new approach based on the combination of k-means++ and SVM at each step of the annealing process. More precisely, k-means++ is initially applied to extract subsets of the data points. Then, an unsupervised SVM is applied to improve the clustering results. Experimental results on various benchmark data sets (of up to over a million points) give evidence that the proposed algorithm is more effective at solving the clustering problem than a number of popular clustering algorithms

Single - particle correlations in events with the total disintegration of nuclei

New experimental data on the behaviour of the single-particle two-dimensional correlation functions R versus Q (Q is the number of nucleons emitted from nuc- lei) and Ap (Ap is the mass of projectile nuclei) are presented in this paper. The interactions of protons, d, 4He and 12C nuclei with carbon nuclei (at a momentum of 4.2 A GeV/c) are considered.The values of R are obtained separately for pi minus mesons and protons.In so doing,the values of R are normalized so that -1=<R=<1.The value of R=0 corresponds to the case of the absence of corre- lations.It has been found that the Q- and Ap-dependence of R takes place only for weak correlations (R< 0.3).In the main (90 %),these correlations are con- nected with the variable pt and have a nonlinear character, that is the regi- ons with different characters of the Q-dependence of R are separated: there is a change of regimes in the Q-dependences of R.The correlations weaken with increasing Ap, and the variable R gets the least values of all the considered ones in 12CC interactions.Simultaneously with weakening the correlations in the region of large Q, the character of the Q-dependence of R changes.Comment: 17 pages, submitted to Phys. Rew.

Parallelization of the discrete gradient method of non-smooth optimization and its applications

We investigate parallelization and performance of the discrete gradient method of nonsmooth optimization. This derivative free method is shown to be an effective optimization tool, able to skip many shallow local minima of nonconvex nondifferentiable objective functions. Although this is a sequential iterative method, we were able to parallelize critical steps of the algorithm, and this lead to a significant improvement in performance on multiprocessor computer clusters. We applied this method to a difficult polyatomic clusters problem in computational chemistry, and found this method to outperform other algorithms. <br /

Chromosome synapsis, recombination and epigenetic modification in rams heterozygous for metacentric chromosome 3 of the domestic sheep Ovis aries and acrocentric homologs of the argali Ovis ammon

Hybridization of domestic animal breeds with their wild relatives is a promising method for increasing the genetic diversity of farm animals. Resource populations derived from the hybridization of various breeds of domestic sheep with mouflon and argali are an important source of breeding material. The karyotypes of argali and domestic sheep differ for a Robertsonian translocation, which occurred in the common ancestor of mouflon and domestic sheep (Ovis aries) due to the centric fusion of chromosomes 5 and 11 of the argali (O. ammon) into chromosome 3 of sheep. It is known that heterozygosity for translocation can lead to synapsis, recombination and chromosome segregation abnormalities in meiosis. Meiosis in the heterozygotes for translocation that distinguishes the karyotypes of sheep and argali has not yet been studied. We examined synapsis, recombination, and epigenetic modification of chromosomes involved in this rearrangement in heterozygous rams using immunolocalization of key proteins of meiosis. In the majority of cells, we observed complete synapsis between the sheep metacentric chromosome and two argali acrocentric chromosomes with the formation of a trivalent. In a small proportion of cells at the early pachytene stage we observed delayed synapsis in pericentromeric regions of the trivalent. Unpaired sites were subjected to epigenetic modification, namely histone H2A.X phosphorylation. However, by the end of the pachytene, these abnormalities had been completely eliminated. Asynapsis was replaced by a nonhomologous synapsis between the centromeric regions of the acrocentric chromosomes. By the end of the pachytene, the γH2A.X signal had been preserved only at the XY bivalent and was absent from the trivalent. The translocation trivalent did not differ from the normal bivalents of metacentric chromosomes for the number and distribution of recombination sites as well as for the degree of centromeric and crossover interference. Thus, we found that heterozygosity for the domestic sheep chromosome 3 and argali chromosomes 5 and 11 does not cause significant alterations in key processes of prophase I meiosis and, therefore, should not lead to a decrease in fertility of the offspring from interspecific sheep hybridization

Genomic assessment and phenotypic characteristics of F2 resource sheep population

The article presents the results of assessment of genetic diversity and Principal Component Analysis (PCA) in the re-source sheep population, originated from crossing of fast-growing (Katahdin) and slow growing (Romanov) breeds for QTL mapping and search for candidate genes associated with growth rate. The study was conducted on 88 sheep from the resource population, including two unrelated families that have been reared in the Moscow region since 2017. Each family consists of a Katahdin ram (founder), Romanov’s ewes (mothers), F1 hybrids, and two groups of backcrosses. All sheep were genotyped using a high-density DNA chip Illumina Ovine Infinium® HD SNP BeadChip (~ 600 thousand SNP markers). SNP markers were filtered in the PLINK v.1.90. PCA was performed in PLINK v.1.90 and visualized in R package ggplot2. The genetic diversity indices (Ho, uHe, Ar, FIS) were calculated in R package “diveRsity”. It was established that both crosses had higher level of genetic diversity in comparison with the mother breed. F1 hybrids were characterized by the highest level of observed heterozygosity (Ho = 0.409-0.407), while Ho ranged from 0.382 to 0.396 for the backcrosses, respectively. The expected heterozygosity ranged from 0.329 to 0.356 in the groups from the resource population. Allelic richness was high in all studied groups (more than 1.849). PCA showed that the mated parent breeds were highly differentiated, as it should be in successful establishment of the resource population. The phenotypic characteristic of the backcrosses on live weight and nine body measurements at 9, 42 and 90 days is given. The coefficients of variation were the highest by live weight (17.0-19.0%), body length (15.5-22.3%) and oblique body length (16.2% and 22.7%) at 90 days. The results are intermediate and create a geno-typic and phenotypic base to perform GWAS at the next stage of our study

The GWAS-MAP|ovis platform for aggregation and analysis of genome-wide association study results in sheep

In recent years, the number of genome-wide association studies (GWAS) carried out for various economically important animal traits has been increasing. GWAS discoveries provide summary statistics that can be used both for targeted marker-oriented selection and for studying the genetic control of economically important traits of farm animals. In contrast to research in human genetics, GWAS on farm animals often does not meet generally accepted standards (availability of information about effect and reference alleles, the size and direction of the effect, etc.). This greatly complicates the use of GWAS results for breeding needs. Within the framework of human genetics, there are several technological solutions for researching the harmonized results of GWAS, including one of the largest, the GWAS-MAP platform. For other types of living organisms, including economically important agricultural animals, there are no similar solutions. To our knowledge, no similar solution has been proposed to date for any of the species of economically important animals. As part of this work, we focused on creating a platform similar to GWAS-MAP for working with the results of GWAS of sheep, since sheep breeding is one of the most important branches of agriculture. By analogy with the GWAS-MAP platform for storing, unifying and analyzing human GWAS, we have created the GWAS-MAP|ovis platform. The platform currently contains information on more than 34 million associations between genomic sequence variants and traits of meat production in sheep. The platform can also be used to conduct colocalization analysis, a method that allows one to determine whether the association of a particular locus with two different traits is the result of pleiotropy or whether these traits are associated with different variants that are in linkage disequilibrium. This platform will be useful for breeders to select promising markers for breeding, as well as to obtain information for the introduction of genomic breeding and for scientists to replicate the results obtained

The GWAS-MAP|ovis platform for aggregation and analysis of genome-wide association study results in sheep.

peer reviewedIn recent years, the number of genome-wide association studies (GWAS) carried out for various economically important animal traits has been increasing. GWAS discoveries provide summary statistics that can be used both for targeted marker-oriented selection and for studying the genetic control of economically important traits of farm animals. In contrast to research in human genetics, GWAS on farm animals often does not meet generally accepted standards (availability of information about effect and reference alleles, the size and direction of the effect, etc.). This greatly complicates the use of GWAS results for breeding needs. Within the framework of human genetics, there are several technological solutions for researching the harmonized results of GWAS, including one of the largest, the GWAS-MAP platform. For other types of living organisms, including economically important agricultural animals, there are no similar solutions. To our knowledge, no similar solution has been proposed to date for any of the species of economically important animals. As part of this work, we focused on creating a platform similar to GWAS-MAP for working with the results of GWAS of sheep, since sheep breeding is one of the most important branches of agriculture. By analogy with the GWAS-MAP platform for storing, unifying and analyzing human GWAS, we have created the GWAS-MAP|ovis platform. The platform currently contains information on more than 34 million associations between genomic sequence variants and traits of meat production in sheep. The platform can also be used to conduct colocalization analysis, a method that allows one to determine whether the association of a particular locus with two different traits is the result of pleiotropy or whether these traits are associated with different variants that are in linkage disequilibrium. This platform will be useful for breeders to select promising markers for breeding, as well as to obtain information for the introduction of genomic breeding and for scientists to replicate the results obtained.В последние годы увеличивается количество полногеномных исследований ассоциаций (ПГИА, GWAS), проведенных для различных экономически важных признаков животных. Результаты этих исследований представлены в виде суммарных статистик, которые можно использовать для изучения генетического контроля экономически важных признаков сельскохозяйственных животных, в том числе и при разработке методик маркер-ориентированной селекции. В большинстве случаев ПГИА сельскохозяйственных животных не соответствуют общепринятым в области исследований генетики человека стандартам формата публикаций результатов ПГИА в виде суммарных статистик (наличие информации об эффекторном и референсном аллелях, значение и направление эффекта и др.). Это существенно затрудняет использование суммарных статистик для нужд селекции. В области исследований генетики человека имеется несколько технологических решений для анализа результатов ПГИА, в том числе одно из самых крупных – платформа GWAS-MAP. Для других видов живых организмов, включающих и экономически важных сельскохозяйственных животных, подобных решений нет. В настоящей работе мы сфокусировались на создании схожей платформы для работы с суммарными статистиками ПГИА различных признаков овец, так как овцеводство в последнее время становится все более актуальной областью сельского хозяйства. По аналогии с платформой GWAS-MAP для хранения, унификации и анализа GWAS человека мы создали платформу GWAS-MAP|ovis. На сегодняшний день платформа содержит информацию о более чем 34 млн ассоциаций между вариантами геномной последовательности и признаками мясной продуктивности. Платформа может быть использована и для проведения анализа колокализации – метода, который позволяет установить, является ли ассоциация определенного локуса с двумя разными признаками результатом плейотропии или же данные признаки ассоциированы с разными вариантами, которые находятся в неравновесии по сцеплению. Эта платформа будет полезна как селекционерам для выбора перспективных маркеров для селекции (эффекты и аллели различных маркеров, влияющих на изучаемые признаки), так и для ученых, ведущих исследования в области генетики овец

ПНЕВМОНЭКТОМИЯ У ПАЦИЕНТА С ОСЛОЖНЕННЫМ ТЕЧЕНИЕМ ГРАНУЛЕМАТОЗА ВЕГЕНЕРА

The article describes a clinical case of 42-year old male patient with necrotising granulomatosis with polyangitis (Wegener's granulomatosis) complicated by pulmonary aspergillosis, and due to the latter a life-saving pneumonectomy had to be done  Microbiological tests of surgery specimens detected the cell crowding of mold fungi of Aspergillus fumigatus The histological tests showed necrotising granulomatosis with polyangitis, formation of cavities with fibrotic walls and fungal population; fibrinous-hemorrhagic pleurisy. In one month after surgery the patient was transferred to the rheumatological ward, where biological anti-B-cellular therapy with rituximab was started with a consequent positive outcome.Представлено клиническое наблюдение пациента 42 лет с некротизирующим гранулематозом с полиангиитом (гранулематоз Вегенера), осложненным аспергиллезом легкого, которому по жизненным показаниям пришлось выполнить пневмонэктомию При микробиологическом исследовании операционного материала получен сливной рост плесневых грибов рода Aspergillus fumigatus При гистологическом исследовании ‒ картина некротизирующего гранулематоза с полиангиитом, формирование полостей деструкции с фиброзными стенками и наличием грибковой флоры; фибринозно-геморрагический плеврит. Через месяц после проведенного оперативного вмешательства пациент переведен в ревматологическое отделение, где была начата биологическая анти-В-клеточная терапия ритуксимабом с хорошим эффектом

A new scoring system in Cystic Fibrosis: statistical tools for database analysis – a preliminary report

<p>Abstract</p> <p>Background</p> <p>Cystic fibrosis is the most common fatal genetic disorder in the Caucasian population. Scoring systems for assessment of Cystic fibrosis disease severity have been used for almost 50 years, without being adapted to the milder phenotype of the disease in the 21^stcentury. The aim of this current project is to develop a new scoring system using a database and employing various statistical tools. This study protocol reports the development of the statistical tools in order to create such a scoring system.</p> <p>Methods</p> <p>The evaluation is based on the Cystic Fibrosis database from the cohort at the Royal Children's Hospital in Melbourne. Initially, unsupervised clustering of the all data records was performed using a range of clustering algorithms. In particular incremental clustering algorithms were used. The clusters obtained were characterised using rules from decision trees and the results examined by clinicians. In order to obtain a clearer definition of classes expert opinion of each individual's clinical severity was sought. After data preparation including expert-opinion of an individual's clinical severity on a 3 point-scale (mild, moderate and severe disease), two multivariate techniques were used throughout the analysis to establish a method that would have a better success in feature selection and model derivation: 'Canonical Analysis of Principal Coordinates' and 'Linear Discriminant Analysis'. A 3-step procedure was performed with (1) selection of features, (2) extracting 5 severity classes out of a 3 severity class as defined per expert-opinion and (3) establishment of calibration datasets.</p> <p>Results</p> <p>(1) Feature selection: CAP has a more effective "modelling" focus than DA.</p> <p>(2) Extraction of 5 severity classes: after variables were identified as important in discriminating contiguous CF severity groups on the 3-point scale as mild/moderate and moderate/severe, Discriminant Function (DF) was used to determine the new groups mild, intermediate moderate, moderate, intermediate severe and severe disease. (3) Generated confusion tables showed a misclassification rate of 19.1% for males and 16.5% for females, with a majority of misallocations into adjacent severity classes particularly for males.</p> <p>Conclusion</p> <p>Our preliminary data show that using CAP for detection of selection features and Linear DA to derive the actual model in a CF database might be helpful in developing a scoring system. However, there are several limitations, particularly more data entry points are needed to finalize a score and the statistical tools have further to be refined and validated, with re-running the statistical methods in the larger dataset.</p