BiMine+: An efficient algorithm for discovering relevant biclusters of DNA microarray data

Biclustering is a very useful tool for analyzing microarray data. It aims to identify maximal groups of genes which are coherent with maximal groups of conditions. In this paper, we propose a biclustering algorithm, called BiMine+, which is able to detect significant biclusters from gene expression data. The proposed algorithm is based on two original features. First, BiMine+ is based on the use of a new tree structure, called Modified Bicluster Enumeration Tree (MBET), on which biclusters are represented by the profile shapes of genes. Second, BiMine+ uses a pruning rule to avoid both trivial biclusters and combinatorial explosion of the search tree. The performance of BiMine+ is assessed on both synthetic and real DNA microarray datasets. Experimental results show that BiMine+ competes favorably with several state-of-the-art biclustering algorithms and is able to extract functionally enriched and biologically relevant biclusters

Pattern-driven neighborhood search for biclustering of microarray data

Biclustering aims at finding subgroups of genes that show highly correlated behaviors across a subgroup of conditions. Biclustering is a very useful tool for mining microarray data and has various practical applications. From a computational point of view, biclustering is a highly combinatorial search problem and can be solved with optimization methods

BicFinder: a biclustering algorithm for microarray data analysis

In the context of microarray data analysis, biclustering allows the simultaneous identification of a maximum group of genes that show highly correlated expression patterns through a maximum group of experimental conditions (samples). This paper introduces a heuristic algorithm called BicFinder (The BicFinder software is available at: http://www.info.univ-angers.fr/pub/hao/BicFinder.html) for extracting biclusters from microarray data. BicFinder relies on a new evaluation function called Average Correspondence Similarity Index (ACSI) to assess the coherence of a given bicluster and utilizes a directed acyclic graph to construct its biclusters. The performance of BicFinder is evaluated on synthetic and three DNA microarray datasets. We test the biological significance using a gene annotation web-tool to show that our proposed algorithm is able to produce biologically relevant biclusters. Experimental results show that BicFinder is able to identify coherent and overlapping biclusters

A memetic algorithm for discovering negative correlation biclusters of DNA microarray data

Most biclustering algorithms for microarrays data analysis focus on positive correlations of genes. However, recent studies demonstrate that groups of biologically significant genes can show negative correlations as well. So, discovering negatively correlated patterns from microarrays data represents a real need. In this paper, we propose a Memetic Biclustering Algorithm (MBA) which is able to detect negatively correlated biclusters. The performance of the method is evaluated based on two well-known microarray datasets (Yeast cell cycle and Saccharomyces cerevisiae), showing that MBA is able to obtain statistically and biologically significant biclusters

Leiomyosarcome du Rein: A Propos D’un Cas

Le léiomyosarcome du rein est une tumeur rare. Les auteurs ont rapporté l’observation d’un homme âgé de 45 ans, chez lequel le diagnostic d’une tumeur rétropéritoénale gauche a été posé lors de l’exploration de douleurs du flanc gauche associées à une altération de l’état général et ce par l’imagerie (Echographie et scanner abdominal). La laparotomie exploratrice avait conclu à une tumeur rénale gauche localement évoluée, une néphrectomie élargie a été réalisée et l’histologie était en faveur d’un léiomyosarcome rénal. Une récidive locale a été diagnostiquée après un recul de 6 mois. Après une nouvelle laparotomie, l’abstention était de mise devant le caractère évolué de la récidive. Le but de cette observation est double. Le premier, est la nécessité de faire un diagnostic précoce, afin d’intervenir sur une tumeur de petite taille, plus accessible à la chirurgie. Le second, est de discuter la place du traitement adjuvant, qui pourrait réduire le risque de récidive précoce.Mots clés : Léiomyosarcome, rei

Appendagite épiploïque primitive: à propos de cinq cas

La torsion de frange épiploïque (ou appendagite) est une pathologie rare qui survient principalement chez les adultes entre 20 et 50 ans.L'incidence de cette pathologie n'est pas réellement connue et elle varie de 2 à 7% chez les patients hospitalisés pour suspicion d'appendicite oude sigmoïdite. Nous rapportons cinq cas d'appendagites dont nous précisons les particularités cliniques, radiologiques et thérapeutiques. Il s'agit de 5 patients dont l'âge moyen est de 34.6 ans (24-55). Le sexe ratio est de 1.5. Le principal motif de consultation était un syndrome douloureux de l'abdomen principalement au niveau de la fosse iliaque droite. L'examen abdominal montrait toujours une sensibilité localisée. La fièvre était présente chez 3 patients. Le bilan biologique révèle un syndrome inflammatoire biologique chez trois patients. Les examens complémentaires radiologiques en particulier échographie abdominale et TDM abdominale ont éliminé formellement une urgence chirurgicale et ont évoqué le diagnostic d'appendagite dans trois cas. Trois patients ont bénéficié d'une coelioscopie diagnostique confirmant le diagnostic  d'appendagite. L'évolution était favorable chez tous les patients. Les appendagites épiploïques primitives sont des étiologies rares et  sous-estimées de syndrome abdominal aigu. Le diagnostic peut être affirmé par imagerie notamment avec le scanner hélicoïdal injecté,  permettant d'instaurer ainsi un traitement médical premier et d'éviter un traitement chirurgical et des hospitalisations excessives

Effect of Ebola virus disease on maternal and child health services in Guinea: a retrospective observational cohort study

Background The 2014 west African epidemic of Ebola virus disease posed a major threat to the health systems of the countries affected. We sought to quantify the consequences of Ebola virus disease on maternal and child health services in the highly-affected Forest region of Guinea. Methods We did a retrospective, observational cohort study of women and children attending public health facilities for antenatal care, institutional delivery, and immunisation services in six of seven health districts in the Forest region (Beyla, Guéckédou, Kissidougou, Lola, Macenta, and N’Zérékoré). We examined monthly service use data for eight maternal and child health services indicators: antenatal care (≥1 antenatal care visit and ≥3 antenatal care visits), institutional delivery, and receipt of five infant vaccines: polio, pentavalent (diphtheria, tetanus, pertussis, hepatitis B virus, and Haemophilus influenzae type b), yellow fever, measles, and tuberculosis. We used interrupted time series models to estimate trends in each indicator across three time periods: pre-Ebola virus disease epidemic (January, 2013, to February, 2014), during-epidemic (March, 2014, to February, 2015) and postepidemic (March, 2015, to Feb, 2016). We used segmented ordinary least-squares (OLS) regression using Newey- West standard errors to accommodate for serial autocorrelation, and adjusted for any potential effect of birth seasonality on our outcomes. Findings In the months before the Ebola virus disease outbreak, all three maternal indicators showed a significantly positive change in trend, ranging from a monthly average increase of 61 (95% CI 38–84) institutional deliveries to 119 (95% CI 79–158) women achieving at least three antenatal care visits. These increasing trends were reversed during the epidemic: fewer institutional deliveries occurred (–240, 95% CI –293 to –187), and fewer women achieved at least one antenatal care visit (–418, 95% CI –535 to –300) or at least three antenatal care visits (–363, 95% CI –485 to –242) per month (p<0·0001 for all). Compared with the negative trend during the outbreak, the change in trend during the post-outbreak period showed that 173 more women per month (95% CI 51–294; p=0·0074) had at least one antenatal care visit, 257 more (95% CI 117–398; p=0·0010) had at least three antenatal care visits and 149 more (95% CI 91–206; p<0·0001) had institutional deliveries. However, although the numbers for these indicators increased in the post-epidemic period, the trends for all stagnated. Similarly, the increasing trend in child vaccination completion during the pre-epidemic period was followed by significant immediate and trend reductions across most vaccine types. Before the outbreak, the number of children younger than 12 months who had completed each vaccination ranged from 5752 (95% CI 2821–8682) for tuberculosis to 8043 (95% CI 7621–8464) for yellow fever. Immediately after the outbreak, significant reductions occurred in the level of all vaccinations except for yellow fever for which the reduction was marginal. The greatest reductions were noted for polio and tuberculosis at –3594 (95% CI –4811 to –2377; p<0·0001) and –3048 (95% CI –5879 to –216; p=0·0362) fewer vaccines administered, respectively. Compared with pre-Ebola virus disease outbreak trends, significant decreases occurred for all vaccines except polio, with the trend of monthly decreases in the number of children vaccinated ranging from –419 (95% CI –683 to –155; p=0·0034) fewer for BCG to –313 (95% CI–446 to –179; p<0·0001) fewer for pentavalent during the outbreak. In the post-Ebola virus disease outbreak period, vaccination coverage for polio, measles, and yellow fever continued to decrease, whereas the trend in coverage for tuberculosis and pentavalent did not significantly differ from zero. Interpretation Most maternal and child health indicators significantly declined during the Ebola virus disease outbreak in 2014. Despite a reduction in this negative trend in the post-outbreak period, the use of essential maternal and child health services have not recovered to their pre-outbreak levels, nor are they all on a course that suggests that they will recover without targeted interventions

Speaker-independent emotion recognition exploiting a psychologically-inspired binary cascade classification schema

In this paper, a psychologically-inspired binary cascade classification schema is proposed for speech emotion recognition. Performance is enhanced because commonly confused pairs of emotions are distinguishable from one another. Extracted features are related to statistics of pitch, formants, and energy contours, as well as spectrum, cepstrum, perceptual and temporal features, autocorrelation, MPEG-7 descriptors, Fujisakis model parameters, voice quality, jitter, and shimmer. Selected features are fed as input to K nearest neighborhood classifier and to support vector machines. Two kernels are tested for the latter: Linear and Gaussian radial basis function. The recently proposed speaker-independent experimental protocol is tested on the Berlin emotional speech database for each gender separately. The best emotion recognition accuracy, achieved by support vector machines with linear kernel, equals 87.7%, outperforming state-of-the-art approaches. Statistical analysis is first carried out with respect to the classifiers error rates and then to evaluate the information expressed by the classifiers confusion matrices. © Springer Science+Business Media, LLC 2011