Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

Ontology for Data Representation in the Production of Cotton Fiber in Brazil

An important feature in computer systems developed for the agricultural sector is to satisfy the heterogeneity of data generated in different processes. Most problems related with this heterogeneity arise from the lack of standard for different computing solutions proposed. An efficient solution for that is to create a single standard for data exchange. The study on the actual process involved in cotton production was based on a research developed by the Brazilian Agricultural Research Corporation (EMBRAPA) that reports all phases as a result of the compilation of several theoretical and practical researches related to cotton crop. The proposition of a standard starts with the identification of the most important classes of data involved in the process, and includes an ontology that is the systematization of concepts related to the production of cotton fiber and results in a set of classes, relations, functions and instances. The results are used as a reference for the development of computational tools, transforming implicit knowledge into applications that support the knowledge described. This research is based on data from the Midwest of Brazil. The choice of the cotton process as a study case comes from the fact that Brazil is one of the major players and there are several improvements required for system integration in this segment.

Detecting an abnormality in a recovery boiler using dynamic multivariate data analysis with parallel coordinate plots

Data visualization techniques are powerful in the handling and analysis of multivariate systems. One such technique known as parallel coordinates was used to support the diagnosis of an event, detected by a neural network-based monitoring system, in a boiler at a Brazilian Kraft pulp mill. Its attractiveness is the possibility of the visualization of several variables simultaneously. The diagnostic procedure was carried out step-by-step going through exploratory, explanatory, confirmatory, and communicative goals. This tool allowed the visualization of the boiler dynamics in an easier way, compared to commonly used univariate trend plots. In addition it facilitated analysis of other aspects, namely relationships among process variables, distinct modes of operation and discrepant data. The whole analysis revealed firstly that the period involving the detected event was associated with a transition between two distinct normal modes of operation, and secondly the presence of unusual changes in process variables at this time.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Exercise Performance and Dynamic Hyperinflation in Lymphangioleiomyomatosis

Rationale: Lymphangioleiomyomatosis (LAM) is characterized by exercise performance impairment. Although airflow limitation is common, no previous studies have evaluated the prevalence and impact of dynamic hyperinflation (DH) in LAM. Objectives: To investigate the dynamic responses during maximal exercise and the prevalence, predictors, and repercussions of DH in LAM. Methods: Forty-two patients with LAM performed symptom-limited incremental cycle exercise and pulmonary functions tests (PFTs) and were compared with 10 age-matched healthy women. Dyspnea intensity, inspiratory capacity, oxygen saturation, and cardiac, metabolic, and respiratory variables were assessed during exercise. Patients with LAM also performed a 6-minute walk test (6MWT). Measurements and Main Results: Patients with LAM had higher baseline dyspnea, poorer quality of life, obstructive pattern, air trapping, and reduced diffusing capacity of carbon monoxide in PFTs. Although they had the same level of regular physical activity, their maximal exercise performance was reduced and was associated with ventilatory limitation, greater desaturation, and dyspnea. The prevalence of DH was high in LAM (55%), even in patients with mild spirometric abnormalities, and was correlated with airflow obstruction, air trapping, and diffusing capacity of carbon monoxide. Compared with the non-DH subgroup, the patients who developed DH had a ventilatory limitation contributing to exercise cessation on cycling and higher desaturation and dyspnea intensity during the 6MWT. Conclusions: Ventilatory limitation and gas exchange impairment are important causes of exercise limitation in LAM. DH is frequent in LAM, even in patients with mild spirometric abnormalities. DH was associated with the severity of disease, higher dyspnea, and lower oxygen saturation. In the 6MWT, desaturation and dyspnea were greater in patients with DH.

Brazilian exchange rate complexity: Financial crisis effects

With the financial market globalization, foreign investments became vital for the economies, mainly in emerging countries. In the last decades, Brazilian exchange rates appeared as a good indicator to measure either investors' confidence or risk aversion. Here, some events of global or national financial crisis are analyzed, trying to understand how they influenced the "dollar-real" rate evolution. The theoretical tool to be used is the Lopez-Mancini-Calbet (LMC) complexity measure that, applied to real exchange rate data, has shown good fitness between critical events and measured patterns. (C) 2011 Elsevier B.V. All rights reserved.

Comparison of INAA elemental composition data between Lago Grande and Osvaldo archaeological sites in the central Amazon: a first perspective

In this work, 50 ceramic fragments from the Lago Grande and 30 from the Osvaldo archaeological site were compared to assess elemental similarities. The aim is to perform a preliminary comparison between the sites, which are located in the central Amazon, Brazil. The analytical technique employed to obtain the ceramics elemental composition was instrumental neutron activation analysis (INAA). The data set obtained was explored by the multivariate statistical techniques of cluster, principal component and discriminant analysis. The analyzed elements were: Na, Lu, U, Yb, La, Th, Cr, Cs, Sc, Fe, Eu, Ce and Hf. The results showed the existence of at least two compositional groups for Lago Grande and Osvaldo. Each compositional group of Osvaldo archaeological site matches with one group of Lago Grande. Correlated with the archaeological background, the results suggest commercial or cultural exchange in the region, which is an indicative of socio-cultural interactions between those sites.

Dynamic Activation and Repression of the Plasmodium falciparum rif Gene Family and Their Relation to Chromatin Modification

The regulation of variant gene expression in Plasmodium falciparum is still only partially understood. Regulation of var genes, the most studied gene family involved in antigenic variation, is orchestrated by a dynamic pattern of inherited chromatin states. Although recent evidence pointed to epigenetic regulation of transcribed and repressed rif loci, little is known about specific on/off associated histone modifications of individual rif genes. To investigate the chromatin marks for transcribed and repressed rif loci, we cultivated parasites and evaluated the transcriptional status of chosen rif targets by qRT-PCR and performed ChIP assays using H3K9ac and H3K9me3 antibodies. We then monitored changes in the epigenetic patterns in parasites after several reinvasions and also evaluated the "poised'' mark in trophozoites and schizonts of the same erythrocytic cycle by ChIP using H3K4me2 specific antibodies. Our results show that H3K9 is acetylated in transcribed rif loci and trimethylated or even unmodified in repressed rif loci. These transcriptional and epigenetic states are inherited after several reinvasions. The poised modification H3K4me2 showed a tendency to be more present in loci in trophozoites that upon progression to schizonts strongly transcribe the respective locus. However, this effect was not consistently observed for all monitored loci. While our data show important similarities to var transcription-associated chromatin modifications, the observed swiftly occurring modifications at rif loci and the absence of H3K9 modification point to a different dynamic of recruitment of chromatin modifying enzymes.

Use of a Single L1 GPS Receiver for Monitoring Structures: First Results of the Detection of Millimetric Dynamic Oscillations

This paper presents preliminary results to determine small displacements of a global positioning system (GPS) antenna fastened to a structure using only one L1 GPS receiver. Vibrations, periodic or not, are common in large structures, such as bridges, footbridges, tall buildings, and towers under dynamic loads. The behavior in time and frequency leads to structural analysis studies. The hypothesis of this article is that any large structure that presents vibrations in the centimeter-to-millimeter range can be monitored by phase measurements of a single L1 receiver with a high data rate, as long as the direction of the displacement is pointing to a particular satellite. Within this scenario, the carrier phase will be modulated by antenna displacement. During a period of a few dozen seconds, the relative displacement to the satellite, the satellite clock, and the atmospheric phase delays can be assumed as a polynomial time function. The residuals from a polynomial adjustment contain the phase modulation owing to small displacements, random noise, receiver clock short time instabilities, and multipath. The results showed that it is possible to detect displacements of centimeters in the phase data of a single satellite and millimeters in the difference between the phases of two satellites. After applying a periodic nonsinusoidal displacement of 10 m to the antenna, it is clearly recovered in the difference of the residuals. The time domain spectrum obtained by the fast Fourier transform (FFT) exhibited a defined peak of the third harmonic much more than the random noise using the proposed third-degree polynomial model. DOI: 10.1061/(ASCE)SU.1943-5428.0000070. (C) 2012 American Society of Civil Engineers.