926 resultados para Genomic data integration
Resumo:
This research paper presents the work on feature recognition, tool path data generation and integration with STEP-NC (AP-238 format) for features having Free form / Irregular Contoured Surface(s) (FICS). Initially, the FICS features are modelled / imported in UG CAD package and a closeness index is generated. This is done by comparing the FICS features with basic B-Splines / Bezier curves / surfaces. Then blending functions are caculated by adopting convolution theorem. Based on the blending functions, contour offsett tool paths are generated and simulated for 5 axis milling environment. Finally, the tool path (CL) data is integrated with STEP-NC (AP-238) format. The tool path algorithm and STEP- NC data is tested with various industrial parts through an automated UFUNC plugin.
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Multiple myeloma is characterized by genomic alterations frequently involving gains and losses of chromosomes. Single nucleotide polymorphism (SNP)-based mapping arrays allow the identification of copy number changes at the sub-megabase level and the identification of loss of heterozygosity (LOH) due to monosomy and uniparental disomy (UPD). We have found that SNP-based mapping array data and fluorescence in situ hybridization (FISH) copy number data correlated well, making the technique robust as a tool to investigate myeloma genomics. The most frequently identified alterations are located at 1p, 1q, 6q, 8p, 13, and 16q. LOH is found in these large regions and also in smaller regions throughout the genome with a median size of 1 Mb. We have identified that UPD is prevalent in myeloma and occurs through a number of mechanisms including mitotic nondisjunction and mitotic recombination. For the first time in myeloma, integration of mapping and expression data has allowed us to reduce the complexity of standard gene expression data and identify candidate genes important in both the transition from normal to monoclonal gammopathy of unknown significance (MGUS) to myeloma and in different subgroups within myeloma. We have documented these genes, providing a focus for further studies to identify and characterize those that are key in the pathogenesis of myeloma.
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The automated transfer of flight logbook information from aircrafts into aircraft maintenance systems leads to reduced ground and maintenance time and is thus desirable from an economical point of view. Until recently, flight logbooks have not been managed electronically in aircrafts or at least the data transfer from aircraft to ground maintenance system has been executed manually. Latest aircraft types such as the Airbus A380 or the Boeing 787 do support an electronic logbook and thus make an automated transfer possible. A generic flight logbook transfer system must deal with different data formats on the input side – due to different aircraft makes and models – as well as different, distributed aircraft maintenance systems for different airlines as aircraft operators. This article contributes the concept and top level distributed system architecture of such a generic system for automated flight log data transfer. It has been developed within a joint industry and applied research project. The architecture has already been successfully evaluated in a prototypical implementation.
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High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.
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Mother and infant mortality has been the scope of analysis throughout the history of public health in Brazil and various strategies to tackle the issue have been proposed to date. The Ministry of Health has been working on this and the Rede Cegonha strategy is the most recent policy in this context. Given the principle of comprehensive health care and the structure of the Unified Health System in care networks, it is necessary to ensure the integration of health care practices, among which are the sanitary surveillance actions (SSA). Considering that the integration of health care practices and SSA can contribute to reduce mother and infant mortality rates, this article is a result of qualitative research that analyzed the integration of these actions in four cities in the State of São Paulo/Brazil: Campinas, Indaiatuba, Jaguariúna and Santa Bárbara D'Oeste. The research was conducted through interviews with SSA and maternal health managers, and the data were evaluated using thematic analysis. The results converge with other studies, identifying the isolation of health care practices and SSA. The insertion of SSA in collectively-managed areas appears to be a potential strategy for health planning and implementation of actions in the context under scrutiny.
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Metastasizing pleomorphic adenoma (MPA) is a rare tumour, and its mechanism of metastasis still is unknown. To date, there has been no study on MPA genomics. We analysed primary and secondary MPAs with array comparative genomic hybridization to identify somatic copy number alterations and affected genes. Tumour DNA samples from primary (parotid salivary gland) and secondary (scalp skin) MPAs were subjected to array comparative genomic hybridization investigation, and the data were analysed with NEXUS COPY NUMBER DISCOVERY. The primary MPA showed copy number losses affecting 3p22.2p14.3 and 19p13.3p123, and a complex pattern of four different deletions at chromosome 6. The 3p deletion encompassed several genes: CTNNB1, SETD2, BAP1, and PBRM1, among others. The secondary MPA showed a genomic profile similar to that of the primary MPA, with acquisition of additional copy number changes affecting 9p24.3p13.1 (loss), 19q11q13.43 (gain), and 22q11.1q13.33 (gain). Our findings indicated a clonal origin of the secondary MPA, as both tumours shared a common profile of genomic copy number alterations. Furthermore, we were able to detect in the primary tumour a specific pattern of copy number alterations that could explain the metastasizing characteristic, whereas the secondary MPA showed a more unbalanced genome.
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In the present study, we investigated the relationship between polymorphisms in the estrogen-metabolizing genes CYP17, CYP1B1, CYP1A1, and COMT and genomic instability in the peripheral blood lymphocytes of 62 BC patients and 62 controls considering that increased or prolonged exposure to estrogen can damage the DNA molecule and increase the genomic instability process in breast tissue. Our data demonstrated increased genomic instability in BC patients and that individuals with higher frequencies of MN exhibited higher risk to BC when belonging Val/Met genotype of the COMT gene. We also observed that CYP17 and CYP1A1 polymorphisms can modify the risk to BC depending on the menopause status. We can conclude that the genetic background in estrogen metabolism pathway can modulate chromosome damage in healthy controls and patients and thereby influence the risk to BC. These findings suggest the importance to ally biomarkers of susceptibility and effects to estimate risk groups.
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Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.
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Oxidation processes can be used to treat industrial wastewater containing non-biodegradable organic compounds. However, the presence of dissolved salts may inhibit or retard the treatment process. In this study, wastewater desalination by electrodialysis (ED) associated with an advanced oxidation process (photo-Fenton) was applied to an aqueous NaCl solution containing phenol. The influence of process variables on the demineralization factor was investigated for ED in pilot scale and a correlation was obtained between the phenol, salt and water fluxes with the driving force. The oxidation process was investigated in a laboratory batch reactor and a model based on artificial neural networks was developed by fitting the experimental data describing the reaction rate as a function of the input variables. With the experimental parameters of both processes, a dynamic model was developed for ED and a continuous model, using a plug flow reactor approach, for the oxidation process. Finally, the hybrid model simulation could validate different scenarios of the integrated system and can be used for process optimization.
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The majority of common diseases such as cancer, allergy, diabetes, or heart disease are characterized by complex genetic traits, in which genetic and environmental components contribute to disease susceptibility. Our knowledge of the genetic factors underlying most of such diseases is limited. A major goal in the post-genomic era is to identify and characterize disease susceptibility genes and to use this knowledge for disease treatment and prevention. More than 500 genes are conserved across the invertebrate and vertebrate genomes. Because of gene conservation, various organisms including yeast, fruitfly, zebrafish, rat, and mouse have been used as genetic models.
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Hepatocellular carcinoma (HCC) is associated with multiple risk factors and is believed to arise from pre-neoplastic lesions, usually in the background of cirrhosis. However, the genetic and epigenetic events of hepatocarcinogenesis are relatively poorly understood. HCC display gross genomic alterations, including chromosomal instability (CIN), CpG island methylation, DNA rearrangements associated with hepatitis B virus (HBV) DNA integration, DNA hypomethylation and, to a lesser degree, microsatellite instability. Various studies have reported CIN at chromosomal regions, 1p, 4q, 5q, 6q, 8p, 10q, 11p, 16p, 16q, 17p and 22q. Frequent promoter hypermethylation and subsequent loss of protein expression has also been demonstrated in HCC at tumor suppressor gene (TSG), p16, p14, p15, SOCS1, RIZ1, E-cadherin and 14-3-3 sigma. An interesting observation emerging from these studies is the presence of a methylator phenotype in hepatocarcinogenesis, although it does not seem advantageous to have high levels of microsatellite instability. Methylation also appears to be an early event, suggesting that this may precede cirrhosis. However, these genes have been studied in isolation and global studies of methylator phenotype are required to assess the significance of epigenetic silencing in hepatocarcinogenesis. Based on previous data there are obvious fundamental differences in the mechanisms of hepatic carcinogenesis, with at least two distinct mechanisms of malignant transformation in the liver, related to CIN and CpG island methylation. The reason for these differences and the relative importance of these mechanisms are not clear but likely relate to the etiopathogenesis of HCC. Defining these broad mechanisms is a necessary prelude to determine the timing of events in malignant transformation of the liver and to investigate the role of known risk factors for HCC.
Resumo:
Dherte PM, Negrao MPG, Mori Neto S, Holzhacker R, Shimada V, Taberner P, Carmona MJC - Smart Alerts: Development of a Software to Optimize Data Monitoring. Background and objectives: Monitoring is useful for vital follow-ups and prevention, diagnosis, and treatment of several events in anesthesia. Although alarms can be useful in monitoring they can cause dangerous user`s desensitization. The objective of this study was to describe the development of specific software to integrate intraoperative monitoring parameters generating ""smart alerts"" that can help decision making, besides indicating possible diagnosis and treatment. Methods: A system that allowed flexibility in the definition of alerts, combining individual alarms of the parameters monitored to generate a more elaborated alert system was designed. After investigating a set of smart alerts, considered relevant in the surgical environment, a prototype was designed and evaluated, and additional suggestions were implemented in the final product. To verify the occurrence of smart alerts, the system underwent testing with data previously obtained during intraoperative monitoring of 64 patients. The system allows continuous analysis of monitored parameters, verifying the occurrence of smart alerts defined in the user interface. Results: With this system a potential 92% reduction in alarms was observed. We observed that in most situations that did not generate alerts individual alarms did not represent risk to the patient. Conclusions: Implementation of software can allow integration of the data monitored and generate information, such as possible diagnosis or interventions. An expressive potential reduction in the amount of alarms during surgery was observed. Information displayed by the system can be oftentimes more useful than analysis of isolated parameters.
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293T and Sk-Hep-1 cells were transduced with a replication-defective self-inactivating HIV-1 derived vector carrying FVIII cDNA. The genomic DNA was sequenced to reveal LTR/human genome junctions and integration sites. One hundred and thirty-two sequences matched human sequences, with an identity of at least 98%. The integration sites in 293T-FVIIIDB and in Sk-Hep-FVIIIDB cells were preferentially located in gene regions. The integrations in both cell lines were distant from the CpG islands and from the transcription start sites. A comparison between the two cell lines showed that the lentiviral-transduced DNA had the same preferred regions in the two different cell lines.
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Outcome after traumatic brain injury (TBI) is characterized by a high degree of variability which has often been difficult to capture in traditional outcome studies. The purpose of this study was to describe patterns of community integration 2-5 years after TBI. Participants were 208 patients admitted to a Brain Injury Rehabilitation Unit between 1991-1995 in Brisbane, Australia. The design comprised retrospective data collection and questionnaire follow-up by mail. Mean follow-up was 3.5 years. Demographic, injury severity and functional status variables were retrieved from hospital records. Community integration was assessed using the Community Integration Questionnaire (CIQ), and vocational status measured by a self administered questionnaire. Data was analysed using cluster analysis which divided the data into meaningful subsets. Based on the CIQ subscale scores of home, social and productive integration, a three cluster solution was selected, with groups labelled as working (n = 78), balanced (n = 46) and poorly integrated (n = 84). Although 38% of the sample returned to a high level of productive activity and 22% achieved a balanced lifestyle, overall community integration was poor for the remainder. This poorly integrated group had more severe injury characterized by longer periods of acute care and post-traumatic amnesia (PTA) and greater functional disability on discharge. These findings have implications for service delivery prior to and during the process of reintegration after brain injury.
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This paper presents a method of formally specifying, refining and verifying concurrent systems which uses the object-oriented state-based specification language Object-Z together with the process algebra CSP. Object-Z provides a convenient way of modelling complex data structures needed to define the component processes of such systems, and CSP enables the concise specification of process interactions. The basis of the integration is a semantics of Object-Z classes identical to that of CSP processes. This allows classes specified in Object-Z to he used directly within the CSP part of the specification. In addition to specification, we also discuss refinement and verification in this model. The common semantic basis enables a unified method of refinement to be used, based upon CSP refinement. To enable state-based techniques to be used fur the Object-Z components of a specification we develop state-based refinement relations which are sound and complete with respect to CSP refinement. In addition, a verification method for static and dynamic properties is presented. The method allows us to verify properties of the CSP system specification in terms of its component Object-Z classes by using the laws of the the CSP operators together with the logic for Object-Z.