970 resultados para Computational methods
Resumo:
Dissertação de mestrado integrado em Engenharia Civil
Resumo:
Tese de Doutoramento em Engenharia Civil.
Resumo:
"Series title: Springerbriefs in applied sciences and technology, ISSN 2191-530X"
Resumo:
"Series title: Springerbriefs in applied sciences and technology, ISSN 2191-530X"
Resumo:
Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.
Resumo:
"Series: Solid mechanics and its applications, vol. 226"
Resumo:
Fluorescence in situ hybridization (FISH) is based on the use of fluorescent staining dyes, however, the signal intensity of the images obtained by microscopy is seldom quantified with accuracy by the researcher. The development of innovative digital image processing programs and tools has been trying to overcome this problem, however, the determination of fluorescent intensity in microscopy images still has issues due to the lack of precision in the results and the complexity of existing software. This work presents FISHji, a set of new ImageJ methods for automated quantification of fluorescence in images obtained by epifluorescence microscopy. To validate the methods, results obtained by FISHji were compared with results obtained by flow cytometry. The mean correlation between FISHji and flow cytometry was high and significant, showing that the imaging methods are able to accurately assess the signal intensity of fluorescence images. FISHji are available for non-commercial use at http://paginas.fe.up.pt/nazevedo/.
Resumo:
Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.
Resumo:
OBJECTIVE - The aim of our study was to assess the profile of a wrist monitor, the Omron Model HEM-608, compared with the indirect method for blood pressure measurement. METHODS - Our study population consisted of 100 subjects, 29 being normotensive and 71 being hypertensive. Participants had their blood pressure checked 8 times with alternate techniques, 4 by the indirect method and 4 with the Omron wrist monitor. The validation criteria used to test this device were based on the internationally recognized protocols. RESULTS - Our data showed that the Omron HEM-608 reached a classification B for systolic and A for diastolic blood pressure, according to the one protocol. The mean differences between blood pressure values obtained with each of the methods were -2.3 +7.9mmHg for systolic and 0.97+5.5mmHg for diastolic blood pressure. Therefore, we considered this type of device approved according to the criteria selected. CONCLUSION - Our study leads us to conclude that this wrist monitor is not only easy to use, but also produces results very similar to those obtained by the standard indirect method.