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Biomedical subjects

Jonas Almeida

Publications and source records attributed to Jonas Almeida.

6 recordsLinked to original sources

Modeling pneumococcal resistance to penicillin in southern Sweden using artificial neural networks.

In recent decades, penicillin-resistant pneumococci (PRP) have emerged and spread rapidly between and within countries over the world. In this study we developed an iterative artificial neural network (ANN) model to describe and predict the spread of PRP in space and time as a function of antibiotic consumption and a number of different confounders. Retrospective data from 1997 to 2000 on an international epidemic PRP clone (serotype 9V) and antibiotic consumption data from Southern Sweden were used to train the ANN models and data from 2001 to 2003 for evaluation of the model predictions. Five different ANN models were trained, each with independent topology optimization for alternative sets of input variables to find the most descriptive model. The model containing all variables was the only one performing better than the reference linear models, as assessed by the correlation between predictions and observations. The inability to identify a smaller subset of most predictive parameters may reflect either diffuse causal mechanisms or just the absence of critical experimental indicators from the dataset. The iterative ANN model identified is useful to predict future data. The sensitivity analysis of the model suggests that past incidence has a small effect on the number of PRP cases.

Humans↗

Priming nonlinear searches for pathway identification.

BACKGROUND: Dense time series of metabolite concentrations or of the expression patterns of proteins may be available in the near future as a result of the rapid development of novel, high-throughput experimental techniques. Such time series implicitly contain valuable information about the connectivity and regulatory structure of the underlying metabolic or proteomic networks. The extraction of this information is a challenging task because it usually requires nonlinear estimation methods that involve iterative search algorithms. Priming these algorithms with high-quality initial guesses can greatly accelerate the search process. In this article, we propose to obtain such guesses by preprocessing the temporal profile data and fitting them preliminarily by multivariate linear regression. RESULTS: The results of a small-scale analysis indicate that the regression coefficients reflect the connectivity of the network quite well. Using the mathematical modeling framework of Biochemical Systems Theory (BST), we also show that the regression coefficients may be translated into constraints on the parameter values of the nonlinear BST model, thereby reducing the parameter search space considerably. CONCLUSION: The proposed method provides a good approach for obtaining a preliminary network structure from dense time series. This will be more valuable as the systems become larger, because preprocessing and effective priming can significantly limit the search space of parameters defining the network connectivity, thereby facilitating the nonlinear estimation task.

Models, Biological↗

Decoupling dynamical systems for pathway identification from metabolic profiles.

RATIONALE: Modern molecular biology is generating data of unprecedented quantity and quality. Particularly exciting for biochemical pathway modeling and proteomics are comprehensive, time-dense profiles of metabolites or proteins that are measurable, for instance, with mass spectrometry, nuclear magnetic resonance or protein kinase phosphorylation. These profiles contain a wealth of information about the structure and dynamics of the pathway or network from which the data were obtained. The retrieval of this information requires a combination of computational methods and mathematical models, which are typically represented as systems of ordinary differential equations. RESULTS: We show that, for the purpose of structure identification, the substitution of differentials with estimated slopes in non-linear network models reduces the coupled system of differential equations to several sets of decoupled algebraic equations, which can be processed efficiently in parallel or sequentially. The estimation of slopes for each time series of the metabolic or proteomic profile is accomplished with a 'universal function' that is computed directly from the data by cross-validated training of an artificial neural network (ANN). CONCLUSIONS: Without preprocessing, the inverse problem of determining structure from metabolic or proteomic profile data is challenging and computationally expensive. The combination of system decoupling and data fitting with universal functions simplifies this inverse problem very significantly. Examples show successful estimations and current limitations of the method. AVAILABILITY: A preliminary Web-based application for ANN smoothing is accessible at http://bioinformatics.musc.edu/webmetabol/. S-systems can be interactively analyzed with the user-friendly freeware PLAS (http://correio.cc.fc.ul.pt/~aenf/plas.html) or with the MATLAB module BSTLab (http://bioinformatics.musc.edu/bstlab/), which is currently being beta-tested.

Algorithms↗

EURISWEB--Web-based epidemiological surveillance of antibiotic-resistant pneumococci in day care centers.

BACKGROUND: EURIS (European Resistance Intervention Study) was launched as a multinational study in September of 2000 to identify the multitude of complex risk factors that contribute to the high carriage rate of drug resistant Streptococcus pneumoniae strains in children attending Day Care Centers in several European countries. Access to the very large number of data required the development of a web-based infrastructure - EURISWEB - that includes a relational online database, coupled with a query system for data retrieval, and allows integrative storage of demographic, clinical and molecular biology data generated in EURIS. METHODS: All components of the system were developed using open source programming tools: data storage management was supported by PostgreSQL, and the hypertext preprocessor to generate the web pages was implemented using PHP. The query system is based on a software agent running in the background specifically developed for EURIS. RESULTS: The website currently contains data related to 13,500 nasopharyngeal samples and over one million measures taken from 5,250 individual children, as well as over one thousand pre-made and user-made queries aggregated into several reports, approximately. It is presently in use by participating researchers from three countries (Iceland, Portugal and Sweden). CONCLUSION: An operational model centered on a PHP engine builds the interface between the user and the database automatically, allowing an easy maintenance of the system. The query system is also sufficiently adaptable to allow the integration of several advanced data analysis procedures far more demanding than simple queries, eventually including artificial intelligence predictive models.

Child↗

Alignment-free sequence comparison-a review.

MOTIVATION: Genetic recombination and, in particular, genetic shuffling are at odds with sequence comparison by alignment, which assumes conservation of contiguity between homologous segments. A variety of theoretical foundations are being used to derive alignment-free methods that overcome this limitation. The formulation of alternative metrics for dissimilarity between sequences and their algorithmic implementations are reviewed. RESULTS: The overwhelming majority of work on alignment-free sequence has taken place in the past two decades, with most reports published in the past 5 years. Two main categories of methods have been proposed-methods based on word (oligomer) frequency, and methods that do not require resolving the sequence with fixed word length segments. The first category is based on the statistics of word frequency, on the distances defined in a Cartesian space defined by the frequency vectors, and on the information content of frequency distribution. The second category includes the use of Kolmogorov complexity and Chaos Theory. Despite their low visibility, alignment-free metrics are in fact already widely used as pre-selection filters for alignment-based querying of large applications. Recent work is furthering their usage as a scale-independent methodology that is capable of recognizing homology when loss of contiguity is beyond the possibility of alignment. AVAILABILITY: Most of the alignment-free algorithms reviewed were implemented in MATLAB code and are available at http://bioinformatics.musc.edu/resources.html

Algorithms↗

Molecular characterization of methicillin-resistant Staphylococcus epidermidis clones: evidence of geographic dissemination.

Denmark and Iceland are countries where the frequency of methicillin-resistant Staphylococcus aureus is very low due to strict infection control and restrictive antibiotic use policies. In contrast, methicillin-resistant S. epidermidis (MRSE) continues to be isolated as a nosocomial pathogen. The molecular typing by pulsed-field gel electrophoresis (PFGE) of 136 MRSE isolates from five hospitals in Denmark and 94 MRSE isolates from one hospital in Iceland collected in 1997 and 1998 defined 40 different patterns. Closely related PFGE types were found in isolates recovered in Iceland, Denmark, Mexico, Uruguay, Greece, and Cape Verde, evidencing for the first time the geographic clonal dissemination of MRSE strains. The large majority (87.4%) of the MRSE isolates studied were multiresistant.

Anti-Bacterial Agents↗