58 resultados para Computational tools
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
The mapping, exact or approximate, of a many-body problem onto an effective single-body problem is one of the most widely used conceptual and computational tools of physics. Here, we propose and investigate the inverse map of effective approximate single-particle equations onto the corresponding many-particle system. This approach allows us to understand which interacting system a given single-particle approximation is actually describing, and how far this is from the original physical many-body system. We illustrate the resulting reverse engineering process by means of the Kohn-Sham equations of density-functional theory. In this application, our procedure sheds light on the nonlocality of the density-potential mapping of density-functional theory, and on the self-interaction error inherent in approximate density functionals.
Resumo:
The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics. ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.
Resumo:
The main purpose of this paper is to present architecture of automated system that allows monitoring and tracking in real time (online) the possible occurrence of faults and electromagnetic transients observed in primary power distribution networks. Through the interconnection of this automated system to the utility operation center, it will be possible to provide an efficient tool that will assist in decisionmaking by the Operation Center. In short, the desired purpose aims to have all tools necessary to identify, almost instantaneously, the occurrence of faults and transient disturbances in the primary power distribution system, as well as to determine its respective origin and probable location. The compilations of results from the application of this automated system show that the developed techniques provide accurate results, identifying and locating several occurrences of faults observed in the distribution system.
Resumo:
Tuberculosis (TB) is one of the most common infectious diseases known to man and responsible for millions of human deaths in the world. The increasing incidence of TB in developing countries, the proliferation of multidrug resistant strains, and the absence of resources for treatment have highlighted the need of developing new drugs against TB. The shikimate pathway leads to the biosynthesis of chorismate, a precursor of aromatic amino acids. This pathway is absent from mammals and shown to be essential for the survival of Mycobacterium tuberculosis, the causative agent of TB. Accordingly, enzymes of aromatic amino acid biosynthesis pathway represent promising targets for structure-based drug design. The first reaction in phenylalanine biosynthesis involves the conversion of chorismate to prephenate, catalyzed by chorismate mutase. The second reaction is catalyzed by prephenate dehydratase (PDT) and involves decarboxylation and dehydratation of prephenate to form phenylpyruvate, the precursor of phenylalanine. Here, we describe utilization of different techniques to infer the structure of M. tuberculosis PDT (MtbPDT) in solution. Small angle X-ray scattering and ultracentrifugation analysis showed that the protein oligomeric state is a tetramer and MtbPDT is a flat disk protein. Bioinformatics tools were used to infer the structure of MtbPDT A molecular model for MtbPDT is presented and molecular dynamics simulations indicate that MtbPDT i.s stable. Experimental and molecular modeling results were in agreement and provide evidence for a tetrameric state of MtbPDT in solution.
Resumo:
Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.
Resumo:
We evaluated the performance of a novel procedure for segmenting mammograms and detecting clustered microcalcifications in two types of image sets obtained from digitization of mammograms using either a laser scanner, or a conventional ""optical"" scanner. Specific regions forming the digital mammograms were identified and selected, in which clustered microcalcifications appeared or not. A remarkable increase in image intensity was noticed in the images from the optical scanner compared with the original mammograms. A procedure based on a polynomial correction was developed to compensate the changes in the characteristic curves from the scanners, relative to the curves from the films. The processing scheme was applied to both sets, before and after the polynomial correction. The results indicated clearly the influence of the mammogram digitization on the performance of processing schemes intended to detect microcalcifications. The image processing techniques applied to mammograms digitized by both scanners, without the polynomial intensity correction, resulted in a better sensibility in detecting microcalcifications in the images from the laser scanner. However, when the polynomial correction was applied to the images from the optical scanner, no differences in performance were observed for both types of images. (C) 2008 SPIE and IS&T [DOI: 10.1117/1.3013544]
Resumo:
Chemical reactivity, photolability, and computational studies of the ruthenium nitrosyl complex with a substituted cyclam, fac-[Ru(NO)Cl(2)(kappa(3)N(4),N(8),N(11)(1-carboxypropyl)cyclam)]Cl center dot H(2)O ((1-carboxypropyl) cyclam = 3-(1,4,8,11-tetraazacyclotetradecan-1-yl) propionic acid)), (I) are described. Chloride ligands do not undergo aquation reactions (at 25 degrees C, pH 3). The rate of nitric oxide (NO) dissociation (k(obs-NO)) upon reduction of I is 2.8 s(-1) at 25 +/- 1 degrees C (in 0.5 mol L(-1) HCl), which is close to the highest value found for related complexes. The uncoordinated carboxyl of I has a pK(a) of similar to 3.3, which is close to that of the carboxyl of the non coordinated (1-carboxypropyl) cyclam (pK(a) = 3.4). Two additional pK(a) values were found for I at similar to 8.0 and similar to 11.5. Upon electrochemical reduction or under irradiation with light (lambda(irr) = 350 or 520 nm; pH 7.4), I releases NO in aqueous solution. The cyclam ring N bound to the carboxypropyl group is not coordinated, resulting in a fac configuration that affects the properties and chemical reactivities of I, especially as NO donor, compared with analogous trans complexes. Among the computational models tested, the B3LYP/ECP28MDF, cc-pVDZ resulted in smaller errors for the geometry of I. The computational data helped clarify the experimental acid-base equilibria and indicated the most favourable site for the second deprotonation, which follows that of the carboxyl group. Furthermore, it showed that by changing the pH it is possible to modulate the electron density of I with deprotonation. The calculated NO bond length and the Ru/NO charge ratio indicated that the predominant canonical structure is [Ru(III)NO], but the Ru-NO bond angles and bond index (b.i.) values were less clear; the angles suggested that [Ru(II)NO(+)] could contribute to the electronic structure of I and b.i. values indicated a contribution from [Ru(IV)NO(-)]. Considering that some experimental data are consistent with a [Ru(II)NO(+)] description, while others are in agreement with [Ru(III)NO], the best description for I would be a linear combination of the three canonical forms, with a higher weight for [Ru(II)NO(+)] and [Ru(III)NO].
Resumo:
Balance problems in hemiparetic patients after stroke can be caused by different impairments in the physiological systems involved in Postural control, including sensory afferents, movement strategies, biomechanical constraints, cognitive processing, and perception of verticality. Balance impairments and disabilities must be appropriately addressed. This article reviews the most common balance abnormalities in hemiparetic patients with stroke and the main tools used to diagnose them.
Resumo:
Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.
Resumo:
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.
Resumo:
Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.
Resumo:
The aim of the study was to evaluate the possible relationships between stress tolerance, training load, banal infections and salivary parameters during 4 weeks of regular training in fifteen basketball players. The Daily Analysis of Life Demands for Athletes` questionnaire (sources and symptoms of stress) and the Wisconsin Upper Respiratory Symptom Survey were used on a weekly basis. Salivary cortisol and salivary immunoglobulin A (SIgA) were collected at the beginning (before) and after the study, and measured by enzyme-linked immunosorbent assay (ELISA). Ratings of perceived exertion (training load) were also obtained. The results from ANOVA with repeated measures showed greater training loads, number of upper respiratory tract infection episodes and negative sensation to both symptoms and sources of stress, at week 2 (p < 0.05). Significant increases in cortisol levels and decreases in SIgA secretion rate were noted (before to after). Negative sensations to symptoms of stress at week 4 were inversely and significantly correlated with SIgA secretion rate. A positive and significant relationship between sources and symptoms of stress at week 4 and cortisol levels were verified. In summary, an approach incorporating in conjunction psychometric tools and salivary biomarkers could be an efficient means of monitoring reaction to stress in sport. Copyright (C) 2010 John Wiley & Sons, Ltd.
Resumo:
Motivation: Understanding the patterns of association between polymorphisms at different loci in a population ( linkage disequilibrium, LD) is of fundamental importance in various genetic studies. Many coefficients were proposed for measuring the degree of LD, but they provide only a static view of the current LD structure. Generative models (GMs) were proposed to go beyond these measures, giving not only a description of the actual LD structure but also a tool to help understanding the process that generated such structure. GMs based in coalescent theory have been the most appealing because they link LD to evolutionary factors. Nevertheless, the inference and parameter estimation of such models is still computationally challenging. Results: We present a more practical method to build GM that describe LD. The method is based on learning weighted Bayesian network structures from haplotype data, extracting equivalence structure classes and using them to model LD. The results obtained in public data from the HapMap database showed that the method is a promising tool for modeling LD. The associations represented by the learned models are correlated with the traditional measure of LD D`. The method was able to represent LD blocks found by standard tools. The granularity of the association blocks and the readability of the models can be controlled in the method. The results suggest that the causality information gained by our method can be useful to tell about the conservability of the genetic markers and to guide the selection of subset of representative markers.
Resumo:
This work presents an analysis of the wavelet-Galerkin method for one-dimensional elastoplastic-damage problems. Time-stepping algorithm for non-linear dynamics is presented. Numerical treatment of the constitutive models is developed by the use of return-mapping algorithm. For spacial discretization we can use wavelet-Galerkin method instead of standard finite element method. This approach allows to locate singularities. The discrete formulation developed can be applied to the simulation of one-dimensional problems for elastic-plastic-damage models. (C) 2007 Elsevier Inc. All rights reserved.