Methods and tools for encoding the WordNet.Br sentences, concept glosses, and conceptual-semantic relations

This paper presents the overall methodology that has been used to encode both the Brazilian Portuguese WordNet (WordNet.Br) standard language-independent conceptual-semantic relations (hyponymy, co-hyponymy, meronymy, cause, and entailment) and the so-called cross-lingual conceptual-semantic relations between different wordnets. Accordingly, after contextualizing the project and outlining the current lexical database structure and statistics, it describes the WordNet.Br editing GUI that was designed to aid the linguist in carrying out the tasks of building synsets, selecting sample sentences from corpora, writing synset concept glosses, and encoding both language-independent conceptual-semantic relations and cross-lingual conceptual-semantic relations between WordNet.Br and Princeton WordNet © Springer-Verlag Berlin Heidelberg 2006.

Molecular modeling databases: A new way in the search of protein targets for drug development

DBMODELING is a relational database of annotated comparative protein structure models and their metabolic, pathway characterization. It is focused on enzymes identified in the genomes of Mycobacterium tuberculosis and Xylella fastidiosa. The main goal of the present database is to provide structural models to be used in docking simulations and drug design. However, since the accuracy of structural models is highly dependent on sequence identity between template and target, it is necessary to make clear to the user that only models which show high structural quality should be used in such efforts. Molecular modeling of these genomes generated a database, in which all structural models were built using alignments presenting more than 30% of sequence identity, generating models with medium and high accuracy. All models in the database are publicly accessible at http://www.biocristalografia.df.ibilce.unesp.br/tools. DBMODELING user interface provides users friendly menus, so that all information can be printed in one stop from any web browser. Furthermore, DBMODELING also provides a docking interface, which allows the user to carry out geometric docking simulation, against the molecular models available in the database. There are three other important homology model databases: MODBASE, SWISSMODEL, and GTOP. The main applications of these databases are described in the present article. © 2007 Bentham Science Publishers Ltd.

Efficient parametric adjustment of fuzzy inference system using unconstrained optimization

This paper presents a new methodology for the adjustment of fuzzy inference systems, which uses technique based on error back-propagation method. The free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules, are automatically adjusted. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through estimation of time series and by a mathematical modeling problem. More specifically, the Mackey-Glass chaotic time series is used for the validation of the proposed methodology. © Springer-Verlag Berlin Heidelberg 2007.

Optimal clone identifier for genomic shotgun libraries: OC Identifier tool

In DNA microarray experiments, the gene fragments that are spotted on the slides are usually obtained by the synthesis of specific oligonucleotides that are able to amplify genes through PCR. Shotgun library sequences are an alternative to synthesis of primers for the study of each gene in the genome. The possibility of putting thousands of gene sequences into a single slide allows the use of shotgun clones in order to proceed with microarray analysis without a completely sequenced genome. We developed an OC Identifier tool (optimal clone identifier for genomic shotgun libraries) for the identification of unique genes in shotgun libraries based on a partially sequenced genome; this allows simultaneous use of clones in projects such as transcriptome and phylogeny studies, using comparative genomic hybridization and genome assembly. The OC Identifier tool allows comparative genome analysis, biological databases, query language in relational databases, and provides bioinformatics tools to identify clones that contain unique genes as alternatives to primer synthesis. The OC Identifier allows analysis of clones during the sequencing phase, making it possible to select genes of interest for construction of a DNA microarray. ©FUNPEC-RP.

Implementation of filters for image pre-processing for leaf analyses in plantations

In this work an image pre-processing module has been developed to extract quantitative information from plantation images with various degrees of infestation. Four filters comprise this module: the first one acts on smoothness of the image, the second one removes image background enhancing plants leaves, the third filter removes isolated dots not removed by the previous filter, and the fourth one is used to highlight leaves' edges. At first the filters were tested with MATLAB, for a quick visual feedback of the filters' behavior. Then the filters were implemented in the C programming language. At last, the module as been coded in VHDL for the implementation on a Stratix II family FPGA. Tests were run and the results are shown in this paper. © 2008 Springer-Verlag Berlin Heidelberg.

A framework for learning in humanoid simulated robots

One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.

A clinical decision support system for cancer diseases

The second main cause of death in Brazil is cancer, and according to statistics disclosed by National Cancer Institute from Brazil (INCA) 466,730 new cases of cancer are forecast for 2008. The analysis of tumour tissues of various types and patients' clinical data, genetic profiles, characteristics of diseases and epidemiological data may lead to more precise diagnoses, providing more effective treatments. In this work we present a clinical decision support system for cancer diseases, which manages a relational database containing information relating to the tumour tissue and their location in freezers, patients and medical forms. Furthermore, it is also discussed some problems encountered, as database integration and the adoption of a standard to describe topography and morphology. It is also discussed the dynamic report generation functionality, that shows data in table and graph format, according to the user's configuration. © ACM 2008.

Routine libraries for pattern recognition in quasispecies.

The results obtained through biological research usually need to be analyzed using computational tools, since manual analysis becomes unfeasible due to the complexity and size of these results. For instance, the study of quasispecies frequently demands the analysis of several, very lengthy sequences of nucleotides and amino acids. Therefore, bioinformatics tools for the study of quasispecies are constantly being developed due to different problems found by biologists. In the present study, we address the development of a software tool for the evaluation of population diversity in quasispecies. Special attention is paid to the localization of genome regions prone to changes, as well as of possible hot spots.

A medical information system to manage a cancer database

Cancer is the second main cause of death in Brazil, and according to statistics disclosed by INCA - National Cancer Institute 466,730 new cases of the disease are forecast for 2008. The storage and analysis of tumour tissues of various types and patients' clinical data, genetic profiles, characteristics of diseases and epidemiological data may provide more precise diagnoses, providing more effective treatments with higher chances for the cure of cancer. In this paper we present a Web system with a client-server architecture, which manages a relational database containing all information relating to the tumour tissue and their location in freezers, patients, medical forms, physicians, users, and others. Furthermore, it is also discussed the software engineering used to developing the system.

Automatic classification of enzyme family in protein annotation

Most of the tasks in genome annotation can be at least partially automated. Since this annotation is time-consuming, facilitating some parts of the process - thus freeing the specialist to carry out more valuable tasks - has been the motivation of many tools and annotation environments. In particular, annotation of protein function can benefit from knowledge about enzymatic processes. The use of sequence homology alone is not a good approach to derive this knowledge when there are only a few homologues of the sequence to be annotated. The alternative is to use motifs. This paper uses a symbolic machine learning approach to derive rules for the classification of enzymes according to the Enzyme Commission (EC). Our results show that, for the top class, the average global classification error is 3.13%. Our technique also produces a set of rules relating structural to functional information, which is important to understand the protein tridimensional structure and determine its biological function. © 2009 Springer Berlin Heidelberg.

Plant species identification using multi-scale fractal dimension applied to images of adaxial surface epidermis

This paper presents the study of computational methods applied to histological texture analysis in order to identify plant species, a very difficult task due to the great similarity among some species and presence of irregularities in a given species. Experiments were performed considering 300 ×300 texture windows extracted from adaxial surface epidermis from eight species. Different texture methods were evaluated using Linear Discriminant Analysis (LDA). Results showed that methods based on complexity analysis perform a better texture discrimination, so conducting to a more accurate identification of plant species. © 2009 Springer Berlin Heidelberg.

Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm

This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The results are compared with bio-inspired methods, and rule induction and decision tree algorithms for data mining. © 2009 Springer Berlin Heidelberg.

Optimal clone identifier based on dynamic rules and process algebra

The rule creation to clone selection in different projects is a hard task to perform by using traditional implementations to control all the processes of the system. The use of an algebraic language is an alternative approach to manage all of system flow in a flexible way. In order to increase the power of versatility and consistency in defining the rules for optimal clone selection, this paper presents the software OCI 2 in which uses process algebra in the flow behavior of the system. OCI 2, controlled by an algebraic approach was applied in the rules elaboration for clone selection containing unique genes in the partial genome of the bacterium Bradyrhizobium elkanii Semia 587 and in the whole genome of the bacterium Xanthomonas axonopodis pv. citri. Copyright© (2009) by the International Society for Research in Science and Technology.

SKPDB: A structural database of shikimate pathway enzymes

Background: The functional and structural characterisation of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design. The main interest in studying shikimate pathway enzymes involves the fact that they are essential for bacteria but do not occur in humans, making them selective targets for design of drugs that do not directly impact humans.Description: The ShiKimate Pathway DataBase (SKPDB) is a relational database applied to the study of shikimate pathway enzymes in microorganisms and plants. The current database is updated regularly with the addition of new data; there are currently 8902 enzymes of the shikimate pathway from different sources. The database contains extensive information on each enzyme, including detailed descriptions about sequence, references, and structural and functional studies. All files (primary sequence, atomic coordinates and quality scores) are available for downloading. The modeled structures can be viewed using the Jmol program.Conclusions: The SKPDB provides a large number of structural models to be used in docking simulations, virtual screening initiatives and drug design. It is freely accessible at http://lsbzix.rc.unesp.br/skpdb/. © 2010 Arcuri et al; licensee BioMed Central Ltd.

Fast automatic microstructural segmentation of ferrous alloy samples using optimum-path forest

In this work we propose a novel automatic cast iron segmentation approach based on the Optimum-Path Forest classifier (OPF). Microscopic images from nodular, gray and malleable cast irons are segmented using OPF, and Support Vector Machines (SVM) with Radial Basis Function and SVM without kernel mapping. Results show accurate and fast segmented images, in which OPF outperformed SVMs. Our work is the first into applying OPF for automatic cast iron segmentation. © 2010 Springer-Verlag.