MR-Radix: a multi-relational data mining algorithm

Abstract Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.

Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

A systematic study of transfection efficiency and cytotoxicity in HeLa cells using iron oxide nanoparticles prepared with organic and inorganic bases

Magnetic iron oxide nanoparticles (magnetite) (MNPs) were prepared using different organic and inorganic bases. Strong inorganic base (KOH) and organic bases (NH4OH and 1,4-diazabicyclo[2.2.2]octane (DABCO)) were used in the syntheses of the MNPs. The MNPs were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM). Fourier transform infrared spectroscopy (FT-IR) and magnetization measurements. MNPs prepared with strong inorganic base yielded an average size of 100 nm, whereas the average size of the MNPs prepared with the organic bases was 150 nm. The main competitive phase for MNPs prepared with the strong inorganic and organic bases was maghemite; however, syntheses with KOH yielded a pure magnetite phase. The transfection study performed with the MNPs revealed that the highest transfection rate was obtained with the MNPs prepared with KOH (74%). The correlation between the magnetic parameters and the transfection ratio without transfection agents indicated that MNPs prepared with KOH were a better vector for possible applications of these MNPs in biomedicine. HeLa cells incubated with MNP-KOH at 10 mu g/mL for 24 and 48 h exhibited a decrease in population in comparison with the control cells and it was presumably related to the toxicity of the MNPs. However, the cells incubated with MNP-KOH at 50 and 100 mu g/mL presented a very small difference in the viability between the cell populations studied at 24 and 48 h. These data illustrate the viability of HeLa cells treated with MNP-KOH and suggest the potential use of these MNPs in biomedical applications. (C) 2012 Elsevier B.V. All rights reserved.

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.

Periódicos de Ciência da Informação nas bases de dados internacionais

PO artigo demonstra as interações entre algumas bases de dados internacionais na disponibilização de periódicos da área de Ciência da Informação. Para isso, foram investigadas seis bases de dados com acesso a texto completo dentro da área de Ciência da Informação. Foram elas: Web of Science, Scopus, Library, Information Science & Technology Abstracts, Information Science & Technology Abstracts, Library Literature Information Science – full text e Library Information Science Abstract. No desenvolvimento da pesquisa foram utilizados conceitos, princípios e equações da ‘teoria ingênua dos conjuntos’, o que permitiu observar as bases de dados como conjuntos compostos por elementos, aqui considerados os títulos de periódicos, bem como conferir consistência aos resultados. A análise dos dados foi dividida em três etapas, a saber: a) a primeira priorizou o cruzamento entre as duas maiores bases de dados utilizadas para levantamento bibliográfico (Web of Science e Scopus), seguido do cruzamento com a mais utilizada na Ciência da Informação, a Library and Information Science Abstracts; b) a segunda etapa tratou somente do cruzamento das bases especialistas da área; c) a terceira e última etapa tratou da interseção de todas as bases de dados do estudo. O resultado mostra que 10 títulos de periódicos constituem a interseção dos seis conjuntos de bases de dados. Foi possível identificar, também, o número de periódicos disponibilizados exclusivamente por uma base de dados, demonstrando que as necessidades de pesquisas bibliográficas exaustivas passam, obrigatoriamente, pelo levantamento em todas as bases de dados aqui elencadas.