Toward a multilevel representation of protein molecules: comparative approaches to the aggregation/folding propensity problem

This paper builds upon the fundamental work of Niwa et al. [34], which provides the unique possibility to analyze the relative aggregation/folding propensity of the elements of the entire Escherichia coli (E. coli) proteome in a cell-free standardized microenvironment. The hardness of the problem comes from the superposition between the driving forces of intra- and inter-molecule interactions and it is mirrored by the evidences of shift from folding to aggregation phenotypes by single-point mutations [10]. Here we apply several state-of-the-art classification methods coming from the field of structural pattern recognition, with the aim to compare different representations of the same proteins gathered from the Niwa et al. data base; such representations include sequences and labeled (contact) graphs enriched with chemico-physical attributes. By this comparison, we are able to identify also some interesting general properties of proteins. Notably, (i) we suggest a threshold around 250 residues discriminating "easily foldable" from "hardly foldable" molecules consistent with other independent experiments, and (ii) we highlight the relevance of contact graph spectra for folding behavior discrimination and characterization of the E. coli solubility data. The soundness of the experimental results presented in this paper is proved by the statistically relevant relationships discovered among the chemico-physical description of proteins and the developed cost matrix of substitution used in the various discrimination systems.Comment: 17 pages, 3 figures, 46 reference

An incremental interval Type-2 neural fuzzy Classifier

© 2015 IEEE. Most real world classification problems involve a high degree of uncertainty, unsolved by a traditional type-1 fuzzy classifier. In this paper, a novel interval type-2 classifier, namely Evolving Type-2 Classifier (eT2Class), is proposed. The eT2Class features a flexible working principle built upon a fully sequential and local working principle. This learning notion allows eT2Class to automatically grow, adapt, prune, recall its knowledge from data streams in the single-pass learning fashion, while employing loosely coupled fuzzy sub-models. In addition, eT2Class introduces a generalized interval type-2 fuzzy neural network architecture, where a multivariate Gaussian function with uncertain non-diagonal covariance matrixes constructs the rule premise, while the rule consequent is crafted by a local non-linear Chebyshev polynomial. The efficacy of eT2Class is numerically validated by numerical studies with four data streams characterizing non-stationary behaviors, where eT2Class demonstrates the most encouraging learning performance in achieving a tradeoff between accuracy and complexity

Toward a Model of Intercultural Warrant: A Case of the Korean Decimal Classification\u27s Cross-cultural Adaptation of the Dewey Decimal Classification

I examined the Korean Decimal Classification (KDC)\u27s adaptation of the Dewey Decimal Classification (DDC) by comparing the two systems. This case manifests the sociocultural influences on KOSs in a cross-cultural context. I focused my analysis on the changes resulting from the meeting of the two cultures, answering the main research question: “How does KDC adapt DDC in terms of underlying sociocultural perspectives in a classificatory form?” I took a comparative approach and address the main research question in two phases. In Phase 1, quantities of class numbers were analyzed by edition and discipline. The main class with the most consistently high number of class numbers in DDC was the social sciences, while the main class with the most consistently high number of class numbers in KDC was technology. The two main classes are expected to differ in semantic contents or specificities. In Phase 2, patterns of adaptations were analyzed by examining the class numbers, captions, and hierarchical relations within the developed adaptation taxonomy. Implementing the taxonomy as a coding scheme brings two comparative features of classifications: 1) semantic contents determined by captions and quantity of subordinate numbers; and 2) structural arrangement determined by ranks, the broader category, presence and the order of subordinate numbers. Surveying proper forms of adaptation resulted in the development of an adaptation taxonomy that will serve as a framework to account for the conflicts between and harmonization of multiple social and cultural influences in knowledge structures. This study has ramifications in theoretical and empirical foundations for the development of “intercultural warrant” in KOSs

Dublin City University at QA@CLEF 2008

We describe our participation in Multilingual Question Answering at CLEF 2008 using German and English as our source and target languages respectively. The system was built using UIMA (Unstructured Information Management Architecture) as underlying framework