Knowledge discovery and data mining in biological databases

The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.

Document retrieval for e-mail search and discovery using Formal Concept Analysis

This paper discusses a document discovery tool based on Conceptual Clustering by Formal Concept Analysis. The program allows users to navigate e-mail using a visual lattice metaphor rather than a tree. It implements a virtual. le structure over e-mail where files and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assist in e-mail discovery. The system described provides more flexibility in retrieving stored e-mails than what is normally available in e-mail clients. The paper discusses how conceptual ontologies can leverage traditional document retrieval systems and aid knowledge discovery in document collections.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Evaluation of unsupervised semantic mapping of natural language with Leximancer concept mapping

The Leximancer system is a relatively new method for transforming lexical co-occurrence information from natural language into semantic patterns in an unsupervised manner. It employs two stages of co-occurrence information extraction-semantic and relational-using a different algorithm for each stage. The algorithms used are statistical, but they employ nonlinear dynamics and machine learning. This article is an attempt to validate the output of Leximancer, using a set of evaluation criteria taken from content analysis that are appropriate for knowledge discovery tasks.

Finding negative event oriented patterns in long temporal sequences

Pattern discovery in a long temporal event sequence is of great importance in many application domains. Most of the previous work focuses on identifying positive associations among time stamped event types. In this paper, we introduce the problem of defining and discovering negative associations that, as positive rules, may also serve as a source of knowledge discovery. In general, an event-oriented pattern is a pattern that associates with a selected type of event, called a target event. As a counter-part of previous research, we identify patterns that have a negative relationship with the target events. A set of criteria is defined to evaluate the interestingness of patterns associated with such negative relationships. In the process of counting the frequency of a pattern, we propose a new approach, called unique minimal occurrence, which guarantees that the Apriori property holds for all patterns in a long sequence. Based on the interestingness measures, algorithms are proposed to discover potentially interesting patterns for this negative rule problem. Finally, the experiment is made for a real application.

Load profiling and data mining techniques in electricity deregulated market

This paper presents load profiles of electricity customers, using the knowledge discovery in databases (KDD) procedure, a data mining technique, to determine the load profiles for different types of customers. In this paper, the current load profiling methods are compared using data mining techniques, by analysing and evaluating these classification techniques. The objective of this study is to determine the best load profiling methods and data mining techniques to classify, detect and predict non-technical losses in the distribution sector, due to faulty metering and billing errors, as well as to gather knowledge on customer behaviour and preferences so as to gain a competitive advantage in the deregulated market. This paper focuses mainly on the comparative analysis of the classification techniques selected; a forthcoming paper will focus on the detection and prediction methods.

Popper and his Commentators on the Discovery of Neptune: a close shave for the Law of Gravitation?

Knowledge of residual perturbations in the orbit of Uranus in the early 1840s did not lead to the refutation of Newton's law of gravitation but instead to the discovery of Neptune in 1846. Karl Popper asserts that this case is atypical of science and that the law of gravitation was at least prima facie falsified by these perturbations. I argue that these assertions are the product of a false, a priori methodological position I call, 'Weak Popperian Falsificationism' (WPF). Further, on the evidence the law was not prima facie false and was not generally considered so by astronomers at the time. Many of Popper's commentators (Kuhn, Lakatos, Feyerabend and others) presuppose WPF and their views on this case and its implications for scientific rationality and method suffer from this same defect.

Recent advances in our knowledge of the Myxozoa

In the last few years two factors have helped to significantly advance our understanding of the Myxozoa. First, the phenomenal increase in fin fish aquaculture in the 1990s has lead to the increased importance of these parasites; in rum this has lead to intensified research efforts, which have increased knowledge of the development, diagnosis, and pathogenesis of myxozoans. The hallmark discovery in the 1980s that the life cycle of Myxobolus cerebralis requires development of an actinosporean stage in the Oligochaete. Tubifex tubifex, led to the elucidation of the life cycles of several other myxozoans. Also, the life cycle and taxonomy of the enigmatic PKX myxozoan has been resolved: it is the alternate stage of the unusual myxozoan. Tetracapsula bryosalmonae, from bryozoans. The 18S rDNA gene of many species has been sequenced, and here we add 22 new sequences to the data set. Phylogenetic analyses using all these sequences indicate that: 1) the Myxozoa are closely related to Cnidaria (also supported by morphological data), 2) marine taxa at the genus level branch separately from genera that usually infect freshwater fishes; 3) taxa cluster more by development and tissue location than by spore morphology; 4) the tetracapsulids branched off early in myxozoan evolution, perhaps reflected by their having bryozoan. rather than annelid hosts; 5) the morphology of actinosporeans offers little information for determining their myxosporean counterparts (assuming that they exist), and 6) the marine actinosporeans from Australia appear to form a clade within the platysporinid myxosporeans. Ribosomal DNA sequences have also enabled development of diagnostic tests for myxozoans. PCR and in situ hybridisation tests based on rDNA sequences have been developed for Myxobolus cerebralis. Ceratomyxa shasta. Kudoa spp,, and Tetracapsula bryosalmonae (PKX). Lectin-based and antibody tests have also been developed for certain myxozoans, such as PKX and C. shasta. We also review important diseases caused by myxozoans. which are emerging or re-emerging. Epizootics of whirling disease in wild rainbow trout (Oncorhynchus mykiss) have recently been reported throughout the Rocky Mountain states of the USA. With a dramatic increase in aquaculture of fishes using marine netpens, several marine myxozoans have been recognized or elevated in status as pathological agents. Kudoa thyrsites infections have caused severe post-harvest myoliquefaction in pen-reared Atlantic salmon (Salmo salar), and Ceratomyxa spp., Sphaerospora spp., and Myxidium leei cause disease in pen-reared sea bass (Dicentrarchus labrax) and sea bream species (family Sparidae) in Mediterranean countries.

Children's body knowledge: Understanding 'life' as a biological goal

Two studies assessed the development of children's understanding of life as a biological goal of body functioning. In Study 1, 4-to-10-year-old children were given an interview consisting of a series of structured questions about the location and function of various body organs. Their responses were coded both for factual correctness and for appeals to the goal of maintaining life. The results showed a gradual increase in children's factual knowledge across this age range but an abrupt increase in appeals to life between the ages of 4 and 6. Analyses of the 4-year-olds' responses suggested that appeals to life were associated with increased knowledge of organ function, but not of organ location. Study 2 was designed to replicate the pattern found in Study I. A continuous sample of 4-to 5-year-old children was administered an abbreviated version of the interview from Study 1. Children's understanding of life as a biological goal was again found to be predictive of their knowledge of organ function, but not of organ location. These results indicate a reorganization in children's understanding of the body between the ages of 4 and 6, which coincides with children's discovery of 'life' as a biological goal for bodily function.

The emergence of order in random walk resource discovery protocols

While others have attempted to determine, by way of mathematical formulae, optimal resource duplication strategies for random walk protocols, this paper is concerned with studying the emergent effects of dynamic resource propagation and replication. In particular, we show, via modelling and experimentation, that under any given decay (purge) rate the number of nodes that have knowledge of particular resource converges to a fixed point or a limit cycle. We also show that even for high rates of decay - that is, when few nodes have knowledge of a particular resource - the number of hops required to find that resource is small.

New descriptions and understandings of internationalisation: A tale of knowledge-intensive SMEs

This research seeks to generate and foster new descriptions and understandings of processes underlying the internationalisation experienced by small- and medium-sized, knowledge-intensive enterprises. The longitudinal study centres on the growth and internationalisation of a cluster of small- and medium-sized enterprises (SMEs) in the most southern state of Australia, of which a number were 'bom global.' It draws on both retrospective data such as corporate archives, as well as observations and interviews as events unfolded over a period of eighteen months to garner insights into processes underlying the SMEs' internationalisation. The approach to inquiry is influenced by an epistemology of social constructionism, interpretive narrative, sensemaking and dramaturgical theoretical perspectives, and elements of cultural anthropology. Exploratory in the early stages, a funnel approach characteristic of ethnographic enquiry was used whereby the study became progressively focused over time. The extended period of fieldwork led to observations and interpretations that cast the retrospective data in new light, and the use of the construct 'legitimacy' as a lens through which to view activities and events infusing the firms' internationalisation. A generic narrative scheme that offers a temporal ordering of actions, context and meaning attributions in relation to legitimation behaviours and internationalisation processes is developed. This narrative scheme is then used to garner a deeper understanding of three activities that were central to the firms' internationalisation over time: the choice of geographic export markets, strategic participation in international standard-setting committees, and portfolio entrepreneurship. In addition, the study offers a rich story of the growth and internationalisation of the cluster of knowledge-intensive SMEs. The tale of growth and internationalisation pursued by the cluster of knowledgeintensive SMEs spans the period from 1975 to mid 1997, and may prove a useful resource for the theorising of others.