Structuring technological information for technology roadmapping: Data mining approach

Most research on technology roadmapping has focused on its practical applications and the development of methods to enhance its operational process. Thus, despite a demand for well-supported, systematic information, little attention has been paid to how/which information can be utilised in technology roadmapping. Therefore, this paper aims at proposing a methodology to structure technological information in order to facilitate the process. To this end, eight methods are suggested to provide useful information for technology roadmapping: summary, information extraction, clustering, mapping, navigation, linking, indicators and comparison. This research identifies the characteristics of significant data that can potentially be used in roadmapping, and presents an approach to extracting important information from such raw data through various data mining techniques including text mining, multi-dimensional scaling and K-means clustering. In addition, this paper explains how this approach can be applied in each step of roadmapping. The proposed approach is applied to develop a roadmap of radio-frequency identification (RFID) technology to illustrate the process practically. © 2013 © 2013 Taylor & Francis.

Development of novel EST-SSR markers in common carp by data mining from public EST sequences

Expressed sequence tags (ESTs) are a source for microsatellite development. In the present study, EST-derived microsatelltes (EST-SSRs) were generated and characterized in the common carp (Cyprinus carpio) by data mining from updated public EST databases and by subsequent testing for polymorphism. About 5.5% (555) of 10,088 ESTs contain repeat motifs of various types and lengths with CA being the most abundant dinucleotide one. Out of the 60 EST-SSRs for which PCR primers were designed, 25 loci showed polymorphism in a common carp population with the alleles per locus ranging from 3 to 17 (mean 7). The observed (H-O) and expected (HE) heterozygosities of these EST-SSRs were 0.13-1.00 and 0.12-0.91, respectively. Six EST-SSR loci significantly deviated from the Hardy-Weinberg equilibrium (HWE) expectation, and the remaining 19 loci were in HWE. Of the 60 primer sets, the rates of polymorphic EST-SSRs were 42% in common carp, 17% in crucian carp (Carassius auratus), and 5% in silver carp (Hypophthalmichthys molitrix), respectively. These new EST-SSR markers would provide sufficient polymorphism for population genetic studies and genome mapping of the common carp and its closely related fishes. (c) 2007 Published by Elsevier B.V.

Mining expressed sequences for single nucleotide polymorphisms in Pacific abalone Haliotis discus hannai

Although single nucleotide polymorphisms (SNPs) are important resources for population genetics, pedigree analysis and genomic mapping, such loci have not been reported in Pacific abalone so far. In this study, a bioinformatics strategy was adopted to discover SNPs within the expressed sequences (ESTs) of Pacific abalone, Haliotis discus hannai, and furthermore, polymerase chain reaction direct sequencing (PCR-DS) and allele-specific PCR (AS-PCR) were used for SNPs detection and genotype scoring respectively. A total of 5893 ESTs were assembled and 302 putative SNPs were identified. The average density of SNPs in ESTs was 1%. Fifty-two sets of sequencing primers were designed from SNPs flanking ESTs to amplify the genomic DNA, and 13 could generate products of expected size. Polymerase chain reaction direct sequencing of the amplification products from pooled DNA samples revealed 40 polymorphic SNP loci. Using a modified tetra-primer AS-PCR, seven mitochondrial and six nuclear SNPs were typed and characterized among 37 wild abalones. In conclusion, it is feasible to discover SNPs from number limited ESTs and the AS-PCR as a simple, robust and reliable assay could be a primary method for small- and medium-scale SNPs detection in abalones as well as other non-model organisms.

Heuristics for protecting competitive knowledge in association rule mining.

2006