and the nuclear gene RAG2 confirm that N. plancyi is related to Pipistrellus. They further show that F. petersi is related to Hypsugo and Vespertilio, and Philetor brachypterus is related to Tylonycteris, with all of these taxa being members of the Vespertilionini, not the Pipistrellini. Nyctalus plancyi

in the program. Data layout choice is of key importance while programming in such languages. A bad data layout may degrade the performance of the system. A good data layout choice depends on various system parameters and hence makes such choice very dicult for a general user of these languages. To automate

text can be significantly aided by the availability of descriptive and semantic metadata. The Digital Curation Centre (DCC) has undertaken research to automate the extraction of metadata from documents in PDF([22]). Documents may include scientific journal papers, lab notes or even emails. We suggest

the G1-to-S progression. In addition, the existing nomenclature for cell cycle genes of Arabidopsis was updated, and the physical positions of all genes were compared with segmentally duplicated blocks in the genome, showing that 22 core cell cycle genes emerged through block duplications. This genome

mathematics [25, 22], deductive databases [7], diagnosis [13, 1], and planning [19]. As a result, mode...

discovery in databases [20], scientific discovery [22], concept discovery [14], automated data a...

disease status at death, and principal and contributory causes of death was extracted from a prospective database5,6 to ensure theIn a study of considerable practical relevance, Offner et al1 have exclusion of patients dying of infections or hemorrhage secondary shown that from 15 days after

Abstract Supporting database schema evolution repre-sents a long-standing challenge of practical and theoretical importance for modern information systems. In this paper, we describe techniques and systems for automating the critical tasks of migrating the database and rewriting the legacy

of the existing vulnerability databases were limited and inconsistent. Consequently, it is very difficult to get complete information about computer vulnerabilities by searching Web sites. Our approach was to bring together this information into a composite database. We did automated data collection from

four different classifiers, namely, support vector machines, logistic regression, classification and regression trees, and neural networks. Experiments with a database of 34 participants, 22 of which have been clinically diagnosed with probable-AD, show a neural network classifier achieving over 91