3 research outputs found

    A framework for improving microRNA prediction in non-human genomes

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    The prediction of novel pre-microRNA (miRNA) from genomic sequence has received considerable attention recently. However, the majority of studies have focused on the human genome. Previous studies have demonstrated that sensitivity (correctly detecting true miRNA) is sustained when human-trained methods are applied to other species, however they have failed to report the dramatic drop in specificity (the ability to correctly reject non-miRNA sequences) in

    Exact string matching for MS/MS protein identification using the cell broadband engine

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    Current computational mass spectrometry techniques are limited by data acquisition techniques which often make sub-optimal use of mass spectrometry hardware and produce datasets which may not uniquely identify all proteins present in the biological sample. This is largely due to the offline nature of the data analysis, which is only conducted after acquisition is complete. Recently proposed online data analysis techniques which guide data acquisition, known as information-driven or directed tandem mass spectrometry (MS/MS) techniques, show promise in producing mass spectrometry datasets which uniquely identify a greater number of proteins, but these techniques have not yet been feasible due to the strict real-time requirements of mass spectrometry data acquisition. With the introduction of novel parallel programming models, such as the heterogeneous multicore Cell broadband engine (Cell B/E) architecture, information-driven MS/MS may now be possible. One of the biggest computational hurdles in creating an information-driven MS/MS system is the need to rapidly search proteomic databases for peptide fragments as they are identified by the mass spectrometer in real-time. Therefore, as a first step toward information-driven MS/MS, we have implemented a parallel string matching algorithm which is tailored to single peptide fragment searches over large proteomic databases. The Orthogonal Parabix algorithm introduced here has achieved sustained throughputs of 215.4 Gbps on a QS22 Cell blade representing a 4x speedup over leading general-purpose string matching algorithms on comparable hardware and more than 10x over an equivalent serial algorithm on a modern desktop processor. The peptide string matching algorithms developed here will form an integral part of a complete real-time information-driven MS/MS system which is expected to achieve higher-confidence protein identifications, particularly for low-abundance proteins and biomarkers

    Argumentation in Foreign Policy Settings

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    This is a study of argumentation in three different kinds of high level, confidential, foreign policy settings: a collegial setting, a bureaucratic setting, and a bargaining setting. The causal and value assertions of the participants were coded using the detailed records of these three settings. The data show to be inadequate a defense/ attack model of argumentation in which the participants support their own arguments to make them resistant to attack, while attacking the weak spots in others'stated positions. In fact, there are few assertions which are supported by specific evidence, almost no mutually supported causal arguments, and the assertions which were attacked were no less emphasized than the assertions which were not attacked. More in accord with the data is the novel-arguments approach in which the key factor in persuasive argumentation is the development of arguments which others have not already taken into account.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67391/2/10.1177_002200277702100410.pd
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