Confidence value prediction of DNA sequencing with Petri net model

Fuzzy Petri net; Fuzzy logic; DNA sequencing; Modeling and simulation Abstract In this paper, a fuzzy Petri net (FPN) approach to modeling fuzzy rule-based reasoning is proposed to determining confidence values for bases called in DNA sequencing. The proposed approach is to bring DNA bases-called within the framework of a powerful modeling tool FPN. The three input features in our fuzzy model-the height, the peakness, and the spacing of the first most likely candidate (the base called) and the peakness and height for the second likely candidate can be formulated as uncertain fuzzy tokens to determines the confidence values. The FPN components and functions are mapped from the different type of fuzzy operators of If-parts and Thenparts in fuzzy rules. The validation was achieved by comparing the results obtained with the FPN model and fuzzy logic using the MATLAB Toolbox; both methods have the same reasoning outcomes. Our experimental results suggest that the proposed models, can achieve the confidence values that matches, of available software. a 2011 King Saud University. Production and hosting by Elsevier B.V. All rights reserved.