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Comparative Gene Finding pp 201–267Cite as

Gene Structure Submodels

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Part of the book series: Computational Biology ((COBO,volume 20))

Abstract

A gene model algorithm integrates a wide range of scores, or signals, coming from the ingoing states of the model. These states are themselves complex submodels, which incorporate a number of sensors used to score the different characteristics of the submodel. Such sensors are traditionally divided into two groups: content sensors and signal sensors. Signal sensors model the transition between states, and attempt to detect the boundaries between exons and introns in the sequence, while content sensors score the content of a candidate region, such as the base composition or length distribution of a candidate exon or intron. In this chapter we describe some of the main submodels used in gene finding algorithms, and detail a number of different methods for integrating the sensors the submodels incorporate.

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  1. Chalmers University of Technology, Gothenburg, Sweden

    Marina Axelson-Fisk

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  1. Marina Axelson-Fisk
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Axelson-Fisk, M. (2015). Gene Structure Submodels. In: Comparative Gene Finding. Computational Biology, vol 20. Springer, London. https://doi.org/10.1007/978-1-4471-6693-1_5

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  • DOI: https://doi.org/10.1007/978-1-4471-6693-1_5

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