Inferring the precise locations and splicing patterns of genes in
DNA is a difficult but important task, with broad applications to
biomedicine. The mathematical and statistical techniques that have
been applied to this problem are surveyed and organized into a
logical framework based on the theory of parsing. Both established
approaches and methods at the forefront of current research are
discussed. Numerous case studies of existing software systems are
provided, in addition to detailed examples that work through the
actual implementation of effective gene-predictors using hidden
Markov models and other machine-learning techniques. Background
material on probability theory, discrete mathematics, computer
science, and molecular biology is provided, making the book
accessible to students and researchers from across the life and
computational sciences. This book is ideal for use in a first
course in bioinformatics at graduate or advanced undergraduate
level, and for anyone wanting to keep pace with this
rapidly-advancing field.
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