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A Practical Approach to Significance Assessment in Alignment with Gaps
Author(s) -
Nicholas Chia,
Ralf Bundschuh
Publication year - 2006
Publication title -
journal of computational biology
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.585
H-Index - 95
eISSN - 1557-8666
pISSN - 1066-5277
ISBN - 3-540-25866-3
DOI - 10.1089/cmb.2006.13.429
Subject(s) - computer science , statistical hypothesis testing , significance testing , statistical analysis , current (fluid) , machine learning , algorithm , data mining , statistics , mathematics , engineering , electrical engineering
Current numerical methods for assessing the statistical significance of local alignments with gaps are time consuming. Analytical solutions thus far have been limited to specific cases. Here, we present a new line of attack to the problem of statistical significance assessment. We combine this new approach with known properties of the dynamics of the global alignment algorithm and high performance numerical techniques and present a novel method for assessing significance of gaps within practical time scales. The results and performance of these new methods test very well against tried methods with drastically less effort.

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