@inproceedings{559a0d6584a74a1188a8d43da2b2ebfb,
title = "SEPA: Approximate non-subjective empirical p-value estimation for nucleotide sequence alignment",
abstract = "In the bioinformatics literature, pairwise sequence alignment methods appear with many variations and diverse applications. With this abundance, comes not only an emphasis on speed and memory efficiency, but also a need for assigning confidence to the computed alignments through p-value estimation, especially for important segment pairs within an alignment. This paper examines an empirical technique, called SEPA, for approximate p-value estimation based on statistically large number of observations over randomly generated sequences. Our empirical studies show that the technique remains effective in identifying biological correlations even in sequen es of low similarities and large expected gaps, and the experimental results shown here point to many interesting insights and features.",
author = "Ofer Gill and Bud Mishra",
year = "2006",
doi = "10.1007/11758525_87",
language = "English (US)",
isbn = "3540343814",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "638--645",
booktitle = "Computational Science - ICCS 2006",
note = "ICCS 2006: 6th International Conference on Computational Science ; Conference date: 28-05-2006 Through 31-05-2006",
}