Output details
11 - Computer Science and Informatics
University of Exeter
Article title
An Ultra-Fast Metabolite Prediction Algorithm
Type
D - Journal article
Title of journal
PLoS ONE
Article number
-
Volume number
7
Issue number
6
First page of article
e39158
ISSN of journal
1932-6203
Year of publication
2012
URL
-
Number of additional authors
1
Additional information
<28> Metabolite data are often very noisy, which makes aligning multiple profiles to generate metabolites and map them to compounds difficult. Nearly all the existing algorithms failed to provide robust and accurate alignments, and some are extremely slow. This paper introduces for the first time the use of divide and conquer recursion ideas to align multiple metabolite profiles. The accuracy is nearly one order of magnitude higher than existing algorithms and the speed is also more than one order of magnitude faster. I designed, implemented and tested the algorithm and wrote the paper.
Interdisciplinary
-
Cross-referral requested
-
Research group
1 - Artificial Intelligence
Citation count
1
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-