Please use this identifier to cite or link to this item: https://doi.org/10.1039/c0an00778a
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dc.titleA fully automated iterative moving averaging (AIMA) technique for baseline correction
dc.contributor.authorPrakash, B.D.
dc.contributor.authorWei, Y.C.
dc.date.accessioned2014-10-29T01:47:21Z
dc.date.available2014-10-29T01:47:21Z
dc.date.issued2011-08-07
dc.identifier.citationPrakash, B.D., Wei, Y.C. (2011-08-07). A fully automated iterative moving averaging (AIMA) technique for baseline correction. Analyst 136 (15) : 3130-3135. ScholarBank@NUS Repository. https://doi.org/10.1039/c0an00778a
dc.identifier.issn00032654
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105564
dc.description.abstractBaseline correction is one of the pre-processing steps in the analysis of metabolite signals from chemometric analytical instruments. Fully automated baseline correction techniques, although more convenient to use, tend to be less accurate than semi-automated baseline correction. A fully automated baseline correction algorithm, the automated iterative moving averaging algorithm (AIMA), is presented and compared with three recently introduced semi-automated algorithms, namely the adaptive iteratively reweighted penalized least squares (airPLS), Asymmetric Least Squares baseline correction (ALS) and a parametric method, using NMR, Raman and HPLC chromatograms. AIMA's potential in increasing the accuracy of multivariate analysis via SELTI-TOF and LCMS chromatograms was also assessed. The results show that the AIMA's accuracy is comparable to these semi-automated algorithms and has the advantage of ease of use. An AIMA plug-in for an open source metabolomics analysis tool, MZmine, was also developed. The AIMA plug-in is available at http://padel.nus.edu.sg/software/padelaima. © The Royal Society of Chemistry 2011.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1039/c0an00778a
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentPHARMACY
dc.description.doi10.1039/c0an00778a
dc.description.sourcetitleAnalyst
dc.description.volume136
dc.description.issue15
dc.description.page3130-3135
dc.description.codenANALA
dc.identifier.isiut000292972200013
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