Linked Life Data

17094243

Source:http://linkedlifedata.com/resource/pubmed/id/17094243

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2006-11-10
pubmed:abstractText
A new peak picking algorithm for the analysis of mass spectrometric (MS) data is presented. It is independent of the underlying machine or ionization method, and is able to resolve highly convoluted and asymmetric signals. The method uses the multiscale nature of spectrometric data by first detecting the mass peaks in the wavelet-transformed signal before a given asymmetric peak function is fitted to the raw data. In an optional third stage, the resulting fit can be further improved using techniques from nonlinear optimization. In contrast to currently established techniques (e.g. SNAP, Apex) our algorithm is able to separate overlapping peaks of multiply charged peptides in ESI-MS data of low resolution. Its improved accuracy with respect to peak positions makes it a valuable preprocessing method for MS-based identification and quantification experiments. The method has been validated on a number of different annotated test cases, where it compares favorably in both runtime and accuracy with currently established techniques. An implementation of the algorithm is freely available in our open source framework OpenMS.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1793-5091
pubmed:author
pubmed:issnType
Print
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
243-54
pubmed:dateRevised
2007-9-12
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
High-accuracy peak picking of proteomics data using wavelet techniques.
pubmed:affiliation
Institute of Computer Science, Free University of Berlin Takustr. 9, 14195 Berlin, Germany. lange@inf.fu-berlin.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't