NNAlign: A Web-Based Prediction Method Allowing Non-Expert End-User Discovery of Sequence Motifs in Quantitative Peptide Data

Open Access

Peer-reviewed

Research Article

Massimo Andreatta ,

* E-mail: massimo@cbs.dtu.dk

Affiliation Center for Biological Sequence Analysis, Technical University of Denmark, Kongens Lyngby, Denmark
⨯
Claus Schafer-Nielsen,

Affiliation Schafer-N, Copenhagen, Denmark
⨯
Ole Lund,

Affiliation Center for Biological Sequence Analysis, Technical University of Denmark, Kongens Lyngby, Denmark
⨯
Søren Buus,

Affiliation Laboratory of Experimental Immunology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
⨯
Morten Nielsen

Affiliation Center for Biological Sequence Analysis, Technical University of Denmark, Kongens Lyngby, Denmark
⨯

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Sequence motif analysis
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Network motifs
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Major histocompatibility complex
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Microarrays
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Sequence alignment
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Artificial neural networks
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Forecasting
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Protein sequencing
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