Multivariate Statistical Analysis Of Protein Variation: Protein Sequence Metric Solution And Applications

Zhao, Jieping; Zhao, Jieping

ISBN 10: 3639202864 / ISBN 13: 9783639202861

Editore: Vdm Verlag Dr. Müller, 2009

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100 pages. 8.66x5.91x0.23 inches. In Stock.

Codice articolo __3639202864

Dati bibliografici

• Titolo: Multivariate Statistical Analysis Of Protein Variation: Protein Sequence Metric Solution And Applications
• Editore: Vdm Verlag Dr. Müller
• Data di pubblicazione: 2009
• Lingua: Inglese
• ISBN 10: 3639202864
• ISBN 13: 9783639202861
• Rilegatura: Paperback
• Condizione: Brand New

Descrizione articolo

Riassunto

Sequence metric problem is caused by the alphabetic coding of amino acids and is a major hindrance to protein sequence analysis. This book studied protein sequence metric problem solution and applied it to explore the structural, functional and evolutionary aspects of basic helix-loop- helix(bHLH)protein family. The book revisited sequence metric problem solution by [Atchley et al 2005]. Some of the unsolved issues were studied. Next, the book focused on statistical studies of the bHLH protein family using the metric solution. Next, protein sequence variability in the level of clades was studied using multivariate statistics. Important discriminant sites for the clades were selected and hierarchical classification strategies for the clades were proposed. Lastly, Arabidopsis bHLH proteins were studied by a series of multivariate analyses. Results showed that there were significant sequence differences between plant and animal bHLH proteins. Contributing discriminant sites were selected and discussed. Binding property of each of the Arabidopsis bHLH proteins was assigned by using the classification rules derived from animal bHLH proteins.

L'autore

Jieping Zhao, BS in biology, Nanjing University, China, 1997. MS in molecular genetics, Chinese Academy of Sciences, 2000. PhD in bioinformatics, North Carolina State University, 2006 Postdoc fellow, Medical College of Georgia, 2007- current. Literature mining based molecular interaction network construction and analysis.