| 000 | 02471nam a22003738i 4500 | ||
|---|---|---|---|
| 001 | CR9780511584589 | ||
| 003 | UkCbUP | ||
| 005 | 20200124160244.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 090612s2006||||enk o ||1 0|eng|d | ||
| 020 | _a9780511584589 (ebook) | ||
| 020 | _z9780521860925 (hardback) | ||
| 020 | _z9781107636989 (paperback) | ||
| 040 |
_aUkCbUP _beng _erda _cUkCbUP |
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| 050 | 0 | 0 |
_aQH450 _b.B39 2006 |
| 082 | 0 | 0 |
_a572.8/6501519542 _222 |
| 245 | 0 | 0 |
_aBayesian inference for gene expression and proteomics / _cedited by Kim-Anh Do, Peter Müller, Marina Vannucci. |
| 246 | 3 | _aBayesian Inference for Gene Expression & Proteomics | |
| 264 | 1 |
_aCambridge : _bCambridge University Press, _c2006. |
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| 300 |
_a1 online resource (xviii, 437 pages) : _bdigital, PDF file(s). |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 500 | _aTitle from publisher's bibliographic system (viewed on 05 Oct 2015). | ||
| 520 | _aThe interdisciplinary nature of bioinformatics presents a research challenge in integrating concepts, methods, software and multiplatform data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high-throughput data, such as proteomic profiles that arise from mass spectrometry experiments. This book discusses the development and application of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as molecular and structural biology. The Bayesian approach has the advantage that evidence can be easily and flexibly incorporated into statistical methods. A basic overview of the biological and technical principles behind multi-platform high-throughput experimentation is followed by expert reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discovery and regulatory networks, and Bayesian networks and gene interactions. | ||
| 650 | 0 |
_aGene expression _xStatistical methods. |
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| 650 | 0 |
_aProteomics _xStatistical methods. |
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| 700 | 1 |
_aDo, Kim-Anh, _d1960- _eeditor. |
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| 700 | 1 |
_aMüller, Peter, _d1963 August 9- _eeditor. |
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| 700 | 1 |
_aVannucci, Marina, _d1966- _eeditor. |
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| 776 | 0 | 8 |
_iPrint version: _z9780521860925 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1017/CBO9780511584589 |
| 999 |
_c518834 _d518832 |
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