| Titre : |
Statistical bioinformatics with R |
| Type de document : |
texte imprimé |
| Auteurs : |
Sunil Mathur, Auteur |
| Editeur : |
New York : Academic press |
| Année de publication : |
2010 |
| Autre Editeur : |
Amsterdam : Elsevier |
| Importance : |
XVI, 319 p. |
| Présentation : |
ill. |
| Format : |
25 cm |
| ISBN/ISSN/EAN : |
978-0-12-375104-1 |
| Note générale : |
Bibliogr. p. 305-314. - Index |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Bioinformatique -- Méthodes statistiques
R (logiciel)
Bioinformatics -- Statistical methods
R (Computer program language) |
| Index. décimale : |
57.087.1 Etude et traitement statistique de données biologiques |
| Résumé : |
Designed for a one or two semester bioinformatics course at the senior undergraduate or graduate level, this book takes a broad view of bioinformatics—not just gene expression and not just sequence analysis.
A careful balance of statistical theory in the context of bioinformatics applications, including the development of advanced methodology such as Bayesian and Markov models provides students with the underlying foundation needed to conduct bioinformatics.
A wide variety of applications in different biomedical and genomic areas, including the identification of differentially expressed genes, sequence analysis, location of recombinant breakpoints, complex designs, and gene clustering, are included.
Statisticians interested in bioinformatics and applied science researchers interested in finding solutions to high-dimensional problems in their fields will find this an essential reference.
The inclusion of R code is unique and a real advantage to graduate students and beginning researchers.
Prerequisite knowledge includes one semester of calculus and an introduction to statistics course. |
| Note de contenu : |
Summary :
1.Introduction
2.Microarrays
3.Probability and Statistical Theory
4.Special Distributions Properties and Applications
5.Statistical Inference and Applications
6.Nonparametric Statistics
7.Bayesian Statistics
8.Markov Chain Monte Carlo
9.Analysis of Variance
10.The Design of Experiments
11.Multiple Testing of Hypotheses |
| En ligne : |
http://books.google.dz/books/about/Statistical_Bioinformatics.html?id=wbJo7L_8CQ [...] |
Statistical bioinformatics with R [texte imprimé] / Sunil Mathur, Auteur . - New York : Academic press : Amsterdam : Elsevier, 2010 . - XVI, 319 p. : ill. ; 25 cm. ISBN : 978-0-12-375104-1 Bibliogr. p. 305-314. - Index Langues : Anglais ( eng)
| Mots-clés : |
Bioinformatique -- Méthodes statistiques
R (logiciel)
Bioinformatics -- Statistical methods
R (Computer program language) |
| Index. décimale : |
57.087.1 Etude et traitement statistique de données biologiques |
| Résumé : |
Designed for a one or two semester bioinformatics course at the senior undergraduate or graduate level, this book takes a broad view of bioinformatics—not just gene expression and not just sequence analysis.
A careful balance of statistical theory in the context of bioinformatics applications, including the development of advanced methodology such as Bayesian and Markov models provides students with the underlying foundation needed to conduct bioinformatics.
A wide variety of applications in different biomedical and genomic areas, including the identification of differentially expressed genes, sequence analysis, location of recombinant breakpoints, complex designs, and gene clustering, are included.
Statisticians interested in bioinformatics and applied science researchers interested in finding solutions to high-dimensional problems in their fields will find this an essential reference.
The inclusion of R code is unique and a real advantage to graduate students and beginning researchers.
Prerequisite knowledge includes one semester of calculus and an introduction to statistics course. |
| Note de contenu : |
Summary :
1.Introduction
2.Microarrays
3.Probability and Statistical Theory
4.Special Distributions Properties and Applications
5.Statistical Inference and Applications
6.Nonparametric Statistics
7.Bayesian Statistics
8.Markov Chain Monte Carlo
9.Analysis of Variance
10.The Design of Experiments
11.Multiple Testing of Hypotheses |
| En ligne : |
http://books.google.dz/books/about/Statistical_Bioinformatics.html?id=wbJo7L_8CQ [...] |
|  |
57.01 Fondements. Lois générales. Aspects théoriques. Caractéristiques et propriétés des être vivants.
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