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- 2009024890 contributor B11422689.
- 2009024890 created "c2010.".
- 2009024890 date "2010".
- 2009024890 date "c2010.".
- 2009024890 dateCopyrighted "c2010.".
- 2009024890 description "Includes bibliographical references and index.".
- 2009024890 description "Road to statistical bioinformatics -- Probability concepts and distributions for analyzing large biological data -- Quality control of high-throughput biological data -- Statistical testing and significance for large biological data analysis -- Clustering : unsupervised learning in large biological data -- Classification : supervised learning with high-dimensional biological data -- Multidimensional analysis and visualization on large biological data -- Statistical models, inference, and algorithms for large biological data analysis -- Experimental designs on high-throughput biological experiments -- Statistical resampling techniques for large biological data analysis -- Statistical network analysis for biological systems and pathways -- Trends and statistical challenges in genomewide association studies -- R and bioconductor packages in bioinformatics : towards systems biology.".
- 2009024890 extent "xiv, 350 p., [20] p. of plates :".
- 2009024890 identifier "0471692727 (cloth)".
- 2009024890 identifier "9780471692720 (cloth)".
- 2009024890 issued "2010".
- 2009024890 issued "c2010.".
- 2009024890 language "eng".
- 2009024890 publisher "Hoboken, N.J. : Wiley-Blackwell,".
- 2009024890 subject "2010 D-464".
- 2009024890 subject "570.285 22".
- 2009024890 subject "Bioinformatics Statistical methods.".
- 2009024890 subject "Biostatistics methods.".
- 2009024890 subject "Computational Biology methods.".
- 2009024890 subject "QH324.2 .S725 2010".
- 2009024890 tableOfContents "Road to statistical bioinformatics -- Probability concepts and distributions for analyzing large biological data -- Quality control of high-throughput biological data -- Statistical testing and significance for large biological data analysis -- Clustering : unsupervised learning in large biological data -- Classification : supervised learning with high-dimensional biological data -- Multidimensional analysis and visualization on large biological data -- Statistical models, inference, and algorithms for large biological data analysis -- Experimental designs on high-throughput biological experiments -- Statistical resampling techniques for large biological data analysis -- Statistical network analysis for biological systems and pathways -- Trends and statistical challenges in genomewide association studies -- R and bioconductor packages in bioinformatics : towards systems biology.".
- 2009024890 title "Statistical bioinformatics : a guide for life and biomedical science researchers / edited by Jae K. Lee.".
- 2009024890 type "text".