Statistics and Informatics in Molecular Cancer Research
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Molecular understanding of cancer and cancer progression is at the forefront of many research programs today, and high-throughput array technologies and other modern molecular techniques produce a wealth of molecular data about the stucture, organization, and function of cells, tissues and organisms. Complex mathematical, statistical and bioinformatics tools are required to extract, handle and process data and this book, edited by two leading researchers with contributions from carefully chosen experts, makes these tools available to a wide range of researchers, in a single coherent book volume.…mehr

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Produktbeschreibung
Molecular understanding of cancer and cancer progression is at the forefront of many research programs today, and high-throughput array technologies and other modern molecular techniques produce a wealth of molecular data about the stucture, organization, and function of cells, tissues and organisms. Complex mathematical, statistical and bioinformatics tools are required to extract, handle and process data and this book, edited by two leading researchers with contributions from carefully chosen experts, makes these tools available to a wide range of researchers, in a single coherent book volume.
Autorenporträt
Carsten Wiuf obtained his PhD in mathematical biology from the University of Aarhus in 1998. Afterwards he spent 4 years in Oxford at the Department of Statistics before joining a biotech company in Boston. In 2003 he became Professor of Bioinformatics at the University of Aarhus. He has co-authored the book Gene Genealogies, Variation and Evolution (OUP). Claus L. Andersen earned his PhD in cancer biology from the University of Aarhus in 2002. In 2002 he became an assistant professor at the University of Aarhus and later in 2005 an associated professor. Today he is heading the colorectal cancer research group at the Molecular Diagnostic Laboratory, Aarhus University Hospital. Both have worked on informatics approaches to the analysis of molecular cancer data and have practical as well as theoretical experience with development of bioinformatics and statistical methods for analysis of molecular data.