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Andrzej Polanski

Bioinformatics

Ebook (PDF Format)

This textbook presents mathematical models in bioinformatics and describes biological problems that inspire the computer science tools used to manage the enormous data sets involved. The first part of the book covers mathematical and computational methods, with practical applications presented in the second part. The mathematical presentation avoids unnecessary formalism, while remaining clear and precise. The book closes with a thorough bibliography, reaching from classic research results to very recent findings. This volume is suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on mathematical and com… Mehr

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Produktdetails


Weitere Autoren: Kimmel, Marek
  • ISBN: 978-3-540-69022-1
  • EAN: 9783540690221
  • Produktnummer: 33304220
  • Verlag: Springer-Verlag GmbH
  • Sprache: Englisch
  • Erscheinungsjahr: 2007
  • Seitenangabe: 376 S.
  • Plattform: PDF
  • Masse: 4'729 KB
  • Auflage: 2007
  • Abbildungen: 4 schwarz-weiße Tabellen, Bibliographie

Über den Autor


Andrzej Polanski is Professor at the Silesian University of Technology. Prior to this, he worked as a Post Doctoral Fellow at the University of Texas, Human Genetics Center, Houston USA (1996-1997) ans as a Visiting Professor at Rice University, Houston USA (2001-2003). His research interests are in bioinformatics, biomedical modeling and control, modern control and optimization theory. Marek Kimmel, Ph.D., is a Professor of Statistics at Rice University in Houston, TX, Professor in Department of Automatic Control, Silesian University of Technology in Gliwice, Poland, Professor of Biostatistics and Applied Mathematics (adj.) at M.D. Anderson Cancer Center in Houston, and a Professor of Biometry (adj.) at the School of Public Health of the University of Texas in Houston. He is heading the Rice Bioinformatics Group as well as the doctoral program in Statistical Genetics and Bioinformatics. Dr. Kimmel is a Fellow of the American Statistical Association. His principal interests are stochastic modeling of human disease (in particular lung cancer progression and screening), statistical and population genetics, biostatistics and bioinformatics.

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