Books in Mathematical biosciences

Computer Methods, Part C

1st Edition
Volume 487
December 24, 2010
Melvin I. Simon
English
Hardback
9 7 8 0 1 2 3 8 1 2 7 0 4
eBook
9 7 8 0 1 2 3 8 1 2 7 1 1

The combination of faster, more advanced computers and more quantitatively oriented biomedical researchers has recently yielded new and more precise methods for the analysis of biomedical data. These better analyses have enhanced the conclusions that can be drawn from biomedical data, and they have changed the way that experiments are designed and performed. This volume, along with the 2 previous Computer Methods volumes for the Methods in Enzymology serial, aims to inform biomedical researchers about recent applications of modern data analysis and simulation methods as applied to biomedical research.

Computer Methods Part B

1st Edition
Volume 467
November 5, 2009
Michael L. Johnson + 1 more
English
Hardback
9 7 8 0 1 2 3 7 5 0 2 3 5
eBook
9 7 8 0 0 8 0 9 6 2 8 0 1

The combination of faster, more advanced computers and more quantitatively oriented biomedical researchers has recently yielded new and more precise methods for the analysis of biomedical data. These better analyses have enhanced the conclusions that can be drawn from biomedical data, and they have changed the way that experiments are designed and performed. This volume, along with previous and forthcoming Computer Methods volumes for the Methods in Enzymology serial, aims to inform biomedical researchers about recent applications of modern data analysis and simulation methods as applied to biomedical research.

Probabilistic Methods for Bioinformatics

1st Edition
April 3, 2009
Richard E. Neapolitan
English
Hardback
9 7 8 0 1 2 3 7 0 4 7 6 4
eBook
9 7 8 0 0 8 0 9 1 9 3 6 2

The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis.

In Silico

1st Edition
June 16, 2008
Jason Sharpe + 2 more
English
eBook
9 7 8 0 0 8 0 8 7 9 2 5 3

In Silico introduces Maya programming into one of the most fascinating application areas of 3D graphics: biological visualization. In five building-block tutorials, this book prepares animators to work with visualization problems in cell biology. The book assumes no deep knowledge of cell biology or 3D graphics programming. An accompanying DVD-ROM includes code derived from the tutorials, the working Maya computer files, and sample animated movies.

Systems Biology

1st Edition
March 20, 2007
Fred Boogerd + 3 more
English
Hardback
9 7 8 0 4 4 4 5 2 0 8 5 2
eBook
9 7 8 0 0 8 0 4 7 5 2 7 1

Systems biology is a vigorous and expanding discipline, in many ways a successor to genomics and perhaps unprecedented in its combination of biology with a great many other sciences, from physics to ecology, from mathematics to medicine, and from philosophy to chemistry. Studying the philosophical foundations of systems biology may resolve a longer standing issue, i.e., the extent to which Biology is entitled to its own scientific foundations rather than being dominated by existing philosophies.

Biostatistics

2nd Edition
December 14, 2006
Ronald N. Forthofer + 2 more
English
Hardback
9 7 8 0 1 2 3 6 9 4 9 2 8
eBook
9 7 8 0 0 8 0 4 6 7 7 2 6

Biostatistics, Second Edition, is a user-friendly guide on biostatistics, which focuses on the proper use and interpretation of statistical methods. This textbook does not require extensive background in mathematics, making it user-friendly for all students in the public health sciences field. Instead of highlighting derivations of formulas, the authors provide rationales for the formulas, allowing students to grasp a better understanding of the link between biology and statistics. The material on life tables and survival analysis allows students to better understand the recent literature in the health field, particularly in the study of chronic disease treatment. This updated edition contains over 40% new material with modern real-life examples, exercises, and references, including new chapters on Logistic Regression, Analysis of Survey Data, and Study Designs. The book is recommended for students in the health sciences, public health professionals, and practitioners.

Related subjects

Computational biology

Theoretical biology

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health