ENGINEERING - Cambridge University Press India

Primer of Genetic
Analysis
A Problems Approach
James N. Thompson Jr.
University of Oklahoma
Jenna J. Hellack
University of Oklahoma
Gerald Braver
University of Oklahoma
& David S. Durica
University of Oklahoma
successfully plan their own experiments and
examine the results obtained.
Contents: 1. General principles; 2. Cell culture
techniques; 3. Centrifugation 4. Microscopy;
5. Molecular biology, bioformatics and basic
techniques; 6. Recombinant DNA and genetic
analysis; 7. Immunological techniques; 8. Protein
structure, purification, characterisation and
functional analysis; 9. Mass spectrometric
techniques; 10. Electrophoretic techniques;
11. Chromatographic techniques;
12. Spectroscopic techniques I; 13. Spectroscopic
techniques II; 14. Radioisotope techniques;
15. Enzymes; 16. Principles of clinical
biochemistry; 17. Cell membrane receptors;
18. Drug discovery and development.
ISBN: 9780521178747 760pp ` 545.00
An invaluable student-tested study aid, this primer
provides guided instruction for the analysis and
interpretation of genetic principles and practice in
problem solving. Each section is introduced with a
summary of useful hints for problem solving and
an overview of the topic with key terms. A series of
problems, generally progressing from simple to
more complex, then allows students to test their
understanding of the material. Each question and
answer is accompanied by detailed explanation.
This new edition includes additional problems in
basic areas that often challenge students,
extended coverage in molecular biology and
development, an expanded glossary of terms, and
updated historical landmarks. Students at all
levels, from beginning biologists and premedical
students to graduates seeking a review of basic
genetics, will find this book a valuable aid. It will
complement the formal presentation in any
genetics textbook or stand alone as a self-paced
review manual.
Contents: 1. Overview of genetic organization
and scale; 2. Mitosis and meiosis; 3. Nucleic
acids: DNA and RNA; 4. Basic mendelian
genetics; 5. Probability and chi-square; 6. Sexlinkage
and gene interactions; 7. Pedigree
analysis; 8. Overview of basic statistical testing;
9. Quantitative inheritance; 10. Overview of
genetic mapping; 11. Assessing chromosome
linkage relationships; 12. Linkage and mapping in
diploids; 13. Mapping in bacteria and viruses;
14. Overview of types of genetic change;
15. Gene mutation; 16. Changes in chromosome
number and structure; 17. Protein synthesis and
the genetic code; 18. Gene regulation and
development; 19. Overview of molecular biology
techniques; 20. DNA mapping and human genome
analysis; 21. Basic population genetics;
22. Selection and evolution; 23. Practice tests;
24. Answers to practice tests and crossword
puzzles; 25. Landmarks in the history of genetics;
Glossary; Reference tables.
ISBN: 9780521603652 328pp $ 54.00
Methods for
Computational Gene
Prediction
William H. Majoros
Duke University,
North Carolina
Foundations of
Mathematical
Genetics
2nd Edition
Anthony W.F. Edwards
Gonville and Caius
College, Cambridge
Inferring the precise locations and splicing
patterns of genes in DNA is a difficult but important
task, with broad applications to biomedicine. The
mathematical and statistical techniques that have
been applied to this problem are surveyed and
organized into a logical framework based on the
theory of parsing. Both established approaches
and methods at the forefront of current research
are discussed. Numerous case studies of existing
software systems are provided, in addition to
detailed examples that work through the actual
implementation of effective gene-predictors using
hidden Markov models and other machinelearning
techniques. Background material on
probability theory, discrete mathematics, computer
science, and molecular biology is provided,
making the book accessible to students and
researchers from across the life and
computational sciences. This book is ideal for use
in a first course in bioinformatics at graduate or
advanced undergraduate level, and for anyone
wanting to keep pace with this rapidly-advancing
field.
Contents: Foreword; 1. Introduction;
2. Mathematical preliminaries; 3. Overview of
gene prediction; 4. Gene finder evaluation; 5. A toy
Exon finder; 6. Hidden Markov models; 7. Signal
and content sensors; 8. Generalized hidden
Markov models; 9. Comparative gene finding;
10. Machine Learning methods; 11. Tips and
tricks; 12. Advanced topics; Appendix - online
resources; References; Index.
ISBN: 9780521706940 448pp £ 33.00
In this second edition of the classic work
Foundations of Mathematical Genetics a definitive
account is given of the basic models of population
genetics, together with the historical origins of
developments since 1908. Existing texts in
mathematical population genetics have revealed
the need for a careful study of the foundations of
the field which have tended to be neglected in the
past. This book satisfies that need, treating the
simple deterministic models for random-mating
diploid populations in depth, though without
sacrificing clarity of expression. In the new edition,
coverage has been extended with the provision of
an extra chapter on the Fundamental Theorem of
Natural Selection. This book is written for those
interested in the mathematical aspects of
genetics, ecology and biology.
Contents: Preface to the second edition; Preface
to the first edition; 1. The genetic model; 2. Two
alleles at a single locus; 3. Two alleles using
homogeneous coordinates; 4. Many alleles at a
single locus; 5. The special case of three alleles;
6. An X-linked locus; 7. Miscellaneous single-locus
models; 8. Two diallelic loci; 9. Fisher’s
fundamental theorem; References; Index.
ISBN: 9780521775441 133pp £ 20.99
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