Biological Distance Analysis: Forensic and Bioarchaeological Perspectives synthesizes research within the realm of biological distance analysis, highlighting current work within the field and discussing future directions. The book is divided into three main sections. The first section clearly outlines datasets and methods within biological distance analysis, beginning with a brief history of the field and how it has progressed to its current state. The second section focuses on approaches using the individual within a forensic context, including ancestry estimation and case studies. The final section concentrates on population-based bioarchaeological approaches, providing key techniques and examples from archaeological samples. The volume also includes an appendix with additional resources available to those interested in biological distance analyses. Defines datasets and how they are used within biodistance analysis Applies methodology to individual and population studies Bridges the sub-fields of forensic anthropology and bioarchaeology Highlights current research and future directions of biological distance analysis Identifies statistical programs and datasets for use in biodistance analysis Contains cases studies and thorough index for those interested in biological distance analyses

Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

Distance measurements in biological systems by EPR The foundation for understanding function and dynamics of biological systems is knowledge of their structure. Many experimental methodologies are used for determination of structure, each with special utility. Volumes in this series on Biological Magnetic Resonance emphasize the methods that involve magnetic resonance. This volume seeks to provide a critical evaluation of EPR methods for determining the distances between two unpaired electrons. The editors invited the authors to make this a very practical book, with specific numerical examples of how experimental data is worked up to produce a distance estimate, and realistic assessments of uncertainties and of the range of applicability, along with examples of the power of the technique to answer biological problems. The first chapter is an overview, by two of the editors, of EPR methods to determine distances, with a focus on the range of applicability. The next chapter, also by the Batons, reviews what is known about electron spin relaxation times that are needed in estimating distances between spins or in selecting appropriate temperatures for particular experiments. Albert Beth and Eric Hustedt describe the information about spin-spin interaction that one can obtain by simulating CW EPR line shapes of nitroxyl radicals. The information in fluid solution CW EPR spectra of dual-spin labeled proteins is illustrated by Hassane Mchaourab and Eduardo Perozo.

In this book, the authors cover the basic methods and advances within distance sampling that are most valuable to practitioners and in ecology more broadly. This is the fourth book dedicated to distance sampling. In the decade since the last book published, there have been a number of new developments. The intervening years have also shown which advances are of most use. This self-contained book covers topics from the previous publications, while also including recent developments in method, software and application. Distance sampling refers to a suite of methods, including line and point transect sampling, in which animal density or abundance is estimated from a sample of distances to detected individuals. The book illustrates these methods through case studies; data sets and computer code are supplied to readers through the book’s accompanying website. Some of the case studies use the software Distance, while others use R code. The book is in three parts. The first part addresses basic methods, the design of surveys, distance sampling experiments, field methods and data issues. The second part develops a range of modelling approaches for distance sampling data. The third part describes variations in the basic method; discusses special issues that arise when sampling different taxa (songbirds, seabirds, cetaceans, primates, ungulates, butterflies, and plants); considers advances to deal with failures of the key assumptions; and provides a check-list for those conducting surveys.

Our environment and natural food resources are continually coming under threat so that the monitoring of population trends is essential today. Whaling is a good example. Here politics and conservation often clash, and over the years more and more restrictions have been applied through the efforts of the International Whaling Commission in an endeavour to save some of our whale species from extinction. Localized fisheries also need to be monitored and quotas set each year. In some countries, sports fishing and hunting are popular so that information is needed about the populations being exploited in order to determine such things as the duration of hunting season and bag limits. Methods of estimating animal abundance have been developing steadily since the 1940s but over the last 20 years activity in this area has intensified and of this growth were two the subject has begun to blossom. At the centre of the authors of this book, David Anderson and Kenneth Burnham, who have widely published in this field. The need for computers in this area was soon recognized and David and Ken were joined by Jeffrey Laake who, with his computing expertise, helped to develop suitable software packages for implementing some of the new techniques. In the 1980s Stephen Buckland entered the arena and began to make his presence felt. Among other contributions, he firmly established the role of Monte Carlo and bootstrapping techniques in population estimation where the unique role of the computer could be fully exploited.