Algebraic And Combinatorial Computational Biology

Algebraic and Combinatorial Computational Biology introduces students and researchers to a panorama of powerful and current methods for mathematical problem-solving in modern computational biology. Presented in a modular format, each topic introduces the biological foundations of the field, covers specialized mathematical theory, and concludes by highlighting connections with ongoing research, particularly open questions. The work addresses problems from gene regulation, neuroscience, phylogenetics, molecular networks, assembly and folding of biomolecular structures, and the use of clustering methods in biology. A number of these chapters are surveys of new topics that have not been previously compiled into one unified source. These topics were selected because they highlight the use of technique from algebra and combinatorics that are becoming mainstream in the life sciences. - Integrates a comprehensive selection of tools from computational biology into educational or research programs - Emphasizes practical problem-solving through multiple exercises, projects and spinoff computational simulations - Contains scalable material for use in undergraduate and graduate-level classes and research projects - Introduces the reader to freely-available professional software - Supported by illustrative datasets and adaptable computer code

This book, first published in 2005, offers an introduction to the application of algebraic statistics to computational biology.

Algebraic statistics is the study of the algebraic varieties that correspond to discrete statistical models. Such statistical models are used throughout computational biology, for example to describe the evolution of DNA sequences. This perspective on statistics allows us to bring mathematical techniques to bear and also provides a source of new problems in mathematics.

This book constitutes the refereed proceedings of the Third International Conference on Algebraic Biology, AB 2008, held at the Castle of Hagenberg, Austria in July 2008 as part of the RISC Summer 2008, organized by the Research Institute for Symbolic Computation. The 14 revised full papers presented together with 3 tutorial lectures were carefully reviewed and selected from 27 submissions. The conference is the interdisciplinary forum for the presentation of research on all aspects of applications of symbolic computation (computer algebra, computational logic, and related methods) to various issues in biology and life sciences as well as other problems in biology being approached with symbolic methods.

There has been considerable interest recently in the subject of patterns in permutations and words, a new branch of combinatorics with its roots in the works of Rotem, Rogers, and Knuth in the 1970s. Consideration of the patterns in question has been extremely interesting from the combinatorial point of view, and it has proved to be a useful language in a variety of seemingly unrelated problems, including the theory of Kazhdan—Lusztig polynomials, singularities of Schubert varieties, interval orders, Chebyshev polynomials, models in statistical mechanics, and various sorting algorithms, including sorting stacks and sortable permutations. The author collects the main results in the field in this up-to-date, comprehensive reference volume. He highlights significant achievements in the area, and points to research directions and open problems. The book will be of interest to researchers and graduate students in theoretical computer science and mathematics, in particular those working in algebraic combinatorics and combinatorics on words. It will also be of interest to specialists in other branches of mathematics, theoretical physics, and computational biology. The author collects the main results in the field in this up-to-date, comprehensive reference volume. He highlights significant achievements in the area, and points to research directions and open problems. The book will be of interest to researchers and graduate students in theoretical computer science and mathematics, in particular those working in algebraic combinatorics and combinatorics on words. It will also be of interest to specialists in other branches of mathematics, theoretical physics, and computational biology.

Emphasizing the search for patterns within and between biological sequences, trees, and graphs, Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R shows how combinatorial pattern matching algorithms can solve computational biology problems that arise in the analysis of genomic, transcriptomic, proteomic, metabolomic

This volume constitutes the refereed proceedings of the Second International Conference on Algebraic Biology. The conference served as an interdisciplinary forum for the presentation of research on all aspects of the application of symbolic computation in biology, including computer algebra, computational logic, and related methods. Papers also examine solutions to problems in biology using symbolic methods.

Historically, mathematics, probability, and statistics have been widely used in the biological sciences. Recent progress in genomics has yielded many millions of gene sequences. But what do these sequences tell us and what are the generalities and rules governed by them? It seems that we understand very little about the genetic contexts required to 'read' them. There is more to life than the genomic blueprint of each organism. Life functions within the natural laws that we know and the ones we do not know. The development of modern mathematical natural sciences is based on the use of certain mathematical tools. Mathematics can be used to understand life from the molecular to the biosphere level.This book provides the foundation and latest advances for an emerging research area that uses tools from symbolic computation, computer algebra and logic, algebraic geometry, fractal geometry, probability and statistics, and matrix algebra to formalize and solve biological problems and explore its applications in algebraic biology and code biology. It introduces highly interdisciplinary topics in biomathematics such as matrix genetics, gestalt biology, bio-antenna arrays, resonance genetics, quantum biology, and more.