Applications of Computational Intelligence in Biology (Studies in Computational Intelligence, #122)
Computational Intelligence (CI) has been a tremendously active area of - search for the past decade or so. There are many successful applications of CI in many sub elds of biology, including bioinformatics, computational - nomics, protein structure prediction, or neuronal systems modeling and an- ysis. However, there still are many open problems in biology that are in d- perate need of advanced and e cient computational methodologies to deal with tremendous amounts of data that those problems ar...
Data Mining and Applications in Genomics (Lecture Notes in Electrical Engineering, #25)
by Sio-Iong Ao
Essential Fish Habitat Mapping in the Mediterranean (Developments in Hydrobiology, #203)
Proper designation of Essential Fish Habitat (EFH) is a highly important spatial measure in any management of fishery resources. EFH is defined as those waters and substrates necessary to fish for spawning, breeding, feeding, or growth to maturity, a definition that includes the physical, chemical and biological properties of marine areas and the associated sediment and biological assemblages that sustain fish populations throughout their full life cycle. This book presents latest advances in EF...
Evolutionary Computation in Combinatorial Optimization (Lecture Notes in Computer Science, #4446)
by Carlos Cotta and Jano Van Hemert
This book constitutes the refereed proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2009, held in Tubingen, Germany, in April 2009. The 21 revised full papers presented were carefully reviewed and selected from 53 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various ind...
Recent decades have witnessed the thriving development of new mathematical, computational and theoretical approaches, such as bioinformatics and neuroinformatics, to tackle fundamental issues in biology. These approaches focus no longer on individual units, such as nerve cells or genes, but rather on dynamic patterns of interactions between them. This volume explores the concept in full, featuring contributions from a global group of contributors, many of whom are pre-eminent in their field.
Foundations of Learning Classifier Systems (Studies in Fuzziness and Soft Computing, #183)
This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computation) tailored for a classifier systems audience and written by acknowledged authorities in their area - as well as a relevant historical original work by John Holland.
Algorithms in Bioinformatics (Lecture Notes in Computer Science, #2149)
We are very pleased to present the proceedings of the First Workshop on Bio- formatics (WABI 2001), which took place in Aarhus on August 28{31, 2001, under the auspices of the European Association for Theoretical Computer S- ence (EATCS) and the Danish Center for Basic Research in Computer Science (BRICS). TheWorkshop onAlgorithmsinBioinformatics coversresearch onallaspects of algorithmic work in bioinformatics. The emphasis is on discrete algorithms that address important problems in molecular...
Systems Biology of Bacteria (Methods in Microbiology)
by Anil Wipat
Focusing on the systems biology of bacteria and microorganisms, the 39th volume of Methods in Microbiology investigates the interface between molecular biology, bioinformatics, and modelling and predicting behavior. This cutting-edge research area is of extreme importance to the field and is developing quickly.
Numerical Computer Methods (Methods in Enzymology)
by Michael L Johnson and Ludwig Brand
The aim of Numerical Computer Methods, Part D is to brief researchers of the importance of data analysis in enzymology, and of the modern methods that have developed concomitantly with computer hardware. It is also to validate researchers' computer programs with real and synthetic data to ascertain that the results produced are what they expected.
Computational Methods for Next Generation Sequencing Data Analysis (Wiley Series in Bioinformatics)
by Ion Mandoiu and Alexander Zelikovsky
Introduces readers to core algorithmic techniques for next-generation sequencing (NGS) data analysis and discusses a wide range of computational techniques and applications This book provides an in-depth survey of some of the recent developments in NGS and discusses mathematical and computational challenges in various application areas of NGS technologies. The 18 chapters featured in this book have been authored by bioinformatics experts and represent the latest work in leading labs actively con...
Bioinformatics (Morgan Kaufmann Series in Multimedia Information and Systems)
Life science data integration and interoperability is one of the most challenging problems facing bioinformatics today. In the current age of the life sciences, investigators have to interpret many types of information from a variety of sources: lab instruments, public databases, gene expression profiles, raw sequence traces, single nucleotide polymorphisms, chemical screening data, proteomic data, putative metabolic pathway models, and many others. Unfortunately, scientists are not currently a...
Quick Guideline for Computational Drug Design
by A Hammad Mirza, Rana Adnan Tahir, and Asif Mir
Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you've...
Bioinformatics in Proteomics (Methods in Molecular Biology)
Genomics of GC Rich Gram-Positive Bacteria (Functional genomics)
Introduction to Theoretical Population Genetics (Biomathematics, #21)
by Thomas Nagylaki
This book covers those areas of theoretical population genetics that can be investigated rigorously by elementary mathematical methods. I have tried to formulate the various models fairly generally and to state the biological as sumptions quite explicitly. I hope the choice and treatment of topics will en able the reader to understand and evaluate detailed analyses of many specific models and applications in the literature. Models in population genetics are highly idealized, often even over i...
Artificial Intelligence in Medicine (Lecture Notes in Computer Science, #934)
Combinatorial Pattern Matching (Theoretical Computer Science and General Issues, #4009)
This book constitutes the refereed proceedings of the 17th Annual Symposium on Combinatorial Pattern Matching, CPM 2006, held in Barcelona, Spain, July 2006. The book presents 33 revised full papers together with 3 invited talks, organized in topical sections on data structures, indexing data structures, probabilistic and algebraic techniques, applications in molecular biology, string matching, data compression, and dynamic programming.