Multiple Sequence Alignments

This book is a practical guide for biologists who use multiple sequence alignments (MSAs) for their data analysis and are looking for a comprehensive overview of the many different programs. Despite their important role in data analysis, there is uncertainty among researchers about exactly how MSA programs work - not to mention how and why the different analyzes lead to different results. Which program is the right one for evaluating my data and how can I ensure that I have drawn all relevant findings from the alignments? This book offers helpful explanations and background information without requiring extensive bioinformatics knowledge and slowly introduces the reader to the topic.In the first part of the book, the possible fields of application as well as the formats that are usually produced by MSA programs are described in detail. The central algorithms as well as the internal processes of the most common MSA programs of the past and the present are also explained in an uncomplicated manner in greater detail. The second part of the book is a detailed, data-based comparison between MSA programs, which is intended to help you decide which program to use for your next alignment.

This book develops a new approach called parameter advising for finding a parameter setting for a sequence aligner that yields a quality alignment of a given set of input sequences. In this framework, a parameter advisor is a procedure that automatically chooses a parameter setting for the input, and has two main ingredients: (a) the set of parameter choices considered by the advisor, and (b) an estimator of alignment accuracy used to rank alignments produced by the aligner. On coupling a parameter advisor with an aligner, once the advisor is trained in a learning phase, the user simply inputs sequences to align, and receives an output alignment from the aligner, where the advisor has automatically selected the parameter setting. The chapters first lay out the foundations of parameter advising, and then cover applications and extensions of advising. The content • examines formulations of parameter advising and their computational complexity, • develops methods for learning good accuracy estimators, • presents approximation algorithms for finding good sets of parameter choices, and • assesses software implementations of advising that perform well on real biological data. Also explored are applications of parameter advising to • adaptive local realignment, where advising is performed on local regions of the sequences to automatically adapt to varying mutation rates, and • ensemble alignment, where advising is applied to an ensemble of aligners to effectively yield a new aligner of higher quality than the individual aligners in the ensemble. The book concludes by offering future directions in advising research.

Covers the fundamentals and techniques of multiple biological sequence alignment and analysis, and shows readers how to choose the appropriate sequence analysis tools for their tasks This book describes the traditional and modern approaches in biological sequence alignment and homology search. This book contains 11 chapters, with Chapter 1 providing basic information on biological sequences. Next, Chapter 2 contains fundamentals in pair-wise sequence alignment, while Chapters 3 and 4 examine popular existing quantitative models and practical clustering techniques that have been used in multiple sequence alignment. Chapter 5 describes, characterizes and relates many multiple sequence alignment models. Chapter 6 describes how traditionally phylogenetic trees have been constructed, and available sequence knowledge bases can be used to improve the accuracy of reconstructing phylogeny trees. Chapter 7 covers the latest methods developed to improve the run-time efficiency of multiple sequence alignment. Next, Chapter 8 covers several popular existing multiple sequence alignment server and services, and Chapter 9 examines several multiple sequence alignment techniques that have been developed to handle short sequences (reads) produced by the Next Generation Sequencing technique (NSG). Chapter 10 describes a Bioinformatics application using multiple sequence alignment of short reads or whole genomes as input. Lastly, Chapter 11 provides a review of RNA and protein secondary structure prediction using the evolution information inferred from multiple sequence alignments. • Covers the full spectrum of the field, from alignment algorithms to scoring methods, practical techniques, and alignment tools and their evaluations • Describes theories and developments of scoring functions and scoring matrices •Examines phylogeny estimation and large-scale homology search Multiple Biological Sequence Alignment: Scoring Functions, Algorithms and Applications is a reference for researchers, engineers, graduate and post-graduate students in bioinformatics, and system biology and molecular biologists. Ken Nguyen, PhD, is an associate professor at Clayton State University, GA, USA. He received his PhD, MSc and BSc degrees in computer science all from Georgia State University. His research interests are in databases, parallel and distribute computing and bioinformatics. He was a Molecular Basis of Disease fellow at Georgia State and is the recipient of the highest graduate honor at Georgia State, the William M. Suttles Graduate Fellowship. Xuan Guo, PhD, is a postdoctoral associate at Oak Ridge National Lab, USA. He received his PhD degree in computer science from Georgia State University in 2015. His research interests are in bioinformatics, machine leaning, and cloud computing. He is an editorial assistant of International Journal of Bioinformatics Research and Applications. Yi Pan, PhD, is a Regents' Professor of Computer Science and an Interim Associate Dean and Chair of Biology at Georgia State University. He received his BE and ME in computer engineering from Tsinghua University in China and his PhD in computer science from the University of Pittsburgh. Dr. Pan's research interests include parallel and distributed computing, optical networks, wireless networks and bioinformatics. He has published more than 180 journal papers with about 60 papers published in various IEEE/ACM journals. He is co-editor along with Albert Y. Zomaya of the Wiley Series in Bioinformatics.

From basic performing of sequence alignment through a proficiency at understanding how most industry-standard alignment algorithms achieve their results, Multiple Sequence Alignment Methods describes numerous algorithms and their nuances in chapters written by the experts who developed these algorithms. The various multiple sequence alignment algorithms presented in this handbook give a flavor of the broad range of choices available for multiple sequence alignment generation, and their diversity is a clear reflection of the complexity of the multiple sequence alignment problem and the amount of information that can be obtained from multiple sequence alignments. Each of these chapters not only describes the algorithm it covers but also presents instructions and tips on using their implementation, as is fitting with its inclusion in the highly successful Methods in Molecular Biology series. Authoritative and practical, Multiple Sequence Alignment Methods provides a readily available resource which will allow practitioners to experiment with different algorithms and find the particular algorithm that is of most use in their application.

Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, genes and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulae; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research.

This book is a practical guide for biologists who use multiple sequence alignments (MSAs) for their data analysis and are looking for a comprehensive overview of the many different programs. Despite their important role in data analysis, there is uncertainty among researchers about exactly how MSA programs work - not to mention how and why the different analyzes lead to different results. Which program is the right one for evaluating my data and how can I ensure that I have drawn all relevant findings from the alignments? This book offers helpful explanations and background information without requiring extensive bioinformatics knowledge and slowly introduces the reader to the topic.In the first part of the book, the possible fields of application as well as the formats that are usually produced by MSA programs are described in detail. The central algorithms as well as the internal processes of the most common MSA programs of the past and the present are also explained in an uncomplicated manner in greater detail. The second part of the book is a detailed, data-based comparison between MSA programs, which is intended to help you decide which program to use for your next alignment.

The sequencing of the human genome involved thousands of scientists but used relatively few tools. Obtaining sequences is simpler, but aligning the sequences remains a complicated but underappreciated aspect of comparative molecular biology. This book discusses the practice of alignment, and the procedures by which alignments are established.

Statistics for Bioinformatics: Methods for Multiple Sequence Alignment provides an in-depth introduction to the most widely used methods and software in the bioinformatics field. With the ever increasing flood of sequence information from genome sequencing projects, multiple sequence alignment has become one of the cornerstones of bioinformatics. Multiple sequence alignments are crucial for genome annotation, as well as the subsequent structural, functional, and evolutionary studies of genes and gene products. Consequently, there has been renewed interest in the development of novel multiple sequence alignment algorithms and more efficient programs. Explains the dynamics that animate health systems Explores tracks to build sustainable and equal architecture of health systems Examines the advantages and disadvantages of the different approaches to care integration and the management of health information