November 24, 2020

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Bioinformatics Algorithms

Bioinformatics Algorithms
Author : Phillip Compeau,Pavel Pevzner
Publisher : Unknown
Release Date : 1986-06
Category :
Total pages :129
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Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Online Open Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed online course (http://coursera.org/course/bioinformatics), this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of biology and computer science students alike.Each chapter begins with a central biological question, such as "Are There Fragile Regions in the Human Genome?" or "Which DNA Patterns Play the Role of Molecular Clocks?" and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind (http://rosalind.info), an online platform for learning bioinformatics.The textbook website (http://bioinformaticsalgorithms.org) directs readers toward additional educational materials, including video lectures and PowerPoint slides.

An Introduction to Bioinformatics Algorithms

An Introduction to Bioinformatics Algorithms
Author : Neil C. Jones,Pavel A. Pevzner,Pavel Pevzner
Publisher : MIT Press
Release Date : 2004
Category : Computers
Total pages :435
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Algorithms and Complexity. Molecular Biology Primer. Exhaustive Search. Greedy Algorithms. Dynamic Programming Algorithms. Divide-and-Conquer Algorithms. Graph Algorithms. Combinatorial Pattern Matching. Clustering and Trees. Hidden Markov Models. Randomized Algorithms.

Bioinformatics Algorithms

Bioinformatics Algorithms
Author : Ion Mandoiu,Alexander Zelikovsky
Publisher : John Wiley & Sons
Release Date : 2008-02-15
Category : Computers
Total pages :520
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Presents algorithmic techniques for solving problems in bioinformatics, including applications that shed new light on molecular biology This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems in post-genomic molecular biology. Beginning with a thought-provoking discussion on the role of algorithms in twenty-first-century bioinformatics education, Bioinformatics Algorithms covers: General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fourier transform, seeding, and approximation algorithms Algorithms and tools for genome and sequence analysis, including formal and approximate models for gene clusters, advanced algorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motif finding Microarray design and analysis, including algorithms for microarray physical design, missing value imputation, and meta-analysis of gene expression data Algorithmic issues arising in the analysis of genetic variation across human population, including computational inference of haplotypes from genotype data and disease association search in case/control epidemiologic studies Algorithmic approaches in structural and systems biology, including topological and structural classification in biochemistry, and prediction of protein-protein and domain-domain interactions Each chapter begins with a self-contained introduction to a computational problem; continues with a brief review of the existing literature on the subject and an in-depth description of recent algorithmic and methodological developments; and concludes with a brief experimental study and a discussion of open research challenges. This clear and approachable presentation makes the book appropriate for researchers, practitioners, and graduate students alike.

Bioinformatics Algorithms

Bioinformatics Algorithms
Author : Miguel Rocha,Pedro G. Ferreira
Publisher : Academic Press
Release Date : 2018-06-08
Category : Technology & Engineering
Total pages :400
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Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important bioinformatics problems, putting forward the best algorithms and showing how to implement them. The book focuses on the use of the Python programming language and its algorithms, which is quickly becoming the most popular language in the bioinformatics field. Readers will find the tools they need to improve their knowledge and skills with regard to algorithm development and implementation, and will also uncover prototypes of bioinformatics applications that demonstrate the main principles underlying real world applications. Presents an ideal text for bioinformatics students with little to no knowledge of computer programming Based on over 12 years of pedagogical materials used by the authors in their own classrooms Features a companion website with downloadable codes and runnable examples (such as using Jupyter Notebooks) and exercises relating to the book

Bioinformatics Algorithms

Bioinformatics Algorithms
Author : Enno Ohlebusch
Publisher : Unknown
Release Date : 2013
Category : Algorithms
Total pages :604
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Algorithms in Bioinformatics

Algorithms in Bioinformatics
Author : Wing-Kin Sung
Publisher : CRC Press
Release Date : 2009-11-24
Category : Science
Total pages :407
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Thoroughly Describes Biological Applications, Computational Problems, and Various Algorithmic Solutions Developed from the author’s own teaching material, Algorithms in Bioinformatics: A Practical Introduction provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the biological motivation and precisely defines the corresponding computational problems. He also includes detailed examples to illustrate each algorithm and end-of-chapter exercises for students to familiarize themselves with the topics. Supplementary material is available at http://www.comp.nus.edu.sg/~ksung/algo_in_bioinfo/ This classroom-tested textbook begins with basic molecular biology concepts. It then describes ways to measure sequence similarity, presents simple applications of the suffix tree, and discusses the problem of searching sequence databases. After introducing methods for aligning multiple biological sequences and genomes, the text explores applications of the phylogenetic tree, methods for comparing phylogenetic trees, the problem of genome rearrangement, and the problem of motif finding. It also covers methods for predicting the secondary structure of RNA and for reconstructing the peptide sequence using mass spectrometry. The final chapter examines the computational problem related to population genetics.

Bioinformatics

Bioinformatics
Author : N. Gautham
Publisher : Alpha Science Int'l Ltd.
Release Date : 2006
Category : Computers
Total pages :248
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&Quot;Bioinformatics: Databases and Algorithms has two features that distinguish it from others in this genre. First, it seeks to explain some of the basic algorithms in bioinformatics to readers who have little exposure to computer science and mathematics. Second, it deals with structural bioinformatics in greater depth than most other books. The emphasis of this book is on algorithms, though databases have not been entirely neglected, and they have a whole chapter to themselves. Also much attention is given to structural bioinformatics."--BOOK JACKET.

Molecular Bioinformatics

Molecular Bioinformatics
Author : Steffen Schulze-Kremer
Publisher : Walter de Gruyter
Release Date : 1996-01-01
Category : Science
Total pages :315
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Pattern Discovery in Bioinformatics

Pattern Discovery in Bioinformatics
Author : Laxmi Parida
Publisher : CRC Press
Release Date : 2007-07-04
Category : Science
Total pages :512
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The computational methods of bioinformatics are being used more and more to process the large volume of current biological data. Promoting an understanding of the underlying biology that produces this data, Pattern Discovery in Bioinformatics: Theory and Algorithms provides the tools to study regularities in biological data. Taking a systematic approach to pattern discovery, the book supplies sound mathematical definitions and efficient algorithms to explain vital information about biological data. It explores various data patterns, including strings, clusters, permutations, topology, partial orders, and boolean expressions. Each of these classes captures a different form of regularity in the data, providing possible answers to a wide range of questions. The book also reviews basic statistics, including probability, information theory, and the central limit theorem. This self-contained book provides a solid foundation in computational methods, enabling the solution of difficult biological questions.

Algorithms in Bioinformatics

Algorithms in Bioinformatics
Author : Steven L. Salzberg,Tandy Warnow
Publisher : Springer Science & Business Media
Release Date : 2009-08-28
Category : Science
Total pages :430
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These proceedings contain papers from the 2009 Workshop on Algorithms in Bioinformatics (WABI), held at the University of Pennsylvania in Philadelphia, Pennsylvania during September 12–13, 2009. WABI 2009 was the ninth annual conference in this series, which focuses on novel algorithms that address imp- tantproblemsingenomics,molecularbiology,andevolution.Theconference- phasizes research that describes computationally e?cient algorithms and data structures that have been implemented and tested in simulations and on real data. WABI is sponsored by the European Association for Theoretical C- puter Science (EATCS) and the International Society for Computational Bi- ogy (ISCB). WABI 2009 was supported by the Penn Genome Frontiers Institute and the Penn Center for Bioinformatics at the University of Pennsylvania. For the 2009 conference, 90 full papers were submitted for review by the Program Committee, and from this strong ?eld of submissions, 34 papers were chosen for presentation at the conference and publication in the proceedings. The ?nal programcovered a wide range of topics including gene interaction n- works, molecular phylogeny, RNA and protein structure, and genome evolution.

Algorithmic Aspects of Bioinformatics

Algorithmic Aspects of Bioinformatics
Author : Hans-Joachim Böckenhauer,Dirk Bongartz
Publisher : Springer Science & Business Media
Release Date : 2007-06-06
Category : Science
Total pages :396
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This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithmic approaches used to solve them. After introducing the basics of molecular biology and algorithmics, Part I explains string algorithms and alignments; Part II details the field of physical mapping and DNA sequencing; and Part III examines the application of algorithmics to the analysis of biological data. Exciting application examples include predicting the spatial structure of proteins, and computing haplotypes from genotype data. Figures, chapter summaries, detailed derivations, and examples, are provided.

Polarity Index in Proteins - A Bioinformatics Tool

Polarity Index in Proteins - A Bioinformatics Tool
Author : Carlos Polanco
Publisher : Bentham Science Publishers
Release Date : 2016-06-29
Category : Science
Total pages :150
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Polarity is a physico-chemical property that characterizes the electromagnetic stability of a protein and can be used to predict its plausible pathogenic action. For this reason, polarity is regarded as a major factor in most mathematical-computational algorithms that seek to characterize peptides and proteins. The Polarity Index Method makes it possible to reproduce the main classification of peptide proteins found in different databases, with a high degree of discriminative efficiency. Polarity Index In Proteins is a brief monograph that explains the foundations of the polarity index method and presents examples of the application of this method for identifying the structural and functional relationships of different types of proteins (including cell penetrating peptides and natively unfolded proteins). The monograph is divided into sections that cover basic protein biochemistry, the computational mathematical foundations of the polarity index method, the application of the method on different protein structures, and the evaluation of the results of famous experiments on biogenesis (Miller & Urey, Fox & Harada, Rode) by the same method. Polarity Index In Proteins serves as an essential handbook for students and researchers in the field of bioinformatics, proteomics as well as for studies on the role of proteins in the origin of life.

Structural Bioinformatics

Structural Bioinformatics
Author : Forbes J. Burkowski
Publisher : CRC Press
Release Date : 2008-10-30
Category : Science
Total pages :429
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The Beauty of Protein Structures and the Mathematics behind Structural Bioinformatics Providing the framework for a one-semester undergraduate course, Structural Bioinformatics: An Algorithmic Approach shows how to apply key algorithms to solve problems related to macromolecular structure. Helps Students Go Further in Their Study of Structural Biology Following some introductory material in the first few chapters, the text solves the longest common subsequence problem using dynamic programming and explains the science models for the Nussinov and MFOLD algorithms. It then reviews sequence alignment, along with the basic mathematical calculations needed for measuring the geometric properties of macromolecules. After looking at how coordinate transformations facilitate the translation and rotation of molecules in a 3D space, the author introduces structural comparison techniques, superposition algorithms, and algorithms that compare relationships within a protein. The final chapter explores how regression and classification are becoming more useful in protein analysis and drug design. At the Crossroads of Biology, Mathematics, and Computer Science Connecting biology, mathematics, and computer science, this practical text presents various bioinformatics topics and problems within a scientific methodology that emphasizes nature (the source of empirical observations), science (the mathematical modeling of the natural process), and computation (the science of calculating predictions and mathematical objects based on mathematical models).

Beginning Perl for Bioinformatics

Beginning Perl for Bioinformatics
Author : James Tisdall
Publisher : "O'Reilly Media, Inc."
Release Date : 2001-10-22
Category : Computers
Total pages :386
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With its highly developed capacity to detect patterns in data, Perl has become one of the most popular languages for biological data analysis. But if you're a biologist with little or no programming experience, starting out in Perl can be a challenge. Many biologists have a difficult time learning how to apply the language to bioinformatics. The most popular Perl programming books are often too theoretical and too focused on computer science for a non-programming biologist who needs to solve very specific problems.Beginning Perl for Bioinformatics is designed to get you quickly over the Perl language barrier by approaching programming as an important new laboratory skill, revealing Perl programs and techniques that are immediately useful in the lab. Each chapter focuses on solving a particular bioinformatics problem or class of problems, starting with the simplest and increasing in complexity as the book progresses. Each chapter includes programming exercises and teaches bioinformatics by showing and modifying programs that deal with various kinds of practical biological problems. By the end of the book you'll have a solid understanding of Perl basics, a collection of programs for such tasks as parsing BLAST and GenBank, and the skills to take on more advanced bioinformatics programming. Some of the later chapters focus in greater detail on specific bioinformatics topics. This book is suitable for use as a classroom textbook, for self-study, and as a reference.The book covers: Programming basics and working with DNA sequences and strings Debugging your code Simulating gene mutations using random number generators Regular expressions and finding motifs in data Arrays, hashes, and relational databases Regular expressions and restriction maps Using Perl to parse PDB records, annotations in GenBank, and BLAST output

5th International Conference on Practical Applications of Computational Biology & Bioinformatics

5th International Conference on Practical Applications of Computational Biology & Bioinformatics
Author : Miguel P. Rocha,Juan Manuel Corchado Rodríguez,Florentino Fdez Riverola,Alfonso Valencia
Publisher : Springer Science & Business Media
Release Date : 2011-03-09
Category : Computers
Total pages :400
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The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Within this scenario of increasing data availability, Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘11 hopes to contribute to this effort promoting this fruitful interaction. PACBB'11 technical program included 50 papers from a submission pool of 78 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference will certainly have promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work that is being developed by each of the participants.