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An Introduction to Bioinformatics Algorithms

An Introduction to Bioinformatics Algorithms
A Book

by Neil C. Jones,Pavel A. Pevzner,Pavel Pevzner

  • Publisher : MIT Press
  • Release : 2004
  • Pages : 435
  • ISBN : 0262101068
  • Language : En, Es, Fr & De
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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
Techniques and Applications

by Ion Mandoiu,Alexander Zelikovsky

  • Publisher : John Wiley & Sons
  • Release : 2008-02-25
  • Pages : 528
  • ISBN : 0470097736
  • Language : En, Es, Fr & De
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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
An Active Learning Approach

by Phillip Compeau,Pavel Pevzner

  • Publisher : Unknown Publisher
  • Release : 2014-05-20
  • Pages : 392
  • ISBN : 9780990374602
  • Language : En, Es, Fr & De
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Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Open Online Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed MOOC on Coursera, 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 both biology and computer science. 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 the Rosalind Bioinformatics Textbook Track. A website augments the textbook by providing additional educational materials, including video lectures and PowerPoint slides.--Book website.

Bioinformatics Algorithms

Bioinformatics Algorithms
Design and Implementation in Python

by Miguel Rocha,Pedro G. Ferreira

  • Publisher : Academic Press
  • Release : 2018-06-08
  • Pages : 400
  • ISBN : 0128125217
  • Language : En, Es, Fr & De
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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
Techniques and Applications

by Ion Mandoiu,Alexander Zelikovsky

  • Publisher : John Wiley & Sons
  • Release : 2008-02-15
  • Pages : 520
  • ISBN : 9780470253427
  • Language : En, Es, Fr & De
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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.

Bioinformatic Algorithms

Bioinformatic Algorithms
Design and Implementation in Python

by Miguel Rocha,Pedro G. Ferreira

  • Publisher : Academic Press
  • Release : 2018-02
  • Pages : 420
  • ISBN : 9780128125205
  • Language : En, Es, Fr & De
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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 regarding 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

Molecular Bioinformatics

Molecular Bioinformatics
Algorithms and Applications

by Steffen Schulze-Kremer

  • Publisher : Walter de Gruyter
  • Release : 1996-01-01
  • Pages : 315
  • ISBN : 3110808919
  • Language : En, Es, Fr & De
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An Introduction to Bioinformatics Algorithms

An Introduction to Bioinformatics Algorithms
A Book

by Neil C. Jones,Pavel A. Pevzner

  • Publisher : Unknown Publisher
  • Release : 2004
  • Pages : 435
  • ISBN : 9788180520785
  • Language : En, Es, Fr & De
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Algorithms in Bioinformatics

Algorithms in Bioinformatics
12th International Workshop, WABI 2012, Ljubljana, Slovenia, September 10-12, 2012. Proceedings

by Ben Raphael,Jijun Tang

  • Publisher : Springer
  • Release : 2012-08-29
  • Pages : 454
  • ISBN : 364233122X
  • Language : En, Es, Fr & De
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This book constitutes the refereed proceedings of the 12th International Workshop on Algorithms in Bioinformatics, WABI 2012, held in Ljubljana, Slovenia, in September 2012. WABI 2012 is one of six workshops which, along with the European Symposium on Algorithms (ESA), constitute the ALGO annual meeting and focuses on algorithmic advances in bioinformatics, computational biology, and systems biology with a particular emphasis on discrete algorithms and machine-learning methods that address important problems in molecular biology. The 35 full papers presented were carefully reviewed and selected from 92 submissions. The papers include algorithms for a variety of biological problems including phylogeny, DNA and RNA sequencing and analysis, protein structure, and others.

Algorithms in Bioinformatics

Algorithms in Bioinformatics
5th International Workshop, WABI 2005, Mallorca, Spain, October 3-6, 2005, Proceedings

by Rita Casadio

  • Publisher : Springer Science & Business Media
  • Release : 2005-09-27
  • Pages : 436
  • ISBN : 9783540290087
  • Language : En, Es, Fr & De
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This book constitutes the refereed proceedings of the 5th International Workshop on Algorithms in Bioinformatics, WABI 2005, held in Mallorca, Spain, in September 2005 as part of the ALGO 2005 conference meetings. The 34 revised full papers presented were carefully reviewed and selected from 95 submissions. All current issues of algorithms in bioinformatics are addressed with special focus on statistical and probabilistic algorithms in the field of molecular and structural biology. The papers are organized in topical sections on expression (hybrid methods and time patterns), phylogeny (quartets, tree reconciliation, clades and haplotypes), networks, genome rearrangements (transposition model and other models), sequences (strings, multi-alignment and clustering, clustering and representation), and structure (threading and folding).

Polarity Index in Proteins - A Bioinformatics Tool

Polarity Index in Proteins - A Bioinformatics Tool
A Book

by Carlos Polanco

  • Publisher : Bentham Science Publishers
  • Release : 2016-06-29
  • Pages : 150
  • ISBN : 1681082691
  • Language : En, Es, Fr & De
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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.

Bioinformatics Algorithms

Bioinformatics Algorithms
A Book

by C. Kuppuswamy

  • Publisher : Unknown Publisher
  • Release : 2007
  • Pages : 299
  • ISBN : 9788178884820
  • Language : En, Es, Fr & De
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5th International Conference on Practical Applications of Computational Biology & Bioinformatics

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

by Miguel P. Rocha,Juan Manuel Corchado Rodríguez,Florentino Fdez Riverola,Alfonso Valencia

  • Publisher : Springer Science & Business Media
  • Release : 2011-03-09
  • Pages : 400
  • ISBN : 9783642199141
  • Language : En, Es, Fr & De
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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.

Bioinformatics Algorithms

Bioinformatics Algorithms
Blast

by Source Wikipedia,Books Llc

  • Publisher : Books LLC, Wiki Series
  • Release : 2010
  • Pages : 64
  • ISBN : 9781156652954
  • Language : En, Es, Fr & De
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 51. Chapters: Genetic algorithms, Genetic programming, Mutation, BLAST, Pseudo amino acid composition, Smith-Waterman algorithm, Weasel program, Microarray analysis techniques, List of genetic algorithm applications, Needleman-Wunsch algorithm, Neighbor-joining, Neuroevolution of augmenting topologies, Quality control and genetic algorithms, Hirschberg's algorithm, Crossover, Genetic algorithm scheduling, Edge recombination operator, Population-based incremental learning, Fitness approximation, Cultural algorithm, HyperNEAT, Kabsch algorithm, Promoter based genetic algorithm, Clonal Selection Algorithm, Genetic fuzzy systems, Genetic algorithms in economics, Robinson-Foulds metric, Baum-Welch algorithm, Holland's schema theorem, Fitness function, Fitness proportionate selection, Velvet assembler, Quartet distance, Chromosome, Stochastic universal sampling, Tournament selection, Premature convergence, Ukkonen's algorithm, Speciation, Genetic operator, PSI Protein Classifier, Defining length, Genetic memory, Truncation selection, Evolver, Inheritance. Excerpt: In artificial intelligence, genetic programming (GP) is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. It is a specialization of genetic algorithms (GA) where each individual is a computer program. It is a machine learning technique used to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task. The goal of having computers automatically solve problems is central to artificial intelligence (AI) machine learning (ML), and the broad area encompassed by what Turing called "machine intelligence" (Turing, 1948). Machine learning pioneer Arthur Samuel, in his 1983 talk entitled "AI: Where It Has Been a...

Beginning Perl for Bioinformatics

Beginning Perl for Bioinformatics
An Introduction to Perl for Biologists

by James Tisdall

  • Publisher : "O'Reilly Media, Inc."
  • Release : 2001-10-22
  • Pages : 386
  • ISBN : 9780596550479
  • Language : En, Es, Fr & De
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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

Biotechnology and Bioinformatics

Biotechnology and Bioinformatics
Advances and Applications for Bioenergy, Bioremediation and Biopharmaceutical Research

by Devarajan Thangadurai,Jeyabalan Sangeetha

  • Publisher : CRC Press
  • Release : 2014-07-01
  • Pages : 524
  • ISBN : 1482239388
  • Language : En, Es, Fr & De
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Reflecting the interdisciplinary nature of biotechnology, this book covers the role of targeted delivery of polymeric nanodrugs to cancer cells, microbial detoxifying enzymes in bioremediation and bacterial plasmids in antimicrobial resistance. It addresses modern trends such as pharmacogenomics, evaluation of gene expression, recombinant proteins from methylotrophic yeast, identification of novel fermentation inhibitors of bioethanol production, and polyhydroxyalkanoate based biomaterials. The book highlights the practical utility of biotechnology and bioinformatics for bioenergy, production of high value biochemicals, modeling molecular interactions, drug discovery, and personalized medicine.

Data Mining for Bioinformatics Applications

Data Mining for Bioinformatics Applications
A Book

by He Zengyou

  • Publisher : Woodhead Publishing
  • Release : 2015-06-09
  • Pages : 100
  • ISBN : 008100107X
  • Language : En, Es, Fr & De
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Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation. Provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems Uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems Contains 45 bioinformatics problems that have been investigated in recent research

Bioinformatics

Bioinformatics
High Performance Parallel Computer Architectures

by Bertil Schmidt

  • Publisher : CRC Press
  • Release : 2010-07-15
  • Pages : 370
  • ISBN : 1439814899
  • Language : En, Es, Fr & De
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New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data. This expansion of biological databases established the need for new ways to harness and apply the astounding amount of available genomic information and convert it into substantive biological

Exploring Bioinformatics

Exploring Bioinformatics
A Book

by Caroline St. Clair,Jonathan E. Visick

  • Publisher : Jones & Bartlett Publishers
  • Release : 2013-12-01
  • Pages : 360
  • ISBN : 128402346X
  • Language : En, Es, Fr & De
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Thoroughly revised and updated, Exploring Bioinformatics: A Project-Based Approach, Second Edition is intended for an introductory course in bioinformatics at the undergraduate level. Through hands-on projects, students are introduced to current biological problems and then explore and develop bioinformatic solutions to these issues. Each chapter presents a key problem, provides basic biological concepts, introduces computational techniques to address the problem, and guides students through the use of existing web-based tools and software solutions. This progression prepares students to tackle the On-Your-Own Project, where they develop their own software solutions. Topics such as antibiotic resistance, genetic disease, and genome sequencing provide context and relevance to capture student interest.

Algorithms in Bioinformatics

Algorithms in Bioinformatics
Theory and Implementation

by Paul A. Gagniuc

  • Publisher : John Wiley & Sons
  • Release : 2021-08-10
  • Pages : 528
  • ISBN : 1119697964
  • Language : En, Es, Fr & De
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ALGORITHMS IN BIOINFORMATICS Explore a comprehensive and insightful treatment of the practical application of bioinformatic algorithms in a variety of fields Algorithms in Bioinformatics: Theory and Implementation delivers a fulsome treatment of some of the main algorithms used to explain biological functions and relationships. It introduces readers to the art of algorithms in a practical manner which is linked with biological theory and interpretation. The book covers many key areas of bioinformatics, including global and local sequence alignment, forced alignment, detection of motifs, Sequence logos, Markov chains or information entropy. Other novel approaches are also described, such as Self-Sequence alignment, Objective Digital Stains (ODSs) or Spectral Forecast and the Discrete Probability Detector (DPD) algorithm. The text incorporates graphical illustrations to highlight and emphasize the technical details of computational algorithms found within, to further the reader’s understanding and retention of the material. Throughout, the book is written in an accessible and practical manner, showing how algorithms can be implemented and used in JavaScript on Internet Browsers. The author has included more than 120 open-source implementations of the material, as well as 33 ready-to-use presentations. The book contains original material that has been class-tested by the author and numerous cases are examined in a biological and medical context. Readers will also benefit from the inclusion of: A thorough introduction to biological evolution, including the emergence of life, classifications and some known theories and molecular mechanisms A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields An examination of information and entropy, including sequence logos and explanations related to their meaning An exploration of the current state of bioinformatics, including what is known and what issues are usually avoided in the field A chapter on philosophical transactions that allows the reader a broader view of the prediction process Native computer implementations in the context of the field of Bioinformatics Extensive worked examples with detailed case studies that point out the meaning of different results Perfect for professionals and researchers in biology, medicine, engineering, and information technology, as well as upper level undergraduate students in these fields, Algorithms in Bioinformatics: Theory and Implementation will also earn a place in the libraries of software engineers who wish to understand how to implement bioinformatic algorithms in their products.