Biological Pattern Discovery With R PDF Download
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| Author | : Zheng Rong Yang |
| Publisher | : World Scientific |
| Total Pages | : 462 |
| Release | : 2021-09-17 |
| Genre | : Science |
| ISBN | : 9811240132 |
Download Biological Pattern Discovery With R: Machine Learning Approaches Book in PDF, ePub and Kindle
This book provides the research directions for new or junior researchers who are going to use machine learning approaches for biological pattern discovery. The book was written based on the research experience of the author's several research projects in collaboration with biologists worldwide. The chapters are organised to address individual biological pattern discovery problems. For each subject, the research methodologies and the machine learning algorithms which can be employed are introduced and compared. Importantly, each chapter was written with the aim to help the readers to transfer their knowledge in theory to practical implementation smoothly. Therefore, the R programming environment was used for each subject in the chapters. The author hopes that this book can inspire new or junior researchers' interest in biological pattern discovery using machine learning algorithms.
| Author | : Yang Rong Zheng |
| Publisher | : |
| Total Pages | : 462 |
| Release | : 2021 |
| Genre | : Biological systems |
| ISBN | : 9789811240126 |
Download Biological Pattern Discovery with R Book in PDF, ePub and Kindle
| Author | : Laura Elnitski |
| Publisher | : World Scientific |
| Total Pages | : 236 |
| Release | : 2011-01-19 |
| Genre | : Science |
| ISBN | : 9814462640 |
Download Advances In Genomic Sequence Analysis And Pattern Discovery Book in PDF, ePub and Kindle
Mapping the genomic landscapes is one of the most exciting frontiers of science. We have the opportunity to reverse engineer the blueprints and the control systems of living organisms. Computational tools are key enablers in the deciphering process. This book provides an in-depth presentation of some of the important computational biology approaches to genomic sequence analysis. The first section of the book discusses methods for discovering patterns in DNA and RNA. This is followed by the second section that reflects on methods in various ways, including performance, usage and paradigms.
| Author | : Jason T. L. Wang |
| Publisher | : Oxford University Press |
| Total Pages | : 272 |
| Release | : 1999-10-28 |
| Genre | : Science |
| ISBN | : 0198028067 |
Download Pattern Discovery in Biomolecular Data Book in PDF, ePub and Kindle
Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. Pattern Discovery in Biomolecular Data provides a clear, up-to-date summary of the principal techniques. Each chapter is self-contained, and the techniques are drawn from many fields, including graph theory, information theory, statistics, genetic algorithms, computer visualization, and vision. Since pattern searches often benefit from multiple approaches, the book presents methods in their purest form so that readers can best choose the method or combination that fits their needs. The chapters focus on finding patterns in DNA, RNA, and protein sequences, finding patterns in 2D and 3D structures, and choosing system components. This volume will be invaluable for all workers in genomics and genetic analysis, and others whose research requires biocomputing.
| Author | : Fabio Fassetti |
| Publisher | : Springer |
| Total Pages | : 45 |
| Release | : 2017-09-01 |
| Genre | : Computers |
| ISBN | : 3319634771 |
Download Discriminative Pattern Discovery on Biological Networks Book in PDF, ePub and Kindle
This work provides a review of biological networks as a model for analysis, presenting and discussing a number of illuminating analyses. Biological networks are an effective model for providing insights about biological mechanisms. Networks with different characteristics are employed for representing different scenarios. This powerful model allows analysts to perform many kinds of analyses which can be mined to provide interesting information about underlying biological behaviors. The text also covers techniques for discovering exceptional patterns, such as a pattern accounting for local similarities and also collaborative effects involving interactions between multiple actors (for example genes). Among these exceptional patterns, of particular interest are discriminative patterns, namely those which are able to discriminate between two input populations (for example healthy/unhealthy samples). In addition, the work includes a discussion on the most recent proposal on discovering discriminative patterns, in which there is a labeled network for each sample, resulting in a database of networks representing a sample set. This enables the analyst to achieve a much finer analysis than with traditional techniques, which are only able to consider an aggregated network of each population.
| Author | : Mourad Elloumi |
| Publisher | : John Wiley & Sons |
| Total Pages | : 655 |
| Release | : 2015-11-30 |
| Genre | : Technology & Engineering |
| ISBN | : 1119078857 |
Download Pattern Recognition in Computational Molecular Biology Book in PDF, ePub and Kindle
A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.
| Author | : Zheng Rong Yang |
| Publisher | : World Scientific |
| Total Pages | : 267 |
| Release | : 2024-03-06 |
| Genre | : Computers |
| ISBN | : 981128735X |
Download Bio-kernel Machines And Applications Book in PDF, ePub and Kindle
Due to its capability of handling very complex problems and its high flexibility in adapting to different algorithms, the kernel machine plays a crucial role in machine learning.Bio-Kernel Machines and Applications will introduce a new type of kernel machine for the exploration and modeling between the genotypic inherent structures of short protein sequences or nucleic sequences and the phenotypic biological properties or functions of proteins or nucleotides.The book seeks to establish the fundamentals of the bio-kernel machines by presenting the basic principle and theory of the kernel machine and the various formats of kernel machines, such as string kernel machines adapted for biological applications. The book will also introduce several biological applications of the mutation matrices, demonstrating how mutation matrices can enhance the efficiency and biological relevance of machine learning models applied in specific biological problems.Through analyzing current applications of bio-kernel machines, readers will delve into the advantages of the bio-kernel machines and explore how bio-kernel machines can be further enhanced to tackle a wide spectrum of biological challenges and pave the way for future advancements.
| Author | : Jason T. L. Wang |
| Publisher | : Oxford University Press |
| Total Pages | : 272 |
| Release | : 1999-10-28 |
| Genre | : Science |
| ISBN | : 0190283726 |
Download Pattern Discovery in Biomolecular Data Book in PDF, ePub and Kindle
Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. Pattern Discovery in Biomolecular Data provides a clear, up-to-date summary of the principal techniques. Each chapter is self-contained, and the techniques are drawn from many fields, including graph theory, information theory, statistics, genetic algorithms, computer visualization, and vision. Since pattern searches often benefit from multiple approaches, the book presents methods in their purest form so that readers can best choose the method or combination that fits their needs. The chapters focus on finding patterns in DNA, RNA, and protein sequences, finding patterns in 2D and 3D structures, and choosing system components. This volume will be invaluable for all workers in genomics and genetic analysis, and others whose research requires biocomputing.
| Author | : Mourad Elloumi |
| Publisher | : John Wiley & Sons |
| Total Pages | : 1126 |
| Release | : 2015-02-04 |
| Genre | : Computers |
| ISBN | : 1118853725 |
Download Biological Knowledge Discovery Handbook Book in PDF, ePub and Kindle
The first comprehensive overview of preprocessing, mining, and postprocessing of biological data Molecular biology is undergoing exponential growth in both the volume and complexity of biological data and knowledge discovery offers the capacity to automate complex search and data analysis tasks. This book presents a vast overview of the most recent developments on techniques and approaches in the field of biological knowledge discovery and data mining (KDD) providing in-depth fundamental and technical field information on the most important topics encountered. Written by top experts, Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data covers the three main phases of knowledge discovery (data preprocessing, data processing also known as data mining and data postprocessing) and analyzes both verification systems and discovery systems. BIOLOGICAL DATA PREPROCESSING Part A: Biological Data Management Part B: Biological Data Modeling Part C: Biological Feature Extraction Part D Biological Feature Selection BIOLOGICAL DATA MINING Part E: Regression Analysis of Biological Data Part F Biological Data Clustering Part G: Biological Data Classification Part H: Association Rules Learning from Biological Data Part I: Text Mining and Application to Biological Data Part J: High-Performance Computing for Biological Data Mining Combining sound theory with practical applications in molecular biology, Biological Knowledge Discovery Handbook is ideal for courses in bioinformatics and biological KDD as well as for practitioners and professional researchers in computer science, life science, and mathematics.
| Author | : Michael W. Berry |
| Publisher | : SIAM |
| Total Pages | : 556 |
| Release | : 2004-01-01 |
| Genre | : Mathematics |
| ISBN | : 9780898715682 |
Download Proceedings of the Fourth SIAM International Conference on Data Mining Book in PDF, ePub and Kindle
The Fourth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. This is reflected in the talks by the four keynote speakers who discuss data usability issues in systems for data mining in science and engineering, issues raised by new technologies that generate biological data, ways to find complex structured patterns in linked data, and advances in Bayesian inference techniques. This proceedings includes 61 research papers.
