Download or read book Multivariate Algorithmics in Biological Data Analysis written by Johannes Uhlmann and published by Univerlagtuberlin. This book was released on 2011 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to the Exploration of Multivariate Biological Data written by János Podani and published by . This book was released on 2000 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Attention is focused on the supraindividual biological level in example plant ecology, phytosociology and taxonomy.
Download or read book Advances in Multivariate Data Analysis written by Hans-Hermann Bock and published by Springer Science & Business Media. This book was released on 2012-09-30 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a range of new developments in the theory and practice of multivariate statistical data analysis. Several contributions illustrate the use of multivariate methods in application fields such as economics, medicine, environment, and biology.
Download or read book Algorithms in Computational Molecular Biology written by Mourad Elloumi and published by John Wiley & Sons. This book was released on 2011-04-04 with total page 1027 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study.
Download or read book Analysis of Multivariate and High Dimensional Data written by Inge Koch and published by . This book was released on 2013 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduate students in statistics and researchers in data-rich disciplines.
Download or read book Bioinformatics Algorithms written by Ion Mandoiu and published by John Wiley & Sons. This book was released on 2008-02-25 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Algorithmic Aspects of Bioinformatics written by Hans-Joachim Böckenhauer and published by Springer Science & Business Media. This book was released on 2007-06-06 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Genome Scale Algorithm Design written by Veli Mäkinen and published by Cambridge University Press. This book was released on 2015-05-07 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an integrated picture of the latest developments in algorithmic techniques, with numerous worked examples, algorithm visualisations and exercises.
Download or read book Multivariate Data Integration Using R written by Kim-Anh Lê Cao and published by CRC Press. This book was released on 2021-11-08 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large biological data, which are often noisy and high-dimensional, have become increasingly prevalent in biology and medicine. There is a real need for good training in statistics, from data exploration through to analysis and interpretation. This book provides an overview of statistical and dimension reduction methods for high-throughput biological data, with a specific focus on data integration. It starts with some biological background, key concepts underlying the multivariate methods, and then covers an array of methods implemented using the mixOmics package in R. Features: Provides a broad and accessible overview of methods for multi-omics data integration Covers a wide range of multivariate methods, each designed to answer specific biological questions Includes comprehensive visualisation techniques to aid in data interpretation Includes many worked examples and case studies using real data Includes reproducible R code for each multivariate method, using the mixOmics package The book is suitable for researchers from a wide range of scientific disciplines wishing to apply these methods to obtain new and deeper insights into biological mechanisms and biomedical problems. The suite of tools introduced in this book will enable students and scientists to work at the interface between, and provide critical collaborative expertise to, biologists, bioinformaticians, statisticians and clinicians.
Download or read book Software Tools and Algorithms for Biological Systems written by Hamid Arabnia and published by Springer Science & Business Media. This book was released on 2011-03-23 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Software Tools and Algorithms for Biological Systems" is composed of a collection of papers received in response to an announcement that was widely distributed to academicians and practitioners in the broad area of computational biology and software tools. Also, selected authors of accepted papers of BIOCOMP’09 proceedings (International Conference on Bioinformatics and Computational Biology: July 13-16, 2009; Las Vegas, Nevada, USA) were invited to submit the extended versions of their papers for evaluation.
Download or read book Analyzing the Large Number of Variables in Biomedical and Satellite Imagery written by Phillip I. Good and published by John Wiley & Sons. This book was released on 2011-05-18 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book grew out of an online interactive offered through statcourse.com, and it soon became apparent to the author that the course was too limited in terms of time and length in light of the broad backgrounds of the enrolled students. The statisticians who took the course needed to be brought up to speed both on the biological context as well as on the specialized statistical methods needed to handle large arrays. Biologists and physicians, even though fully knowledgeable concerning the procedures used to generate microaarrays, EEGs, or MRIs, needed a full introduction to the resampling methods—the bootstrap, decision trees, and permutation tests, before the specialized methods applicable to large arrays could be introduced. As the intended audience for this book consists both of statisticians and of medical and biological research workers as well as all those research workers who make use of satellite imagery including agronomists and meteorologists, the book provides a step-by-step approach to not only the specialized methods needed to analyze the data from microarrays and images, but also to the resampling methods, step-down multi-comparison procedures, multivariate analysis, as well as data collection and pre-processing. While many alternate techniques for analysis have been introduced in the past decade, the author has selected only those techniques for which software is available along with a list of the available links from which the software may be purchased or downloaded without charge. Topical coverage includes: very large arrays; permutation tests; applying permutation tests; gathering and preparing data for analysis; multiple tests; bootstrap; applying the bootstrap; classification methods; decision trees; and applying decision trees.
Download or read book Multivariate Statistical Machine Learning Methods for Genomic Prediction written by Osval Antonio Montesinos López and published by Springer Nature. This book was released on 2022-02-14 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Download or read book Basics of Bioinformatics written by Rui Jiang and published by Springer Science & Business Media. This book was released on 2013-11-26 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book outlines 11 courses and 15 research topics in bioinformatics, based on curriculums and talks in a graduate summer school on bioinformatics that was held in Tsinghua University. The courses include: Basics for Bioinformatics, Basic Statistics for Bioinformatics, Topics in Computational Genomics, Statistical Methods in Bioinformatics, Algorithms in Computational Biology, Multivariate Statistical Methods in Bioinformatics Research, Association Analysis for Human Diseases: Methods and Examples, Data Mining and Knowledge Discovery Methods with Case Examples, Applied Bioinformatics Tools, Foundations for the Study of Structure and Function of Proteins, Computational Systems Biology Approaches for Deciphering Traditional Chinese Medicine, and Advanced Topics in Bioinformatics and Computational Biology. This book can serve as not only a primer for beginners in bioinformatics, but also a highly summarized yet systematic reference book for researchers in this field. Rui Jiang and Xuegong Zhang are both professors at the Department of Automation, Tsinghua University, China. Professor Michael Q. Zhang works at the Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
Download or read book Contemporary Experimental Design Multivariate Analysis and Data Mining written by Jianqing Fan and published by Springer Nature. This book was released on 2020-05-22 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can easily collect data characterised by massive dimensions and complexity. In celebration of Professor Kai-Tai Fang’s 80th birthday, we present this book, which furthers new and exciting developments in modern statistical theories, methods and applications. The book features four review papers on Professor Fang’s numerous contributions to the fields of experimental design, multivariate analysis, data mining and education. It also contains twenty research articles contributed by prominent and active figures in their fields. The articles cover a wide range of important topics such as experimental design, multivariate analysis, data mining, hypothesis testing and statistical models.
Download or read book Bio inspired Algorithms for Data Streaming and Visualization Big Data Management and Fog Computing written by Simon James Fong and published by Springer Nature. This book was released on 2020-08-25 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases. The subject area of this book is within the realm of computer science, notably algorithms (meta-heuristic and, more particularly, bio-inspired algorithms). Although application domains of these new algorithms may be mentioned, the scope of this book is not on the application of algorithms to specific or general domains but to provide an update on recent research trends for bio-inspired algorithms within a specific application domain or emerging area. These areas include data streaming, fog computing, and phases of big data management. One of the reasons for writing this book is that the bio-inspired approach does not receive much attention but shows considerable promise and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase such as data mining or business intelligence as many books focus on); effective demonstration of the effectiveness of a selected algorithm within a chapter against comparative algorithms using the experimental method. Another novel approach is a brief overview and evaluation of traditional algorithms, both sequential and parallel, for use in data mining, in order to provide an overview of existing algorithms in use. This overview complements a further chapter on bio-inspired algorithms for data mining to enable readers to make a more suitable choice of algorithm for data mining within a particular context. In all chapters, references for further reading are provided, and in selected chapters, the author also include ideas for future research.
Download or read book Data Analysis Machine Learning and Knowledge Discovery written by Myra Spiliopoulou and published by Springer Science & Business Media. This book was released on 2013-11-26 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012.
Download or read book New Approaches in Classification and Data Analysis written by Edwin Diday and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of this book is the analysis and processing of structural or quantitative data with emphasis on classification methods, new algorithms as well as applications in various fields related to data analysis and classification. The book presents the state of the art in world-wide research and application of methods from the fields indicated above and consists of survey papers as well as research papers.
