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Analysis Of Biological Data

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The Analysis Of Biological Data

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Author : Michael C. Whitlock
language : en
Publisher: WH Freeman
Release Date : 2020-03-15

The Analysis Of Biological Data written by Michael C. Whitlock and has been published by WH Freeman this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-15 with Medical categories.

Analysis of Biological Data provides students with a practical foundation of statistics for biology students. Every chapter has several biological or medical examples of key concepts, and each example is prefaced by a substantial description of the biological setting. The emphasis on real and interesting examples carries into the problem sets where students have dozens of practice problems based on real data. The third edition features over 200 new examples and problems. These include new calculation practice problems, which guide the student step by step through the methods, and a greater number of examples and topics come from medical and human health research. Every chapter has been carefully edited for even greater clarity and ease of use. All the data sets, R scripts for all worked examples in the book, as well as many other teaching resources, are available to adopting instructors.

Analysis Of Biological Data

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Author : Sanghamitra Bandyopadhyay
language : en
Publisher: World Scientific
Release Date : 2007

Analysis Of Biological Data written by Sanghamitra Bandyopadhyay and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.

Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, they are scattered in different journals, conference proceedings and technical reports, thus causing inconvenience to readers, students and researchers. This book, unique in its nature, is aimed at providing a treatise in a unified framework, with both theoretical and experimental results, describing the basic principles of soft computing and demonstrating the various ways in which they can be used for analyzing biological data in an efficient manner. Interesting research articles from eminent scientists around the world are brought together in a systematic way such that the reader will be able to understand the issues and challenges in this domain, the existing ways of tackling them, recent trends, and future directions. This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in the latter. Sample Chapter(s). Chapter 1: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (160 KB). Contents: Overview: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (H Tang & S Kim); An Introduction to Soft Computing (A Konar & S Das); Biological Sequence and Structure Analysis: Reconstructing Phylogenies with Memetic Algorithms and Branch-and-Bound (J E Gallardo et al.); Classification of RNA Sequences with Support Vector Machines (J T L Wang & X Wu); Beyond String Algorithms: Protein Sequence Analysis Using Wavelet Transforms (A Krishnan & K-B Li); Filtering Protein Surface Motifs Using Negative Instances of Active Sites Candidates (N L Shrestha & T Ohkawa); Distill: A Machine Learning Approach to Ab Initio Protein Structure Prediction (G Pollastri et al.); In Silico Design of Ligands Using Properties of Target Active Sites (S Bandyopadhyay et al.); Gene Expression and Microarray Data Analysis: Inferring Regulations in a Genomic Network from Gene Expression Profiles (N Noman & H Iba); A Reliable Classification of Gene Clusters for Cancer Samples Using a Hybrid Multi-Objective Evolutionary Procedure (K Deb et al.); Feature Selection for Cancer Classification Using Ant Colony Optimization and Support Vector Machines (A Gupta et al.); Sophisticated Methods for Cancer Classification Using Microarray Data (S-B Cho & H-S Park); Multiobjective Evolutionary Approach to Fuzzy Clustering of Microarray Data (A Mukhopadhyay et al.). Readership: Graduate students and researchers in computer science, bioinformatics, computational and molecular biology, artificial intelligence, data mining, machine learning, electrical engineering, system science; researchers in pharmaceutical industries.

A Primer In Biological Data Analysis And Visualization Using R

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Author : Gregg Hartvigsen
language : en
Publisher: Columbia University Press
Release Date : 2014-02-18

A Primer In Biological Data Analysis And Visualization Using R written by Gregg Hartvigsen and has been published by Columbia University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-18 with Education categories.

R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.

The Analysis Of Biological Data

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Author : Michael C. Whitlock
language : en
Publisher: WH Freeman
Release Date : 2014-07-28

This second edition textbook teaches modern methods of statistics through the use of fascinating biological and medical case studies. The clear and engaging writing and practical perspective allows students to understand the analytical process behind biological data. Through the use of real world biological examples, biologists and health professionals can learn statistics in an essential manner. Authors Whitlock and Schulter have over 40 years’ experience between the two of them and therefore able to understand that students learn best through interesting examples and not overcomplicated formulas. This edition includes several unusual features that they have discovered to be helpful for effectively reaching their readers.

Computer Simulation And Data Analysis In Molecular Biology And Biophysics

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Author : Victor Bloomfield
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-05

Computer Simulation And Data Analysis In Molecular Biology And Biophysics written by Victor Bloomfield and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-05 with Science categories.

This book provides an introduction to two important aspects of modern bioch- istry, molecular biology, and biophysics: computer simulation and data analysis. My aim is to introduce the tools that will enable students to learn and use some f- damental methods to construct quantitative models of biological mechanisms, both deterministicandwithsomeelementsofrandomness;tolearnhowconceptsofpr- ability can help to understand important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data. The availability of very capable but inexpensive personal computers and software makes it possible to do such work at a much higher level, but in a much easier way, than ever before. TheExecutiveSummaryofthein?uential2003reportfromtheNationalAcademy of Sciences, “BIO 2010: Transforming Undergraduate Education for Future - search Biologists” [12], begins The interplay of the recombinant DNA, instrumentation, and digital revolutions has p- foundly transformed biological research. The con?uence of these three innovations has led to important discoveries, such as the mapping of the human genome. How biologists design, perform, and analyze experiments is changing swiftly. Biological concepts and models are becoming more quantitative, and biological research has become critically dependent on concepts and methods drawn from other scienti?c disciplines. The connections between the biological sciences and the physical sciences, mathematics, and computer science are rapidly becoming deeper and more extensive.

Experimental Design And Data Analysis For Biologists

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Author : Gerald Peter Quinn
language : en
Publisher: Cambridge University Press
Release Date : 2002-03-21

Experimental Design And Data Analysis For Biologists written by Gerald Peter Quinn and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-03-21 with Mathematics categories.

An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a website that provides all data sets, questions for each chapter and links to software.

Biological Sequence Analysis

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Author : Richard Durbin
language : en
Publisher: Cambridge University Press
Release Date : 1998-04-23

Biological Sequence Analysis written by Richard Durbin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-04-23 with Medical categories.

Presents up-to-date computer methods for analysing DNA, RNA and protein sequences.

Biostatistics With R

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Author : Babak Shahbaba
language : en
Publisher: Springer Science+Business Media
Release Date : 2012

Biostatistics With R written by Babak Shahbaba and has been published by Springer Science+Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Biometry categories.

Biostatistics with R is designed to mimic the interaction between theory and application in statistics. Topics include data exploration, estimation, and clustering with two appendices on installing and running R and R-commander.

Analysis Of Biological Development

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Author : Klaus Kalthoff
language : en
Publisher: McGraw-Hill Science, Engineering & Mathematics
Release Date : 2001

Analysis Of Biological Development written by Klaus Kalthoff and has been published by McGraw-Hill Science, Engineering & Mathematics this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Biologie du développement categories.

This text, now available in full color, presents developmental biology as an ongoing process of enquiry, giving students a sense of the ways developmental biologists gain knowledge and a taste of the challenges ahead. The first part of the text focuses on the classical methods of analysis and the stages of embryonic development from gametogenesis to histogenesis. Part Two introduces the genetic and molecular analysis of development. The final part combines classical and modern types of analysis towards the investigation of long standing problems in development. Key experiments are described throughout to reinforce the relationship between scientific models and experimental data.

Analysis Of Biological Data A Soft Computing Approach

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Author : Sanghamitra Bandyopadhyay
language : en
Publisher: World Scientific
Release Date : 2007-09-03

Analysis Of Biological Data A Soft Computing Approach written by Sanghamitra Bandyopadhyay and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-03 with Computers categories.

Analysis Of Biological Data

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