Data Analytics in Bioinformatics

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Publisher : John Wiley & Sons
ISBN 13 : 111978560X
Total Pages : 433 pages
Book Rating : 4.06/5 ( download)

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Book Synopsis Data Analytics in Bioinformatics by : Rabinarayan Satpathy

Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Big Data Analytics in Bioinformatics and Healthcare

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Publisher : IGI Global
ISBN 13 : 1466666129
Total Pages : 552 pages
Book Rating : 4.22/5 ( download)

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Book Synopsis Big Data Analytics in Bioinformatics and Healthcare by : Wang, Baoying

Download or read book Big Data Analytics in Bioinformatics and Healthcare written by Wang, Baoying and published by IGI Global. This book was released on 2014-10-31 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.

Big Data Analytics in Chemoinformatics and Bioinformatics

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Publisher : Elsevier
ISBN 13 : 0323857140
Total Pages : 503 pages
Book Rating : 4.47/5 ( download)

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Book Synopsis Big Data Analytics in Chemoinformatics and Bioinformatics by : Subhash C. Basak

Download or read book Big Data Analytics in Chemoinformatics and Bioinformatics written by Subhash C. Basak and published by Elsevier. This book was released on 2022-12-06 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics in Chemoinformatics and Bioinformatics: With Applications to Computer-Aided Drug Design, Cancer Biology, Emerging Pathogens and Computational Toxicology provides an up-to-date presentation of big data analytics methods and their applications in diverse fields. The proper management of big data for decision-making in scientific and social issues is of paramount importance. This book gives researchers the tools they need to solve big data problems in these fields. It begins with a section on general topics that all readers will find useful and continues with specific sections covering a range of interdisciplinary applications. Here, an international team of leading experts review their respective fields and present their latest research findings, with case studies used throughout to analyze and present key information. Brings together the current knowledge on the most important aspects of big data, including analysis using deep learning and fuzzy logic, transparency and data protection, disparate data analytics, and scalability of the big data domain Covers many applications of big data analysis in diverse fields such as chemistry, chemoinformatics, bioinformatics, computer-assisted drug/vaccine design, characterization of emerging pathogens, and environmental protection Highlights the considerable benefits offered by big data analytics to science, in biomedical fields and in industry

Bioinformatics Data Skills

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449367518
Total Pages : 538 pages
Book Rating : 4.10/5 ( download)

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Book Synopsis Bioinformatics Data Skills by : Vince Buffalo

Download or read book Bioinformatics Data Skills written by Vince Buffalo and published by "O'Reilly Media, Inc.". This book was released on 2015-07 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, youâ??ll learn how to use freely available open source tools to extract meaning from large complex biological data sets. At no other point in human history has our ability to understand lifeâ??s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, youâ??re ready to get started. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles

Data Analysis in Molecular Biology and Evolution

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Publisher : Springer Science & Business Media
ISBN 13 : 030646893X
Total Pages : 284 pages
Book Rating : 4.33/5 ( download)

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Book Synopsis Data Analysis in Molecular Biology and Evolution by : Xuhua Xia

Download or read book Data Analysis in Molecular Biology and Evolution written by Xuhua Xia and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis in Molecular Biology and Evolution introduces biologists to DAMBE, a proprietary, user-friendly computer program for molecular data analysis. The unique combination of this book and software will allow biologists not only to understand the rationale behind a variety of computational tools in molecular biology and evolution, but also to gain instant access to these tools for use in their laboratories. Data Analysis in Molecular Biology and Evolution serves as an excellent resource for advanced level undergraduates or graduates as well as for professionals working in the field.

Analysis of Biological Data

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Publisher :
ISBN 13 : 9814475122
Total Pages : pages
Book Rating : 4.29/5 ( download)

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Book Synopsis Analysis of Biological Data by :

Download or read book Analysis of Biological Data written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bioinformatics for Omics Data

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Publisher : Springer Science+Business Media
ISBN 13 : 9781617790270
Total Pages : 584 pages
Book Rating : 4.73/5 ( download)

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Book Synopsis Bioinformatics for Omics Data by : Bernd Mayer

Download or read book Bioinformatics for Omics Data written by Bernd Mayer and published by Springer Science+Business Media. This book was released on 2011-01-01 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting an area of research that intersects with and integrates diverse disciplines, Bioinformatics for Omics Data: Methods and Protocols collects contributions from expert researchers in order to provide practical guidelines to this complex study.

Pattern Recognition and Machine Intelligence

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Publisher : Springer Science & Business Media
ISBN 13 : 3540770453
Total Pages : 693 pages
Book Rating : 4.59/5 ( download)

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Book Synopsis Pattern Recognition and Machine Intelligence by : Rajat K. De

Download or read book Pattern Recognition and Machine Intelligence written by Rajat K. De and published by Springer Science & Business Media. This book was released on 2007-11-29 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Conference on Pattern Recognition and Machine Intelligence, PReMI 2007, held in Kolkata, India in December 2007. The 82 revised papers presented were carefully reviewed and selected from 241 submissions. The papers are organized in topical sections on pattern recognition, image analysis, soft computing and applications, data mining and knowledge discovery, bioinformatics, signal and speech processing, document analysis and text mining, biometrics, and video analysis.

Genome Data Analysis

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Publisher : Springer
ISBN 13 : 9811319421
Total Pages : 367 pages
Book Rating : 4.26/5 ( download)

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Book Synopsis Genome Data Analysis by : Ju Han Kim

Download or read book Genome Data Analysis written by Ju Han Kim and published by Springer. This book was released on 2019-04-30 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases. The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics.

Introduction to Bioinformatics with R

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Author :
Publisher : CRC Press
ISBN 13 : 1351015303
Total Pages : 311 pages
Book Rating : 4.01/5 ( download)

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Book Synopsis Introduction to Bioinformatics with R by : Edward Curry

Download or read book Introduction to Bioinformatics with R written by Edward Curry and published by CRC Press. This book was released on 2020-11-02 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: In biological research, the amount of data available to researchers has increased so much over recent years, it is becoming increasingly difficult to understand the current state of the art without some experience and understanding of data analytics and bioinformatics. An Introduction to Bioinformatics with R: A Practical Guide for Biologists leads the reader through the basics of computational analysis of data encountered in modern biological research. With no previous experience with statistics or programming required, readers will develop the ability to plan suitable analyses of biological datasets, and to use the R programming environment to perform these analyses. This is achieved through a series of case studies using R to answer research questions using molecular biology datasets. Broadly applicable statistical methods are explained, including linear and rank-based correlation, distance metrics and hierarchical clustering, hypothesis testing using linear regression, proportional hazards regression for survival data, and principal component analysis. These methods are then applied as appropriate throughout the case studies, illustrating how they can be used to answer research questions. Key Features: · Provides a practical course in computational data analysis suitable for students or researchers with no previous exposure to computer programming. · Describes in detail the theoretical basis for statistical analysis techniques used throughout the textbook, from basic principles · Presents walk-throughs of data analysis tasks using R and example datasets. All R commands are presented and explained in order to enable the reader to carry out these tasks themselves. · Uses outputs from a large range of molecular biology platforms including DNA methylation and genotyping microarrays; RNA-seq, genome sequencing, ChIP-seq and bisulphite sequencing; and high-throughput phenotypic screens. · Gives worked-out examples geared towards problems encountered in cancer research, which can also be applied across many areas of molecular biology and medical research. This book has been developed over years of training biological scientists and clinicians to analyse the large datasets available in their cancer research projects. It is appropriate for use as a textbook or as a practical book for biological scientists looking to gain bioinformatics skills.