Hands on Data Science for Biologists Using Python

Hands on Data Science for Biologists Using Python

Author: Yasha Hasija

Publisher: CRC Press

Published: 2021-04-08

Total Pages: 299

ISBN-13: 1000345483

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Hands-on Data Science for Biologists using Python has been conceptualized to address the massive data handling needs of modern-day biologists. With the advent of high throughput technologies and consequent availability of omics data, biological science has become a data-intensive field. This hands-on textbook has been written with the inception of easing data analysis by providing an interactive, problem-based instructional approach in Python programming language. The book starts with an introduction to Python and steadily delves into scrupulous techniques of data handling, preprocessing, and visualization. The book concludes with machine learning algorithms and their applications in biological data science. Each topic has an intuitive explanation of concepts and is accompanied with biological examples. Features of this book: The book contains standard templates for data analysis using Python, suitable for beginners as well as advanced learners. This book shows working implementations of data handling and machine learning algorithms using real-life biological datasets and problems, such as gene expression analysis; disease prediction; image recognition; SNP association with phenotypes and diseases. Considering the importance of visualization for data interpretation, especially in biological systems, there is a dedicated chapter for the ease of data visualization and plotting. Every chapter is designed to be interactive and is accompanied with Jupyter notebook to prompt readers to practice in their local systems. Other avant-garde component of the book is the inclusion of a machine learning project, wherein various machine learning algorithms are applied for the identification of genes associated with age-related disorders. A systematic understanding of data analysis steps has always been an important element for biological research. This book is a readily accessible resource that can be used as a handbook for data analysis, as well as a platter of standard code templates for building models.


Introduction to Biological Data Analysis in Python

Introduction to Biological Data Analysis in Python

Author: Stilianos Louca

Publisher: Stilianos Louca

Published: 2023-03-17

Total Pages: 264

ISBN-13:

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This book introduces computational data analysis in biology, using the free and popular programming language python 3. The book targets undergraduate and graduate students in biology with an interest in computational techniques, but could also be of interest to students in other scientific disciplines such as biochemistry, environmental sciences and physics. No prior programming experience is required -- this book is intended for the motivated novice! Readers will learn to load and analyze data and produce professional visualizations. The mathematical content is kept to a bare minimum. Examples and exercises are drawn from a wide spectrum across biology, such as epidemiology, ecology, conservation biology, neuroscience, evolution, genetics, genomics and microbiology. Many exercises use realistic datasets published in the scientific literature, such as bacterial genome sequences, animal GPS tracking data, population time series and biodiversity inventories. References to the scientific literature are provided throughout.


Python for Biologists

Python for Biologists

Author: Martin Jones

Publisher: Createspace Independent Publishing Platform

Published: 2013

Total Pages: 248

ISBN-13:

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Python for biologists is a complete programming course for beginners that will give you the skills you need to tackle common biological and bioinformatics problems.


Python Programming for Biology

Python Programming for Biology

Author: Tim J. Stevens

Publisher: Cambridge University Press

Published: 2015-02-12

Total Pages: 721

ISBN-13: 1316194140

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Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language.


A Primer for Computational Biology

A Primer for Computational Biology

Author: Shawn T. O'Neil

Publisher:

Published: 2017-12-21

Total Pages: 0

ISBN-13: 9780870719264

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A Primer for Computational Biology aims to provide life scientists and students the skills necessary for research in a data-rich world. The text covers accessing and using remote servers via the command-line, writing programs and pipelines for data analysis, and provides useful vocabulary for interdisciplinary work. The book is broken into three parts: Introduction to Unix/Linux: The command-line is the "natural environment" of scientific computing, and this part covers a wide range of topics, including logging in, working with files and directories, installing programs and writing scripts, and the powerful "pipe" operator for file and data manipulation. Programming in Python: Python is both a premier language for learning and a common choice in scientific software development. This part covers the basic concepts in programming (data types, if-statements and loops, functions) via examples of DNA-sequence analysis. This part also covers more complex subjects in software development such as objects and classes, modules, and APIs. Programming in R: The R language specializes in statistical data analysis, and is also quite useful for visualizing large datasets. This third part covers the basics of R as a programming language (data types, if-statements, functions, loops and when to use them) as well as techniques for large-scale, multi-test analyses. Other topics include S3 classes and data visualization with ggplot2.


Managing Your Biological Data with Python

Managing Your Biological Data with Python

Author: Allegra Via

Publisher: CRC Press

Published: 2014-03-18

Total Pages: 556

ISBN-13: 1439880948

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Take Control of Your Data and Use Python with ConfidenceRequiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how


Data Analysis for the Life Sciences with R

Data Analysis for the Life Sciences with R

Author: Rafael A. Irizarry

Publisher: CRC Press

Published: 2016-10-04

Total Pages: 537

ISBN-13: 1498775861

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This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.


Bioinformatics Programming Using Python

Bioinformatics Programming Using Python

Author: Mitchell L Model

Publisher: "O'Reilly Media, Inc."

Published: 2009-12-08

Total Pages: 526

ISBN-13: 1449382908

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Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming. Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks. Become familiar with Python's fundamentals, including ways to develop simple applications Learn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database access Discover generalized patterns that cover a large proportion of how Python code is used in bioinformatics Learn how to apply the principles and techniques of object-oriented programming Benefit from the "tips and traps" section in each chapter


Python for Bioinformatics

Python for Bioinformatics

Author: Sebastian Bassi

Publisher: CRC Press

Published: 2017-08-07

Total Pages: 423

ISBN-13: 1351976958

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In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language. This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics, but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases, the Anaconda Python distribution, graphical libraries like Bokeh, and the use of Github for collaborative development.


Bioinformatics Data Skills

Bioinformatics Data Skills

Author: Vince Buffalo

Publisher: "O'Reilly Media, Inc."

Published: 2015-07

Total Pages: 538

ISBN-13: 1449367518

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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