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Managing Your Biological Data with Python

2014-03-18 Science
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Release : 2014-03-18
Genre : Science
Kind : eBook
Book Rating : 93X/5 ( reviews)

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Book Synopsis Managing Your Biological Data with Python by : Allegra Via

Download or read book Managing Your Biological Data with Python written by Allegra Via. This book was released on 2014-03-18. Available in PDF, EPUB and Kindle. Book excerpt: Take Control of Your Data and Use Python with Confidence Requiring 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 to read data from files in different formats, analyze and manipulate the data, and write the results to a file or computer screen. The first part of the text introduces the Python language and teaches readers how to write their first programs. The second part presents the basic elements of the language, enabling readers to write small programs independently. The third part explains how to create bigger programs using techniques to write well-organized, efficient, and error-free code. The fourth part on data visualization shows how to plot data and draw a figure for an article or slide presentation. The fifth part covers the Biopython programming library for reading and writing several biological file formats, querying the NCBI online databases, and retrieving biological records from the web. The last part provides a cookbook of 20 specific programming "recipes," ranging from secondary structure prediction and multiple sequence alignment analyses to superimposing protein three-dimensional structures. Tailoring the programming topics to the everyday needs of biologists, the book helps them easily analyze data and ultimately make better discoveries. Every piece of code in the text is aimed at solving real biological problems.

Managing Your Biological Data with Python

2014-03-18 Computers
Download Managing Your Biological Data with Python PDF Online Free

Author :
Release : 2014-03-18
Genre : Computers
Kind : eBook
Book Rating : 948/5 ( reviews)

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Book Synopsis Managing Your Biological Data with Python by : Allegra Via

Download or read book Managing Your Biological Data with Python written by Allegra Via. This book was released on 2014-03-18. Available in PDF, EPUB and Kindle. Book excerpt: 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

Hands on Data Science for Biologists Using Python

2021-04-08 Computers
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Release : 2021-04-08
Genre : Computers
Kind : eBook
Book Rating : 483/5 ( reviews)

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Book Synopsis Hands on Data Science for Biologists Using Python by : Yasha Hasija

Download or read book Hands on Data Science for Biologists Using Python written by Yasha Hasija. This book was released on 2021-04-08. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Biological Data Exploration with Python, Pandas and Seaborn

2020-06-03
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Release : 2020-06-03
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Kind : eBook
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Book Synopsis Biological Data Exploration with Python, Pandas and Seaborn by : Martin Jones

Download or read book Biological Data Exploration with Python, Pandas and Seaborn written by Martin Jones. This book was released on 2020-06-03. Available in PDF, EPUB and Kindle. Book excerpt: In biological research, we''re currently in a golden age of data. It''s never been easier to assemble large datasets to probe biological questions. But these large datasets come with their own problems. How to clean and validate data? How to combine datasets from multiple sources? And how to look for patterns in large, complex datasets and display your findings? The solution to these problems comes in the form of Python''s scientific software stack. The combination of a friendly, expressive language and high quality packages makes a fantastic set of tools for data exploration. But the packages themselves can be hard to get to grips with. It''s difficult to know where to get started, or which sets of tools will be most useful. Learning to use Python effectively for data exploration is a superpower that you can learn. With a basic knowledge of Python, pandas (for data manipulation) and seaborn (for data visualization) you''ll be able to understand complex datasets quickly and mine them for biological insight. You''ll be able to make beautiful, informative charts for posters, papers and presentations, and rapidly update them to reflect new data or test new hypotheses. You''ll be able to quickly make sense of datasets from other projects and publications - millions of rows of data will no longer be a scary prospect! In this book, Dr. Jones draws on years of teaching experience to give you the tools you need to answer your research questions. Starting with the basics, you''ll learn how to use Python, pandas, seaborn and matplotlib effectively using biological examples throughout. Rather than overwhelm you with information, the book concentrates on the tools most useful for biological data. Full color illustrations show hundreds of examples covering dozens of different chart types, with complete code samples that you can tweak and use for your own work. This book will help you get over the most common obstacles when getting started with data exploration in Python. You''ll learn about pandas'' data model; how to deal with errors in input files and how to fit large datasets in memory. The chapters on visualization will show you how to make sophisticated charts with minimal code; how to best use color to make clear charts, and how to deal with visualization problems involving large numbers of data points. Chapters include: Getting data into pandas: series and dataframes, CSV and Excel files, missing data, renaming columns Working with series: descriptive statistics, string methods, indexing and broadcasting Filtering and selecting: boolean masks, selecting in a list, complex conditions, aggregation Plotting distributions: histograms, scatterplots, custom columns, using size and color Special scatter plots: using alpha, hexbin plots, regressions, pairwise plots Conditioning on categories: using color, size and marker, small multiples Categorical axes:strip/swarm plots, box and violin plots, bar plots and line charts Styling figures: aspect, labels, styles and contexts, plotting keywords Working with color: choosing palettes, redundancy, highlighting categories Working with groups: groupby, types of categories, filtering and transforming Binning data: creating categories, quantiles, reindexing Long and wide form: tidying input datasets, making summaries, pivoting data Matrix charts: summary tables, heatmaps, scales and normalization, clustering Complex data files: cleaning data, merging and concatenating, reducing memory FacetGrids: laying out multiple charts, custom charts, multiple heat maps Unexpected behaviours: bugs and missing groups, fixing odd scales High performance pandas: vectorization, timing and sampling Further reading: dates and times, alternative syntax

Introduction to Biological Data Analysis in Python

2023-03-17 Computers
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Release : 2023-03-17
Genre : Computers
Kind : eBook
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Book Synopsis Introduction to Biological Data Analysis in Python by : Stilianos Louca

Download or read book Introduction to Biological Data Analysis in Python written by Stilianos Louca. This book was released on 2023-03-17. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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