Developing Bioinformatics Computer Skills


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Developing Bioinformatics Computer Skills


Developing Bioinformatics Computer Skills

Author: Cynthia Gibas

language: en

Publisher: "O'Reilly Media, Inc."

Release Date: 2001


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This practical, hands-on guide shows how to develop a structured approach to biological data and the tools needed to analyze it. It's aimed at scientists and students learning computational approaches to biological data, as well as experienced biology researchers starting to use computers to handle data.

Developing Bioinformatics Computer Skills


Developing Bioinformatics Computer Skills

Author: Cynthia Gibas

language: en

Publisher: Turtleback

Release Date: 2001-01-01


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Offers a structured approach to biological data and the computer tools needed to analyze it, covering UNIX, databases, computation, Perl, data mining, data visualization, and tailoring software to suit specific research needs.

Bioinformatics Data Skills


Bioinformatics Data Skills

Author: Vince Buffalo

language: en

Publisher: "O'Reilly Media, Inc."

Release Date: 2015-07


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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