dc.contributor.author |
O'Neil, Shawn T. |
|
dc.creator |
O'Neil, Shawn T. |
|
dc.date.accessioned |
2020-09-02T18:00:26Z |
|
dc.date.available |
2020-09-02T18:00:26Z |
|
dc.date.issued |
2017 |
|
dc.identifier |
4f0f3b91-e7ad-4791-b3f5-9bd1014c943e |
|
dc.identifier.isbn |
9780870719264 |
|
dc.identifier.uri |
https://openlibrary-repo.ecampusontario.ca/jspui/handle/123456789/831 |
|
dc.description.tableofcontents |
I. Introduction to Unix/Linux |
|
dc.description.tableofcontents |
II. Programming in Python |
|
dc.description.tableofcontents |
III. Programming in R |
|
dc.language.iso |
eng |
en_US |
dc.publisher |
Oregon State University Press |
|
dc.relation.isformatof |
https://open.oregonstate.education/computationalbiology/ |
|
dc.relation.haspart |
Student Resources: Data files and Scripts | https://open.oregonstate.education/computationalbiology/back-matter/files/ |
|
dc.rights |
CC BY-NC-SA | https://creativecommons.org/licenses/by-nc-sa/4.0/ |
en_US |
dc.subject |
Computational biology / bioinformatics |
|
dc.title |
A Primer for Computational Biology |
en_US |
dc.type |
Book |
|
dc.type |
Other |
|
dc.type |
Software |
|
dcterms.accessRights |
Open Access |
|
dcterms.educationLevel |
Adult and Continuing Education |
|
dcterms.educationLevel |
University - Undergraduate |
|
dc.identifier.slug |
https://openlibrary.ecampusontario.ca/catalogue/item/?id=4f0f3b91-e7ad-4791-b3f5-9bd1014c943e |
|
ecO-OER.Adopted |
Yes |
|
ecO-OER.AncillaryMaterial |
Yes |
|
ecO-OER.InstitutionalAffiliation |
Oregon State University |
en_US |
ecO-OER.ISNI |
0000 0001 2112 1969 |
|
ecO-OER.Reviewed |
No |
|
ecO-OER.AccessibilityStatement |
Unknown |
|
lrmi.learningResourceType |
Learning Resource - Textbook |
|
lrmi.learningResourceType |
Learning Resource - Data/Dataset |
|
lrmi.learningResourceType |
Learning Resource - Software |
|
ecO-OER.POD.compatible |
Yes |
|
dc.description.abstract |
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: 1. 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. -- 2. 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. -- 3. 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. |
en_US |
dc.subject.other |
Sciences - Biology |
|
dc.subject.other |
Technology - Programming & Programs |
|
dc.subject.other |
Technology - Research & Data |
|
ecO-OER.ItemType |
Textbook |
|
ecO-OER.MediaFormat |
eBook |
|
ecO-OER.MediaFormat |
HTML/XML |
|
ecO-OER.MediaFormat |
PDF |
|