Difference between revisions of "CSB Assignment Week 5"
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| − | Assignments for Week | + | Assignments for Week 5<br/> |
| + | <span style="font-size: 70%">Graphs !</span> | ||
</div> | </div> | ||
| + | <table style="width:100%;"><tr> | ||
| + | <td style="height:30px; vertical-align:middle; text-align:left; font-size:80%;">[[CSB_Assignment_Week_4|< Assignment 4]]</td> | ||
| + | <td style="height:30px; vertical-align:middle; text-align:right; font-size:80%;">[[CSB_Assignment_Week_6|Assignment 6 >]]</td> | ||
| + | </tr></table> | ||
| + | |||
| + | {{Active}} | ||
| + | |||
| + | |||
| + | <!-- | ||
Exercises for this week relate to this week's lecture.<br /> | Exercises for this week relate to this week's lecture.<br /> | ||
Pre-reading for this week will prepare next week's lecture.<br /> | Pre-reading for this week will prepare next week's lecture.<br /> | ||
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__TOC__ | __TOC__ | ||
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| + | __NOTOC__ | ||
| + | <!-- | ||
==Exercises== | ==Exercises== | ||
| + | {{#lst:R_expression_analysis|exercises}} | ||
| + | --> | ||
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| + | ==Pre-reading== | ||
| + | |||
| + | This paper is a good crash-course in concepts of graph theory and their application to biology. It contains a lot of definitions that I don't expect you to learn by heart. But do familiarize yourself with the concepts - they are important to properly work with the '''R''' graph tutorial. | ||
| + | |||
| + | {{#lst:Graph_theory|reading}} | ||
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| + | {{Vspace}} | ||
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| + | ==An '''R''' tutorial on biological graphs== | ||
| + | |||
| + | {{task|1= | ||
| + | |||
| + | Graph theory has so many applications in computational systems biology that being able to compute with graphs in '''R''' is a phantastic asset. This brief tutorial reviews the basics and then covers the igraph package in some detail. It concludes with an exploration of the graph of functional relationships of human proteins from the STRING database. | ||
| + | |||
| + | |||
| + | * Open RStudio | ||
| + | * Select '''File → New Project ...''' | ||
| + | * Choose '''Version control → Git ''' | ||
| + | * Enter the repository URL for the tutorial: https://github.com/hyginn/R_Exercise-Graphs | ||
| + | * Click on '''Create Project'''. | ||
| + | * Start the tutorial by typing <code>init()</code> | ||
| + | }} | ||
| − | |||
| + | ;Note - This tutorial has a hand-in component that will replace the quiz: | ||
| + | : ''" - Find the nodes with the 10 - highest betweenness centralities. Use centr_betw() to calculate the values, V() to get the names, and how many nodes there are. The N - 10 highest ranked nodes is what you are looking for. Get the list of IDs. Then find what these proteins are..."'' | ||
| − | + | Bring with you to class: | |
| + | * a list of these protein IDs, | ||
| + | * with a brief annotation what they are (use STRING, or ensembl to get a synopsis), | ||
| + | * and a short paragraph of why this is remarkable - or not. | ||
| + | |||
| + | |||
| + | |||
| + | {{Vspace}} | ||
| + | {{#lst:CSB_Assignment_Week_1|assignment_footer}} | ||
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| + | <table style="width:100%;"><tr> | ||
| + | <td style="height:30px; vertical-align:middle; text-align:left; font-size:80%;">[[CSB_Assignment_Week_4|< Assignment 4]]</td> | ||
| + | <td style="height:30px; vertical-align:middle; text-align:right; font-size:80%;">[[CSB_Assignment_Week_6|Assignment 6 >]]</td> | ||
| + | </tr></table> | ||
[[Category:Computational_Systems_Biology]] | [[Category:Computational_Systems_Biology]] | ||
</div> | </div> | ||
Latest revision as of 02:20, 1 March 2016
Assignments for Week 5
Graphs !
| < Assignment 4 | Assignment 6 > |
Note! This assignment is currently active. All significant changes will be announced on the mailing list.
Pre-reading
This paper is a good crash-course in concepts of graph theory and their application to biology. It contains a lot of definitions that I don't expect you to learn by heart. But do familiarize yourself with the concepts - they are important to properly work with the R graph tutorial.
| Pavlopoulos et al. (2011) Using graph theory to analyze biological networks. BioData Min 4:10. (pmid: 21527005) |
|
[ PubMed ] [ DOI ] Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system. |
An R tutorial on biological graphs
Task:
Graph theory has so many applications in computational systems biology that being able to compute with graphs in R is a phantastic asset. This brief tutorial reviews the basics and then covers the igraph package in some detail. It concludes with an exploration of the graph of functional relationships of human proteins from the STRING database.
- Open RStudio
- Select File → New Project ...
- Choose Version control → Git
- Enter the repository URL for the tutorial: https://github.com/hyginn/R_Exercise-Graphs
- Click on Create Project.
- Start the tutorial by typing
init()
- Note - This tutorial has a hand-in component that will replace the quiz
- " - Find the nodes with the 10 - highest betweenness centralities. Use centr_betw() to calculate the values, V() to get the names, and how many nodes there are. The N - 10 highest ranked nodes is what you are looking for. Get the list of IDs. Then find what these proteins are..."
Bring with you to class:
- a list of these protein IDs,
- with a brief annotation what they are (use STRING, or ensembl to get a synopsis),
- and a short paragraph of why this is remarkable - or not.
- That is all.
Footnotes and references
- Ask, if things don't work for you!
- If anything about the assignment is not clear to you, please ask on the mailing list. You can be certain that others will have had similar problems. Success comes from joining the conversation.
- Do consider how to ask your questions so that a meaningful answer is possible. the following two links:
- How to create a Minimal, Complete, and Verifiable example on stackoverflow and ...
- How to make a great R reproducible example
- ... are required reading.
| < Assignment 4 | Assignment 6 > |
