Difference between revisions of "User:Boris/Temp/APB"
m |
m |
||
Line 13: | Line 13: | ||
<td class="sc">'''Week'''</td> | <td class="sc">'''Week'''</td> | ||
<td class="sc">'''Date'''</td> | <td class="sc">'''Date'''</td> | ||
− | <td class="sc">''' | + | <td class="sc">'''Topics'''</td> |
<td class="sc">'''Activities'''</td> | <td class="sc">'''Activities'''</td> | ||
<td class="sc">'''Assignment'''</td> | <td class="sc">'''Assignment'''</td> | ||
Line 22: | Line 22: | ||
<td class="sc">Jan. 9 - 14</td> | <td class="sc">Jan. 9 - 14</td> | ||
<td class="sc"> | <td class="sc"> | ||
+ | Computational Biology aims to bring biology from its descriptive beginnings to a truly predictive science, based on consistent and well understood principles. In the systems biology field of computational biology, we deal primarily with large-scale, cross-sectional data, its relationships and hierarchies. | ||
+ | * Course Organisation | ||
* [[CSB_Introduction|Introduction to Computational Systems Biology]] | * [[CSB_Introduction|Introduction to Computational Systems Biology]] | ||
− | |||
</td> | </td> | ||
<td class="sc">—</td> | <td class="sc">—</td> | ||
Line 29: | Line 30: | ||
</tr> | </tr> | ||
− | <!-- =================== | + | <!-- =================== THEME =================== --> |
<tr><td colspan="5" class="sp"> </td></tr> | <tr><td colspan="5" class="sp"> </td></tr> | ||
<tr class="st"> | <tr class="st"> | ||
Line 37: | Line 38: | ||
<td class="sc">'''Week'''</td> | <td class="sc">'''Week'''</td> | ||
<td class="sc">'''Date'''</td> | <td class="sc">'''Date'''</td> | ||
− | <td class="sc">''' | + | <td class="sc">'''Topics'''</td> |
<td class="sc">'''Activities'''</td> | <td class="sc">'''Activities'''</td> | ||
<td class="sc">'''Assignment'''</td> | <td class="sc">'''Assignment'''</td> | ||
</tr> | </tr> | ||
− | <!-- =================== / | + | <!-- =================== /THEME =================== --> |
<tr class="s1"> | <tr class="s1"> | ||
Line 47: | Line 48: | ||
<td class="sc">Jan. 16 - 21</td> | <td class="sc">Jan. 16 - 21</td> | ||
<td class="sc"> | <td class="sc"> | ||
− | + | In principle, most of the data of interest to us is freely available on the Web, in public repositories. However, the number of databases and associated Web services is large and in constant flux and integrating the data has its own issues. The most important issue is the question of how to define ''function'' and make this concept computable; from this arises the central role that ontologies play in the field. | |
− | + | * [[CSB_Web_tools|CSB on the Web: Databases and services]] | |
− | + | * [[Data_integration|Data integration]] | |
− | + | * [[CSB_Ontologies|GO, OMIM and other phenotype databases]] | |
− | + | * [[Function_prediction|Prediction of function]] | |
</td> | </td> | ||
<td class="sc">Quiz 1</td> | <td class="sc">Quiz 1</td> | ||
Line 61: | Line 62: | ||
<td class="sc">Jan. 23 - 28</td> | <td class="sc">Jan. 23 - 28</td> | ||
<td class="sc"> | <td class="sc"> | ||
− | * Working with -ome scale data | + | The large volume of data in any given systems biology experiment basically precludes the manual, gene-by-gene analysis of results. Questions arise regarding computational strategies for ''gene lists'', especially the statistical tools and strategies we have at our disposal, and a minimum set of programming and automation skills. |
− | ** [[Enrichment|Enrichment analysis]] | + | * Working with -ome scale data |
− | ** [[Statistics|Principles of Statistics in molecular biology | + | ** [[CSB Gene lists|Gene lists]] |
− | *** [[R]] | + | ** [[Enrichment|Enrichment analysis]] |
+ | ** [[GSEA|The GSEA approach]] | ||
+ | ** Statistics | ||
+ | *** [[Statistics|Principles of Statistics in molecular biology]] | ||
+ | *** [[R]] | ||
+ | *** [[Bioconductor]] | ||
*** [[Clustering|Clustering and Classification]] | *** [[Clustering|Clustering and Classification]] | ||
+ | *** [[EDA|Exploratory Data Analysis]] | ||
*** [[Data_mining|Data mining]] | *** [[Data_mining|Data mining]] | ||
− | ** [[Informal_programming|Informal programming | + | ** Programming |
− | *** [[IDE|Integrated Development Environments]] | + | *** [[Informal_programming|Informal programming]] |
+ | *** [[IDE|Using an IDE (Integrated Development Environments)]] | ||
</td> | </td> | ||
<td class="sc">Quiz 2, project concept due</td> | <td class="sc">Quiz 2, project concept due</td> | ||
Line 75: | Line 83: | ||
− | <!-- =================== | + | <!-- =================== THEME =================== --> |
<tr><td colspan="5" class="sp"> </td></tr> | <tr><td colspan="5" class="sp"> </td></tr> | ||
<tr class="st"> | <tr class="st"> | ||
Line 84: | Line 92: | ||
<td class="sc">'''Week'''</td> | <td class="sc">'''Week'''</td> | ||
<td class="sc">'''Date'''</td> | <td class="sc">'''Date'''</td> | ||
− | <td class="sc">''' | + | <td class="sc">'''Topics'''</td> |
<td class="sc">'''Activities'''</td> | <td class="sc">'''Activities'''</td> | ||
<td class="sc">'''Assignment'''</td> | <td class="sc">'''Assignment'''</td> | ||
</tr> | </tr> | ||
− | <!-- =================== / | + | <!-- =================== /THEME =================== --> |
<tr class="s2"> | <tr class="s2"> | ||
Line 94: | Line 102: | ||
<td class="sc">Jan. 30 - Feb. 3</td> | <td class="sc">Jan. 30 - Feb. 3</td> | ||
<td class="sc"> | <td class="sc"> | ||
+ | Genome sequencing brought the first complete overview of the information underlying life; the associated concept of the ''transcriptome'' - a description of which portion of the genome is expressed at what time - is the most basic ''functional'' description of this information. | ||
* [[Genomics|Genome]] | * [[Genomics|Genome]] | ||
* [[Transcriptome|Transcriptome]] | * [[Transcriptome|Transcriptome]] | ||
Line 105: | Line 114: | ||
<td class="sc">Feb. 6 - 10</td> | <td class="sc">Feb. 6 - 10</td> | ||
<td class="sc"> | <td class="sc"> | ||
+ | Many more holistic, or cross-sectional descriptions of the molecular construction of the cell are being worked on. | ||
* [[Proteome|Proteome]] | * [[Proteome|Proteome]] | ||
− | |||
* [[Metabolome|Metabolome]] | * [[Metabolome|Metabolome]] | ||
* [[Glycome|Glycome]] | * [[Glycome|Glycome]] | ||
Line 115: | Line 124: | ||
</tr> | </tr> | ||
− | <!-- =================== | + | <!-- =================== THEME =================== --> |
<tr><td colspan="5" class="sp"> </td></tr> | <tr><td colspan="5" class="sp"> </td></tr> | ||
<tr class="st"> | <tr class="st"> | ||
Line 124: | Line 133: | ||
<td class="sc">'''Week'''</td> | <td class="sc">'''Week'''</td> | ||
<td class="sc">'''Date'''</td> | <td class="sc">'''Date'''</td> | ||
− | <td class="sc">''' | + | <td class="sc">'''Theme'''</td> |
<td class="sc">'''Activities'''</td> | <td class="sc">'''Activities'''</td> | ||
<td class="sc">'''Assignment'''</td> | <td class="sc">'''Assignment'''</td> | ||
</tr> | </tr> | ||
− | <!-- =================== / | + | <!-- =================== /THEME =================== --> |
<tr class="s1"> | <tr class="s1"> | ||
Line 134: | Line 143: | ||
<td class="sc">Feb. 13 - 17</td> | <td class="sc">Feb. 13 - 17</td> | ||
<td class="sc"> | <td class="sc"> | ||
− | + | Fundamentally, ''-omics'' descriptions provide us with lists of components. However, to understand how things work, we need to address the ''relationships'' of the components - how things are put together: the molecular blueprints. At its most basic level, this is the question of molecular interactions in the cell. A quantitative description of molecular interactions relies heavily on the mathematical discipline of ''graph theory''. ''Cytoscape'' is a visualization and analysis platform for molecular interactions. | |
− | * [[ | + | * [[Graph_theory|Graph theory]] |
* [[Cytoscape|Cytoscape]] | * [[Cytoscape|Cytoscape]] | ||
</td> | </td> | ||
Line 152: | Line 161: | ||
<td class="sc">Feb. 27 - Mar. 2</td> | <td class="sc">Feb. 27 - Mar. 2</td> | ||
<td class="sc"> | <td class="sc"> | ||
− | * [[ | + | Here we focus on the biological objects of "Interaction Science". |
− | * [[Interaction_prediction|Interaction prediction]] | + | * [[Interactome|The Interactome]] |
+ | * [[Interaction_databases|Interaction databases]] | ||
+ | * [[Pathways_and_Networks|Pathways and Networks]] | ||
+ | * [[Interaction_prediction|Interaction prediction]] | ||
</td> | </td> | ||
<td class="sc">Quiz 6</td> | <td class="sc">Quiz 6</td> | ||
Line 159: | Line 171: | ||
</tr> | </tr> | ||
− | <!-- =================== | + | <!-- =================== THEME =================== --> |
<tr><td colspan="5" class="sp"> </td></tr> | <tr><td colspan="5" class="sp"> </td></tr> | ||
<tr class="st"> | <tr class="st"> | ||
Line 168: | Line 180: | ||
<td class="sc">'''Week'''</td> | <td class="sc">'''Week'''</td> | ||
<td class="sc">'''Date'''</td> | <td class="sc">'''Date'''</td> | ||
− | <td class="sc">''' | + | <td class="sc">'''Topics'''</td> |
<td class="sc">'''Activities'''</td> | <td class="sc">'''Activities'''</td> | ||
<td class="sc">'''Assignment'''</td> | <td class="sc">'''Assignment'''</td> | ||
</tr> | </tr> | ||
− | <!-- =================== / | + | <!-- =================== /THEME =================== --> |
<tr class="s1"> | <tr class="s1"> | ||
Line 178: | Line 190: | ||
<td class="sc">Mar. 5 - 9</td> | <td class="sc">Mar. 5 - 9</td> | ||
<td class="sc"> | <td class="sc"> | ||
− | * [[Gene_regulatory_networks|Gene regulatory networks]] | + | Several key networked systems exist in the cell. Here we discuss their paradigms, how they are constructed from experimental data and examples of how they can be organized in databases. |
+ | * [[Gene_regulatory_networks|Gene regulatory networks]] | ||
+ | * [[Metabolic_networks|Metabolic networks]] | ||
* [[Signal_transduction_networks|Signal transduction networks]] | * [[Signal_transduction_networks|Signal transduction networks]] | ||
− | * [[ | + | * [[Developmental_networks|Developmental networks]] |
− | * [[KEGG]] | + | * Pathway and network databases |
+ | ** [[KEGG]] | ||
+ | ** [[BioCYC]] | ||
</td> | </td> | ||
<td class="sc">Quiz 7</td> | <td class="sc">Quiz 7</td> | ||
Line 191: | Line 207: | ||
<td class="sc">Mar. 12 - 16</td> | <td class="sc">Mar. 12 - 16</td> | ||
<td class="sc"> | <td class="sc"> | ||
− | * [[CSB_Mutual information|Extracting systems from -omics datasets through mutual information]] | + | Information theory has proven to be one of the cornerstones of biological analysis. A good example of its power and utility is the definition of systems in large-scale biological datasets. |
+ | * [[CSB_Mutual information|Extracting systems from ''-omics'' datasets through mutual information]] | ||
</td> | </td> | ||
<td class="sc">Quiz 8</td> | <td class="sc">Quiz 8</td> | ||
Line 201: | Line 218: | ||
<td class="sc">Mar. 19 - 23</td> | <td class="sc">Mar. 19 - 23</td> | ||
<td class="sc"> | <td class="sc"> | ||
− | * [[Systems dynamics|Systems dynamics]] | + | Life is not static, only death is. Yet, the dynamic nature of biological systems is often overlooked. |
+ | * [[Systems dynamics|Systems dynamics]] | ||
</td> | </td> | ||
<td class="sc">Quiz 9, project final submission due</td> | <td class="sc">Quiz 9, project final submission due</td> | ||
Line 207: | Line 225: | ||
</tr> | </tr> | ||
− | <!-- =================== | + | <!-- =================== THEME =================== --> |
<tr><td colspan="5" class="sp"> </td></tr> | <tr><td colspan="5" class="sp"> </td></tr> | ||
<tr class="st"> | <tr class="st"> | ||
Line 216: | Line 234: | ||
<td class="sc">'''Week'''</td> | <td class="sc">'''Week'''</td> | ||
<td class="sc">'''Date'''</td> | <td class="sc">'''Date'''</td> | ||
− | <td class="sc">''' | + | <td class="sc">'''Theme'''</td> |
<td class="sc">'''Activities'''</td> | <td class="sc">'''Activities'''</td> | ||
<td class="sc">'''Assignment'''</td> | <td class="sc">'''Assignment'''</td> | ||
</tr> | </tr> | ||
− | <!-- =================== / | + | <!-- =================== /THEME =================== --> |
<tr class="s1"> | <tr class="s1"> | ||
Line 226: | Line 244: | ||
<td class="sc">Mar. 26 - 30</td> | <td class="sc">Mar. 26 - 30</td> | ||
<td class="sc"> | <td class="sc"> | ||
+ | The notion that computational biology will at some time become redictive is tied to the idea that we will be able to model the cell's systems. Many approaches exist, each with its own strengths and weaknesses; how to integrate such models, preferrably | ||
* [[CSB_modelling_principles|Modelling principles]]: | * [[CSB_modelling_principles|Modelling principles]]: | ||
* [[CSB_modelling_methods|Modelling methods]]: | * [[CSB_modelling_methods|Modelling methods]]: | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
* [[CSB_model_representations|Model representations]] (SBML, CellML) | * [[CSB_model_representations|Model representations]] (SBML, CellML) | ||
− | * [[ | + | * [[CSB_modelling_examples|Modelling examples]] |
</td> | </td> | ||
<td class="sc">—</td> | <td class="sc">—</td> |
Revision as of 17:36, 27 January 2012
Timetable and syllabus
I n t r o d u c t i o n | ||||
Week | Date | Topics | Activities | Assignment |
1 | Jan. 9 - 14 |
Computational Biology aims to bring biology from its descriptive beginnings to a truly predictive science, based on consistent and well understood principles. In the systems biology field of computational biology, we deal primarily with large-scale, cross-sectional data, its relationships and hierarchies.
|
— | Assignment 1 |
D a t a | ||||
Week | Date | Topics | Activities | Assignment |
2 | Jan. 16 - 21 |
In principle, most of the data of interest to us is freely available on the Web, in public repositories. However, the number of databases and associated Web services is large and in constant flux and integrating the data has its own issues. The most important issue is the question of how to define function and make this concept computable; from this arises the central role that ontologies play in the field. |
Quiz 1 | Assignment 2 |
3 | Jan. 23 - 28 |
The large volume of data in any given systems biology experiment basically precludes the manual, gene-by-gene analysis of results. Questions arise regarding computational strategies for gene lists, especially the statistical tools and strategies we have at our disposal, and a minimum set of programming and automation skills.
|
Quiz 2, project concept due | Assignment 3 |
"-omics" | ||||
Week | Date | Topics | Activities | Assignment |
4 | Jan. 30 - Feb. 3 |
Genome sequencing brought the first complete overview of the information underlying life; the associated concept of the transcriptome - a description of which portion of the genome is expressed at what time - is the most basic functional description of this information. |
Quiz 3 | Assignment 4 |
5 | Feb. 6 - 10 |
Many more holistic, or cross-sectional descriptions of the molecular construction of the cell are being worked on. |
Quiz 4, project outline due | Assignment 5 |
I n t e r a c t i o n s , P a t h w a y s a n d N e t w o r k s | ||||
Week | Date | Theme | Activities | Assignment |
6 | Feb. 13 - 17 |
Fundamentally, -omics descriptions provide us with lists of components. However, to understand how things work, we need to address the relationships of the components - how things are put together: the molecular blueprints. At its most basic level, this is the question of molecular interactions in the cell. A quantitative description of molecular interactions relies heavily on the mathematical discipline of graph theory. Cytoscape is a visualization and analysis platform for molecular interactions. |
Quiz 5 | Assignment 6 |
Feb. 20 - 24 | Reading Week - School closed | |||
7 | Feb. 27 - Mar. 2 |
Here we focus on the biological objects of "Interaction Science". |
Quiz 6 | Assignment 7 |
S y s t e m s | ||||
Week | Date | Topics | Activities | Assignment |
8 | Mar. 5 - 9 |
Several key networked systems exist in the cell. Here we discuss their paradigms, how they are constructed from experimental data and examples of how they can be organized in databases.
|
Quiz 7 | Assignment 8 |
9 | Mar. 12 - 16 |
Information theory has proven to be one of the cornerstones of biological analysis. A good example of its power and utility is the definition of systems in large-scale biological datasets. |
Quiz 8 | Assignment 9 |
10 | Mar. 19 - 23 |
Life is not static, only death is. Yet, the dynamic nature of biological systems is often overlooked. |
Quiz 9, project final submission due | Assignment 10 |
M o d e l s | ||||
Week | Date | Theme | Activities | Assignment |
11 | Mar. 26 - 30 |
The notion that computational biology will at some time become redictive is tied to the idea that we will be able to model the cell's systems. Many approaches exist, each with its own strengths and weaknesses; how to integrate such models, preferrably
|
— | Assignment 11 |
12 | Apr. 2 - 6 | — | Assignment 12 |