Biological networks Tutorial 12. Protein-Protein interactions –STRING Protein and genetic...

Biological networks

Tutorial 12

• Protein-Protein interactions– STRING

• Protein and genetic interactions– BioGRID

• Network visualization– Cytoscape

• Cool story of the day

How to model natural selection

Biological networks

Protein Protein interactions (PPI)

http://string-db.org/

http://string-db.org/


Will change according to the prediction method you choose.

Protein and genetic interactions

http://thebiogrid.org/

http://thebiogrid.org/

Protein and genetic interactions

Signaling pathways

Hearing and vision map

Network visualization - Cytoscape

http://www.cytoscape.org/

http://www.cytoscape.org/


The input is a tab delimited file:<Protein 1> <interaction type> <Protein 2>


Degree: the number of edges that a node has.

The node with the highest degree in the graph


Closeness: measure how close a node to all other nodes in the network.

The nodes with the highest closeness


The node with the highest betweenness

Betweenness: quantify the number of all shortest paths that pass through a node.


Know your network type:Directed – for regulatory networksUndirected – for protein-protein networks


(Analysis of another network)


Highest degree = bigHighest betweens = red


Cytoscape has ~200 plugins http://chianti.ucsd.edu/cyto_web/plugins/

http://chianti.ucsd.edu/cyto_web/plugins/

Cool Story of the day

How to model natural selection

Natural Selection

• Consider a biological system whose phenotypes are defined by v quantitative traits (such as bird beak length and not DNA sequences).

• Most theories of natural selection maximize a specific fitness function F(v) resulting in an optimal phenotype – a point in morpho-space.

• But, in many cases organisms need to perform multiple tasks that contribute to fitness.

The case two tasks

The case of a trade-off between two tasks may explain the widespread occurrence of linearrelations between traits.

The Pareto Front

Pareto front geometry

For three tasks, the Pareto front is the full triangle whose vertices are the three archetypes. In this case, because a triangle defines a plane, even high dimensional data on many traits are expected to collapse onto two dimensions.

The closer a point is to one of the vertices of the triangle, the more important the corresponding task is to fitness inthe organism’s habitat.

Evidence for triangular suites of variation in classic studies

Bacteria face a trade-off in partitioning the total amount of proteins they can make at a given moment between the different types of proteins, that ishow much of each gene to express.

Trade-off: rapid growth (ribosomes) vs. survival (stress response proteins)

Beyond animal morphology

Corr. of the top 200 temporally varying genes

E.coli promoter activity

Promoter activity of 3 genes at different time points

Thank you!Hope you enjoyed the course!!

Biological networks Tutorial 12. Protein-Protein interactions –STRING Protein and genetic...

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