Question: Network comparison by using network topological features.
3
gravatar for Bioinformatist Newbie
3.7 years ago by
Germany
Bioinformatist Newbie230 wrote:

I want to find disease drug relationship by using network based approaches. Up til now I was using individual network properties like Strongly connected components (SCC), Betweeness Centrality,  transitivity, network diameter and Miniminum dominating set (MDS) but none of these characteristics are yielding the results I am interested in. As example on which I am trying this idea are known (I know the drug causing the phenotype reversion in Gene expression).

Can anybody devise me some other network topology properties like I mentioned, which can be use to compare networks inferred from Gene Expression data?

Secondly I am thinking about combining mentioned features to train the random forest for classification, is it a good idea? If yes, then do share your your experience.

Thanks. 

ADD COMMENTlink modified 3.7 years ago by Zhilong Jia1.4k • written 3.7 years ago by Bioinformatist Newbie230
1
gravatar for Girolamo
3.7 years ago by
Girolamo140
Italia
Girolamo140 wrote:

Regarding the first question, you can have a look for algorithm for exact and quasi-exact network (sub)isomorphism ( VF2 is one of the most used for exact subgraph isomorphism and is already implemented in networkx library for python), or network alignment ( http://www.ncbi.nlm.nih.gov/pubmed/22234340 ). 

ADD COMMENTlink modified 3.7 years ago by pld4.8k • written 3.7 years ago by Girolamo140

The link you provided doesn't work, can you please correct this?

ADD REPLYlink written 3.7 years ago by pld4.8k

Just remove the last bracket and it'll work. http://www.ncbi.nlm.nih.gov/pubmed/22234340

ADD REPLYlink written 3.7 years ago by Bioinformatist Newbie230
1
gravatar for Zhilong Jia
3.7 years ago by
Zhilong Jia1.4k
London
Zhilong Jia1.4k wrote:

Another one, Network fingerprint: a knowledge-based characterization of biomedical networks may be helpful.

ADD COMMENTlink modified 3.7 years ago • written 3.7 years ago by Zhilong Jia1.4k
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