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Gephi 0.9 released: Graph visualization software for networks

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Re: Gephi 0.9 released: Graph visualization software for networks

#2
Thanks to the Gephi team for this long-awaited update - for me, Gephi an essential tool in many aspects of my scientific work, as it allows to express visually very complex datasets of almost any type (interactions between proteins, binding of certain genomic elements, etc) as well as overlay by color or size additional parameters (expression of genes, conservation, mutation rate in the population) - endless possibilities!

From my initial impressions the performance is A LOT better for large networks, which can mean only one thing - I can now play with even LARGER networks :)

Re: Gephi 0.9 released: Graph visualization software for networks

#4

Thanks to the Gephi team for this long-awaited update - for me, Gephi an essential tool in many aspects of my scientific work, as it allows to express visually very complex datasets of almost any type (interactions between proteins, binding of certain genomic elements, etc) as well as overlay by color or size additional parameters (expression of genes, conservation, mutation rate in the population) - endless possibil…

Roughly what size networks can you actually get useful information for? Every time I play with Gephi using any network of reasonable size (in my field), it's always a giant useless hairball.

Re: Gephi 0.9 released: Graph visualization software for networks

#7
post #4

Thanks to the Gephi team for this long-awaited update - for me, Gephi an essential tool in many aspects of my scientific work, as it allows to express visually very complex datasets of almost any type (interactions between proteins, binding of certain genomic elements, etc) as well as overlay by color or size additional parameters (expression of genes, conservation, mutation rate in the population) - endless possibil…

Roughly what size networks can you actually get useful information for? Every time I play with Gephi using any network of reasonable size (in my field), it's always a giant useless hairball.

I have tested a few layout algorithms in Gephi for networks with ~200K nodes. It becomes slow but does work.

Re: Gephi 0.9 released: Graph visualization software for networks

#8
post #4

Thanks to the Gephi team for this long-awaited update - for me, Gephi an essential tool in many aspects of my scientific work, as it allows to express visually very complex datasets of almost any type (interactions between proteins, binding of certain genomic elements, etc) as well as overlay by color or size additional parameters (expression of genes, conservation, mutation rate in the population) - endless possibil…

Roughly what size networks can you actually get useful information for? Every time I play with Gephi using any network of reasonable size (in my field), it's always a giant useless hairball.

That's due to the network structure rather than the size. Maybe you can strip/split it to sub-'questions' or weigh nodes or edges?

Re: Gephi 0.9 released: Graph visualization software for networks

#9

"Since the last release in 2013, users were facing compatibility issues with Java, which have been resolved with this release." Finally, I've struggled with this for months on a few different computers.

Thank you for this comment, I may give it another try.

Re: Gephi 0.9 released: Graph visualization software for networks

#10
post #4

Thanks to the Gephi team for this long-awaited update - for me, Gephi an essential tool in many aspects of my scientific work, as it allows to express visually very complex datasets of almost any type (interactions between proteins, binding of certain genomic elements, etc) as well as overlay by color or size additional parameters (expression of genes, conservation, mutation rate in the population) - endless possibil…

Roughly what size networks can you actually get useful information for? Every time I play with Gephi using any network of reasonable size (in my field), it's always a giant useless hairball.

50-100k nodes, as posters above said, it's very variable on the network structure, but for me I get highly information clusters. Try increasing your cutoff for interaction via edge weight might help.