One of my favourite graphics site:

http://cytoscape-publications.tumblr.com/

One visualization library related to chip-chip and chip-seq data, is the hilbertviz package.

See the R/Bioconductor View for visualization. I especially like GenomeGraphs.

You should also consider matplotlib

Hi,

I just dug a bit into my delicious bookmarks and found this few resources.

• The useful palette of R colours
• A list of underused but useful data visualization
• Rgraphviz, to plot graphs with R or here
• Gephi, an open source and free software to plot complex graphs
• A great list of resources for data visualization for many different programming languages

I hope this helped.

BALLView for a range of molecular modelling and visualization applications. One from their Gallery:

Here are some generic ones:

simple graph with r

quick-R

Specialized:

R / heat map plot

R / Manhattan plot

I've been using d3.js a lot. It's a great javascript library that you can use to create charts and diagrams in SVG format. Add Firebug or Chrome's console abilities, and you have a really nice method of creating your figures because you can step through your code and debug easily with the visual changes reflected instantly.

Here is a great beginner's tutorial for it assuming you have some knowledge of browser languages:

http://www.recursion.org/d3-for-mere-mortals/

Here is a really great video tutorial:

http://vimeo.com/35005701

Some python libraries:

• matplotlib
• networkx library (for networks and graph only)

Also, colorbrewer, pointed by russH, is a resource to choose good color palettes. It is useful when you have to draw a graph of some data and you want to know which colors to choose.

I think you wish (like me) that you had attended the Vizbi conference last week in Heidelberg: http://vizbi.org/

I think their unofficial aim is to increase the beauty of science :)

Luckily they have already uploaded some beautiful posters & I'm sure that some amazing talks will be uploaded too.

There are two resources by Publishing Houses, that provide image search in articles. One from Springer - SpringerImages. Second is from Cell - CellImageLibrary. Of course they do have bioinformatics images.

If using python, consider the seaborn package (gallery here) which is built on top of matplotlib. It includes heatmaps, many statistical plots including linear models, mult-faceted/grid plotting, and color palettes (including colorbrewer). It leverages the pandas DataFrame object to make it easier for plotting then standard matplotlib. Personally, I like the figure aesthetics more than ggplot2.

For color palette selection of charts, I use: IWantHue "Colors for data scientists"

They do k-means clustering of colors in a selected range to achieve maximum divergence between the individual colors. However, you can keep colors and re-cluster and similar thing to make it suit your needs.

If you want to create animations or explore high-dimensional data, GGobi is the tool to use. You can use it in R (package "rggobi") which is a great convenience. I would highly recommend a visit to r-forge, where you can search through lots of interesting projects with a wide range of bioinformatics applications.

For general plotting, you should consider GD, though you probably already have it if you generate graphics in BioPerl. Since you mentioned Perl, there is a great list of relevant modules on CPAN.

Though Its not related directly to Bioinformatics, still this site shows 50 great data vizualizations. We can implement these ideas on bioinformatics data with any of the tools listed above.

http://www.webdesignerdepot.com/2009/06/50-great-examples-of-data-visualization/

I am developping a new R graph gallery. Have a look to

http://www.r-graph-gallery.com

All the best !

You can use PathwayBuilder at http://www.proteinlounge.com or ePath3D which is available at the same site.

Dear John,

I wrote this program to help me in my research: http://i-pv.org/

In a nutshell: it displays most protein features you can think of in an interactive interface that works for PC/mobile.

Here is an example: http://i-pv.org/FOXP2.html

Here you will find more examples and tutorial videos: http://i-pv.org/ipv_minimal.html

Regards

Rcharts looks pretty cool. It's not really specific to bioinformatics though.
http://rcharts.io/gallery/