This site contains supplementary information to the paper:

 

V. Varadan, D. Miller III and D. Anastassiou, “Computational Inference of the Molecular Logic for Synaptic Connectivity in C. elegans,” Bioinformatics, volume 22, issue 14 – ISMB 2006, pp. e497-506.

 

Please make reference to the above paper in any publication for which you make use of any data or software from this website, which will be updated and maintained to include newer versions of the matrices E, A, B, as well as related software.

 

The ISMB 2006 paper connects the neural wiring diagram with the single-neuron transcriptome of C. elegans using a systems-based computational approach known as EMBP (entropy minimization and Boolean parsimony). It also introduces an information-theoretic analysis of the multivariate synergy of the joint expression levels of multiple genes with respect to a phenotype, which provides insight into the structure of pathways responsible for the phenotype.  An introduction to EMBP analysis is presented in the paper:

 

V. Varadan and D. Anastassiou, “Inference of Disease-Related Molecular Logic from Systems-Based Microarray Analysis,” PLoS Computational Biology, Vol. 2, Issue 6, e68, June 2006, pp. 585-597.

 

The latest versions of the expression matrix are available in the Mining WormBase for Expression Data section along with a description of the methodology used for creating it, as a result of our continuing cross-disciplinary collaboration between Columbia and Vanderbilt.

 

The adjacency matrices of the wiring diagram were taken from the paper “Wiring optimization can relate neuronal structure and function” by B.L. Chen, D.H. Hall, and D.B. Chklovskii, PNAS, March 21, 2006 vol. 103:12 pp.4723-4728.

 

                Gap Junction Neuronal Partners (Excel File)

                Post Synaptic Neuronal Partners (Excel File)

                Pre Synaptic Neuronal Partners (Excel File)

 

You can download a simple “demo” version of nearest-neighbor heuristic search entropy minimization software by clicking here. Starting from a “seed” gene set, the program will iteratively produce new gene sets of the same size with lower conditional entropy. Please type “help iterate” for instructions. Following is an example output:

 

 

[pre_egl-3   pre_unc-129 ]; H = 0.991604

[pre_egl-3   post_glr-6  ]; H = 0.990541

[pre_egl-3   post_mgl-2  ]; H = 0.982978

[post_mgl-2  post_flp-18 ]; H = 0.981130

[pre_mig-1   post_mgl-2  ]; H = 0.969051

[pre_mig-1   post_glr-5  ]; H = 0.966375

[pre_mig-1   post_cam-1  ]; H = 0.966088

[pre_mig-1   post_F25B5.2]; H = 0.955069

[pre_unc-18  post_F25B5.2]; H = 0.954243

[pre_unc-18  post_glr-1  ]; H = 0.952017