|Network Motif finding|
This package contains a gzipped tar file, with C code and perl scripts that run it. Code developed by Adam Sadovsky and was tested on linux.
Download: the package (gzipped tar file) (14Kb). Browse the directory.
To install: tar -xvzf findmotifs.tgz; make clean all;
To run: findmotifs.pl --help
Reference: If you use this code, please refer to
Activity motifs reveal principles of timing in transcription control of the yeast metabolic network Nature Biotechnology, 26, 1251-1259 (26 Oct 2008) Gal Chechik, Eugene Oh, Oliver Rando, Jonathan Weissman, Aviv Regev, Daphne Koller
|Co-Occurence Data Embedding (CODE)|
This package contains a gzipped tar file, with multiple matlab files and one linux binary. Send me an email if you are intersted to run the code on another platform.
Download: the package (gzipped tar file) (14Kb).
Browse the main function.
or get code_gad.C for mexing on a different architecture.
To install: tar -xvzf code.tgz.
How to run: [phi_x,psi_y] = code(pxys,embed_dim,options)
use 'help code' for further instructions.
Amir globerson, Gal Chechik, Fernando Pereira and Naftali Tishby
Euclidean Embedding of Co-occurrence Data.
Advances in Neural Information Processing Systems-18, (NIPS 2004).
|Information Bottleneck with Side Information (IBSI)|
An implementation of the sequential IB algorithm for IB with side information. The function also supports regular IB, and some specific form of multivairate-IB (see help for details).
Download: the matlab function(12Kb).
How to run: [Ptys,Ptx,trace]= ibsi_sequ(Pxys,parms)
use 'help ibsi_sequ' for further instructions.
G. Chechik and N. Tishby
Extracting relevant structures with side information.
Advances in Neural Information Processing Systems-16, (NIPS 2002).