Downloadable Software

This page contains some of the software used in the implementation section of my recent publications. More software is available from the PUMA webpage.
  • Noisy PPCA: a matlab package containing the code and demos used in "Accounting for Probe-level Noise in the Processing of Microarray Data with Principal Component Analysis", G.S., Marta Milo, Magnus Rattray and Neil D. Lawrence (also available in R from PUMA).

  • Unsupervised LDA, a matlab package containing an implementation of the model described in my recent paper "Dimensionality reduction of clustered data sets" (to appear in IEEE TPAMI)

  • MMG, a matlab package for a finding submodules of metabolic networks, as described in this Bioinformatics paper.

  • swRegVariational and swRegExact a matlab and C packages for inferring TF reaction to stress bioinformatics paper.

  • multiSwitch a MATLAB package for combinatorial regulation, described in Opper and Sanguinetti, Bioinformatics 26(13), 2010. A brief documentation can be found here

  • TFInfer an open-source package extending and optimising the method described in Sanguinetti et al, Bioinformatics 22(22):2775-2781 (2006). An application note describing the software has appeared in Asif et al, Bioinformatics 26(20), 2010.

  • Multi-task GP classification (method under review), a demo of the MATLAB code developed by Grigorios Skolidis. You will need some extra files which can be publicly downloaded, see instructions in README.txt.

  • Large scale inference of combinatorial regulation, MATLAB package developed by Shahzad Asif implementing the work described in this Bioinformatics paper.

  • Inference in hierarchical networks, MATLAB package developed by Andrea Ocone implementing the work described in this Bioinformatics paper.

  • Testing chip-seq histograms developed by Gabriele Schweikert journal link.

  • Hybrid Regulatory Models developed by Andrea Ocone journal link.

  • Multi-task GP regression for inference of pKA developed by Grigorios Skolidis for the paper Multi-task learning for pKa prediction, Skolidis, Hansen, Sanguinetti and Rupp, in press with Journal of Computer Aided Molecular Design.

  • DSS, network inference for oscillatory networks, developed by Daniel Trejo-Banos (paper under review).
  • MDC, modular differential connection modelling, developed by Ronald Begg (paper under review)