The software was first released on 25 Nov 2009. It was last updated in Dec 2012 with some bugs corrected. The software is designed to solve anchor-free graph realization problems based on semidefinite programming (SDP) relaxation of the following nonconvex minimization problem:

where is a positive regularization parameter.

The given data is with being a sparse subset of the set of all short-range distances given by , and is the cut-off radius.

For molecular conformation of protein molecules, is typically set to 6 Angstrom.

Important note: this is a research software. It is not intended nor designed to be a general purpose software.

**For more details, see**:

- N.-H. Z. Leung and K.-C. Toh,
*An SDP-based divide-and-conquer algorithm for large scale noisy anchor-free graph realization*, SIAM J.*Scientific Computing*, 31 (2009), pp. 4351--4372. - X.Y. Fang and K.C. Toh,
*Using a distributed SDP approach to solve simulated protein molecular conformation problems,*in Distance Geometry: Theory, Methods, and Applications, A. Mucherino, C. Lavor, L. Liberti, and N. Maculan eds., Springer, 2013, pp. 351--376. - A movie showing how the divide-and-conquer algorithm computes the conformation of a protein molecule.

**Copyright:**This version of DISCO is distributed under the**GNU General Public License 2.0**. For commercial applications that may be incompatible with this license, please contact the authors to discuss alternatives.

You can download the package here: DISCO-1.4.zip

Please read. Welcome to DISCO-1.4!

Firstly, unpack the software:

`xxxxxxxxxx`

`>> unzip DISCO-1.4.zip`

Run Matlab in the directory DISCO-1.4

To see whether you have installed DISCO-1.4 correctly, type:

`xxxxxxxxxx`

`>> discostartup`

`>> testdisco`

By now, DISCO is ready for you to use.

**Sparse distance data generated from some protein molecules:** MolecularData.zip. The folder contains several problems such as **1PTQ.mat** which contains two structure arrays (called prob and probchem) each encoding several sparse distance matrices such as

`prob.Dmat30, prob.Lmat30, prob.Umat30.`

**prob.Dmat30**corresponds to the sparse distance matrix containing 30% of distances (without noise) within the cut-off radius of 6.**prob.Lmat30**is the corresponding lower bound for the true distances.**prob.Umat30**is the corresponding upper bound for the true distances.**prob.A**is the true coordinates of the atoms.**probchem**is the same as`prob`

except that the pairwise distances between neighboring atoms on the backbone and some pairwise distances of covalently bonded atoms on the side chains are also included in**probchem.Dmat30**, etc.