We currently have a few open source software released to the public.
They are listed hereafter in reverse chronological order.
is a tool to identify and rebuild residues in predicted
models with a large error. The error in predicted models is estimated
using the average pairwise geometric distance per residue computed among
selected lowest energy models. This error distribution among residues is
employed to guide the rebuilding process that focuses on more error-prone
residues of the coarse-grain models. MORPHEUS is implemented in C++.
It can be run either in batch mode or in parallel mode using MPI.
is a C++/MPI software prototype for fragment-based
protein structure prediction based on an Estimation of
Distribution Algorithm. Fragment-based approaches
build protein models by assembling short fragments
from known protein structures. Whereas the probability mass functions
over the fragment libraries are uniform in the
usual case, we propose an algorithm that learns from previously
generated decoys and steers the search towards native-like regions.
Durandal with QCP
We have further enhanced the performance of Durandal
a Quaternion-based Characteristic Polynomial
method to speedup RMSD calculations.
is a tool implementing entropy-accelerated exact clustering
for protein models stored in PDB files.
Clustering is commonly used to identify the best decoy
among many generated in protein structure prediction when using
energy alone is insufficient. Calculation of the pairwise distance
matrix for a large decoy set is computationally expensive. Typically,
only a reduced set of decoys using energy filtering is subjected to
clustering analysis. We propose a method using propagation of geometric
constraints to accelerate exact clustering, without compromising the
distance measure. Our method can be used with any metric distance.
Durandal became an official
Phenix tool, starting from Phenix v.1.7.2 !
is a PARallel and distributed job crusher. Bag-of-Tasks (BoT)
applications are commonly encountered in bioinformatics. They consist of a
large number of independent computation-intensive tasks. PAR is a scalable,
dynamic, parallel and distributed execution engine for Bag-of-Tasks.
PAR is aimed at multi-core architectures and small clusters.