Linear programming optimization and a double statistical filter for protein threading protocols

2001 ◽  
Vol 45 (3) ◽  
pp. 241-261 ◽  
Author(s):  
Jaroslaw Meller ◽  
Ron Elber
Keyword(s):  
Linear Programming ◽  
Protein Threading

RAPTOR: OPTIMAL PROTEIN THREADING BY LINEAR PROGRAMMING

2003 ◽  
Vol 01 (01) ◽  
pp. 95-117 ◽  
Author(s):  
JINBO XU ◽  
MING LI ◽  
DONGSUP KIM ◽  
YING XU
Keyword(s):  
Linear Programming ◽  
Structure Prediction ◽  
Large Scale ◽  
3D Structure ◽  
Fold Recognition ◽  
Programming Approach ◽  
Linear Programs ◽  
Surprising Result ◽  
3 Dimensional ◽  
Protein Threading

This paper presents a novel linear programming approach to do protein 3-dimensional (3D) structure prediction via threading. Based on the contact map graph of the protein 3D structure template, the protein threading problem is formulated as a large scale integer programming (IP) problem. The IP formulation is then relaxed to a linear programming (LP) problem, and then solved by the canonical branch-and-bound method. The final solution is globally optimal with respect to energy functions. In particular, our energy function includes pairwise interaction preferences and allowing variable gaps which are two key factors in making the protein threading problem NP-hard. A surprising result is that, most of the time, the relaxed linear programs generate integral solutions directly. Our algorithm has been implemented as a software package RAPTOR–RApid Protein Threading by Operation Research technique. Large scale benchmark test for fold recognition shows that RAPTOR ignificantly outperforms other programs at the fold similarity level. The CAFASP3 evaluation, a blind and public test by the protein structure prediction community, ranks RAPTOR as top 1, among individual prediction servers, in terms of the recognition capability and alignment accuracy for Fold Recognition (FR) family targets. RAPTOR also performs very well in recognizing the hard Homology Modeling (HM) targets. RAPTOR was implemented at the University of Waterloo and it can be accessed at .

PROTEIN THREADING BY LINEAR PROGRAMMING

2002 ◽  
Author(s):  
JINBO XU ◽  
MING LI ◽  
GUOHUI LIN ◽  
DONGSUP KIM ◽  
YING XU
Keyword(s):  
Linear Programming ◽  
Protein Threading

Elementary Linear Programming (2nd edition)

1997 ◽  
Vol 48 (7) ◽  
pp. 757-758
Author(s):  
B Kolman ◽  
R E Beck ◽  
M J Panik
Keyword(s):  
Linear Programming

Optimal approaches to manage power system decarbonation

2020 ◽  
Vol 64 (1-4) ◽  
pp. 1447-1452
Author(s):  
Vincent Mazauric ◽  
Ariane Millot ◽  
Claude Le Pape-Gardeux ◽  
Nadia Maïzi
Keyword(s):  
Free Energy ◽  
Linear Programming ◽  
Phase Transitions ◽  
Power System ◽  
Energy System ◽  
Energy Sources ◽  
Low Carbon ◽  
Faraday’S Law ◽  
Optimal Description ◽  
Low Carbon Technologies

To overcome the negative environemental impact of the actual power system, an optimal description of quasi-static electromagnetics relying on a reversible interpretation of the Faraday’s law is given. Due to the overabundance of carbon-free energy sources, this description makes it possible to consider an evolution towards an energy system favoring low-carbon technologies. The management for changing is then explored through a simplified linear-programming problem and an analogy with phase transitions in physics is drawn.

Sign in / Sign up

Export Citation Format

Share Document