@conference {15269,
	title = {A cooperative combinatorial Particle Swarm Optimization algorithm for side-chain packing},
	booktitle = {IEEE Swarm Intelligence Symposium, 2009. SIS {\textquoteright}09},
	year = {2009},
	month = {2009/04/30/March},
	pages = {22 - 29},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Particle Swarm Optimization (PSO) is a well-known, competitive technique for numerical optimization with real-parameter representation. This paper introduces CCPSO, a new Cooperative Particle Swarm Optimization algorithm for combinatorial problems. The cooperative strategy is achieved by splitting the candidate solution vector into components, where each component is optimized by a particle. Particles move throughout a continuous space, their movements based on the influences exerted by static particles that then get feedback based on the fitness of the candidate solution. Here, the application of this technique to side-chain packing (a proteomics optimization problem) is investigated. To verify the efficiency of the proposed CCPSO algorithm, we test our algorithm on three side-chain packing problems and compare our results with the provably optimal result. Computational results show that the proposed algorithm is very competitive, obtaining a conformation with an energy value within 1\% of the provably optimal solution in many proteins.},
	keywords = {Algorithm design and analysis, Amino acids, combinatorial mathematics, cooperative combinatorial particle swarm optimization algorithm, Design optimization, Encoding, Feedback, numerical optimization, Optimization methods, particle swarm optimisation, Particle swarm optimization, Partitioning algorithms, Proteins, proteomics, proteomics optimization, Robustness, side-chain packing},
	isbn = {978-1-4244-2762-8},
	doi = {10.1109/SIS.2009.4937840},
	author = {Lapizco-Encinas,G. and Kingsford, Carl and Reggia, James A.}
}
@article {13421,
	title = {Amino acid quantitative structure property relationship database: a web-based platform for quantitative investigations of amino acids},
	journal = {Protein Engineering Design and SelectionProtein Engineering, Design and Selection},
	volume = {20},
	year = {2007},
	month = {2007/07/01/},
	pages = {347 - 351},
	abstract = {Here, we present the AA-QSPR Db (Amino Acid Quantitative Structure Property Relationship Database): a novel, freely available web-resource of data pertaining to amino acids, both engineered and naturally occurring. In addition to presenting fundamental molecular descriptors of size, charge and hydrophobicity, it also includes online visualization tools for users to perform instant, interactive analyses of amino acid sub-sets in which they are interested. The database has been designed with extensible markup language technology to provide a flexible structure, suitable for future development. In addition to providing easy access for queries by external computers, it also offers a user-friendly web-based interface that facilitates human interactions (submission, storage and retrieval of amino acid data) and an associated e-forum that encourages users to question and discuss current and future database contents.},
	keywords = {Amino acids, database, QSPR, XML},
	isbn = {1741-0126, 1741-0134},
	doi = {10.1093/protein/gzm027},
	url = {http://peds.oxfordjournals.org/content/20/7/347},
	author = {Lu,Yi and Bulka,Blazej and desJardins, Marie and Freeland,Stephen J}
}
