@article {16506243,
	title = {Accuracy of sequence alignment and fold assessment using reduced amino acid alphabets},
	journal = {Proteins},
	volume = {63},
	number = {4},
	year = {2006},
	note = {Melo, Francisco Marti-Renom, Marc A Research Support, Non-U.S. Gov{\textquoteright}t United States Proteins Proteins. 2006 Jun 1;63(4):986-95.},
	pages = {986-95},
	abstract = {Reduced or simplified amino acid alphabets group the 20 naturally occurring amino acids into a smaller number of representative protein residues. To date, several reduced amino acid alphabets have been proposed, which have been derived and optimized by a variety of methods. The resulting reduced amino acid alphabets have been applied to pattern recognition, generation of consensus sequences from multiple alignments, protein folding, and protein structure prediction. In this work, amino acid substitution matrices and statistical potentials were derived based on several reduced amino acid alphabets and their performance assessed in a large benchmark for the tasks of sequence alignment and fold assessment of protein structure models, using as a reference frame the standard alphabet of 20 amino acids. The results showed that a large reduction in the total number of residue types does not necessarily translate into a significant loss of discriminative power for sequence alignment and fold assessment. Therefore, some definitions of a few residue types are able to encode most of the relevant sequence/structure information that is present in the 20 standard amino acids. Based on these results, we suggest that the use of reduced amino acid alphabets may allow to increasing the accuracy of current substitution matrices and statistical potentials for the prediction of protein structure of remote homologs.},
	keywords = {Amino Acid Sequence Amino Acids/*chemistry/classification/*metabolism Consensus Sequence Molecular Sequence Data Oxidation-Reduction *Protein Folding Proteins/*chemistry/*metabolism Sequence Alignment/*methods Structural Homology, Protein},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16506243},
	author = {Melo, F. and M. A. Marti-Renom}
}
@article {12824315,
	title = {EVA: Evaluation of protein structure prediction servers},
	journal = {Nucleic Acids Res},
	volume = {31},
	number = {13},
	year = {2003},
	note = {Koh, Ingrid Y Y Eyrich, Volker A Marti-Renom, Marc A Przybylski, Dariusz Madhusudhan, Mallur S Eswar, Narayanan Grana, Osvaldo Pazos, Florencio Valencia, Alfonso Sali, Andrej Rost, Burkhard 1-P50-GM62413-01/GM/NIGMS NIH HHS/United States 5-P20-LM7276/LM/NLM NIH HHS/United States P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States R01-GM63029-01/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov{\textquoteright}t Research Support, U.S. Gov{\textquoteright}t, Non-P.H.S. Research Support, U.S. Gov{\textquoteright}t, P.H.S. England Nucleic acids research Nucleic Acids Res. 2003 Jul 1;31(13):3311-5.},
	pages = {3311-5},
	abstract = {EVA (http://cubic.bioc.columbia.edu/eva/) is a web server for evaluation of the accuracy of automated protein structure prediction methods. The evaluation is updated automatically each week, to cope with the large number of existing prediction servers and the constant changes in the prediction methods. EVA currently assesses servers for secondary structure prediction, contact prediction, comparative protein structure modelling and threading/fold recognition. Every day, sequences of newly available protein structures in the Protein Data Bank (PDB) are sent to the servers and their predictions are collected. The predictions are then compared to the experimental structures once a week; the results are published on the EVA web pages. Over time, EVA has accumulated prediction results for a large number of proteins, ranging from hundreds to thousands, depending on the prediction method. This large sample assures that methods are compared reliably. As a result, EVA provides useful information to developers as well as users of prediction methods.},
	keywords = {Automation Databases, Protein, Protein Internet *Protein Conformation Protein Folding Protein Structure, Protein Structural Homology, Secondary Proteins/chemistry Reproducibility of Results *Sequence Analysis},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12824315},
	author = {Koh, I. Y. and Eyrich, V. A. and M. A. Marti-Renom and Przybylski, D. and Madhusudhan, M. S. and Eswar, N. and Grana, O. and Pazos, F. and Valencia, A. and Sali, A. and Rost, B.}
}
