P. Baldi, S. Brunak, P. Frasconi, G. Soda, and G. Pollastri, Exploiting the past and the future in protein secondary structure prediction, Bioinformatics, vol.15, issue.11, pp.937-946, 1999.
DOI : 10.1093/bioinformatics/15.11.937

C. Anfinsen, Studies on the principles that govern the folding of protein chains. Les Prix Nobel en 1972, pp.103-119, 1973.

F. Richards and C. Kundrot, Identification of structural motifs from protein coordinate data: Secondary structure and first-level supersecondary structure, Proteins: Structure, Function, and Genetics, vol.72, issue.2, pp.71-84, 1988.
DOI : 10.1002/prot.340030202

G. Pollastri, D. Przybylski, B. Rost, and P. Baldi, Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles, Proteins: Structure, Function, and Genetics, vol.47, issue.2, pp.228-235, 2002.
DOI : 10.1002/prot.10069

B. Rost and V. Eyrich, EVA: Large-scale analysis of secondary structure prediction, Proteins: Structure, Function, and Genetics, vol.405, issue.S5, pp.192-199, 2001.
DOI : 10.1016/0005-2795(75)90109-9
URL : http://cubic.bioc.columbia.edu/papers/2001_casp4_eva/paper.pdf

N. Qian and T. Sejnowski, Predicting the secondary structure of globular proteins using neural network models, Journal of Molecular Biology, vol.202, issue.4, pp.865-884, 1988.
DOI : 10.1016/0022-2836(88)90564-5

B. Rost and C. Sander, Improved prediction of protein secondary structure by use of sequence profiles and neural networks., Proceedings of the National Academy of Sciences, vol.90, issue.16, pp.7558-62, 1993.
DOI : 10.1073/pnas.90.16.7558

B. Rost and C. Sander, Combining evolutionary information and neural networks to predict protein secondary structure, Proteins: Structure, Function, and Genetics, vol.6, issue.1, pp.55-72, 1994.
DOI : 10.1016/0005-2795(75)90109-9

A. Salamov and V. Soloveyev, Protein secondary structure prediction using local alignments, Journal of Molecular Biology, vol.268, issue.1, pp.31-36, 1997.
DOI : 10.1006/jmbi.1997.0958

J. Cuff and G. Barton, Evaluation and improvement of multiple sequence methods for protein secondary structure prediction, Proteins: Structure, Function, and Genetics, vol.266, issue.4, pp.508-519, 1999.
DOI : 10.1016/0022-2836(82)90212-1

J. Chen and N. S. Chaudhari, Cascaded Bidirectional Recurrent Neural Networks for Protein Secondary Structure Prediction, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.4, issue.4, pp.572-582, 2007.
DOI : 10.1109/tcbb.2007.1055

A. Zemla, C. Venclovas, K. Fidelis, and B. Rost, A modified definition of Sov, a segment-based measure for protein secondary structure prediction assessment, Proteins: Structure, Function, and Genetics, vol.1, issue.2, pp.220-223, 1999.
DOI : 10.1002/(SICI)1097-0134(1997)1+<140::AID-PROT19>3.0.CO;2-O

H. Uwe, S. Michael, S. Reinhard, and S. Chris, Selection of representative protein data sets, Protein Science, vol.1, pp.409-417, 1992.

W. Kabsch and C. Sander, Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features, Biopolymers, vol.33, issue.12, pp.2577-2637, 1983.
DOI : 10.1016/0005-2795(73)90350-4

R. Schneider and C. Sander, The HSSP database of protein structure-sequence alignments, Nucleic Acids Research, vol.24, issue.1, pp.201-205, 1996.
DOI : 10.1093/nar/24.1.201

J. Elman, Finding Structure in Time, Cognitive Science, vol.49, issue.2, pp.179-211, 1990.
DOI : 10.1007/BF00308682
URL : http://onlinelibrary.wiley.com/doi/10.1207/s15516709cog1402_1/pdf

D. Baram and A. Yonath, From peptide-bond formation to cotranslational folding: dynamic, regulatory and evolutionary aspects, FEBS Letters, vol.289, issue.4, pp.948-954, 2005.
DOI : 10.1126/science.289.5481.905
URL : http://onlinelibrary.wiley.com/doi/10.1016/j.febslet.2004.11.063/pdf

D. Rumelhart, G. Hinton, and R. Williams, Learning representations by back-propagating errors, Nature, vol.85, issue.6088, pp.533-536, 1986.
DOI : 10.1038/323533a0