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Matching Protein b-Sheet Partners by Feedforward and Recurrent Neural Networks., , , and . ISMB, page 25-36. AAAI, (2000)Long-Range Information and Physicality Constraints Improve predicted protein Contact Maps., , , , and . J. Bioinform. Comput. Biol., 6 (5): 1001-1020 (2008)Exploiting the past and the future in protein secondary structure prediction., , , , and . Bioinform., 15 (11): 937-946 (1999)Accurate prediction of protein enzymatic class by N-to-1 Neural Networks., , and . BMC Bioinform., 14 (S-1): S11 (2013)Algorithms for Structure Comparison and Analysis: Docking., , and . Encyclopedia of Bioinformatics and Computational Biology (1), Elsevier, (2019)The Principled Design of Large-Scale Recursive Neural Network Architectures--DAG-RNNs and the Protein Structure Prediction Problem., and . J. Mach. Learn. Res., (2003)On the Convergence of Protein Structure and Dynamics. Statistical Learning Studies of Pseudo Folding Pathways., , , , and . EvoBIO, volume 4973 of Lecture Notes in Computer Science, page 200-211. Springer, (2008)Protein β-Sheet Partner Prediction by Neural Networks., , , and . ANNIMAB, page 3-9. Springer, (2000)G-quadruplex Structure Prediction and integration in the GenData2020 data model., , , , , , and . BCB, page 663-670. ACM, (2016)A Machine-Learning Strategy for Protein Analysis., and . IEEE Intell. Syst., 17 (2): 28-35 (2002)