NNcon: improved protein contact map prediction using 2D-recursive neural networks. Protein contact map prediction is useful for protein folding rate prediction, model selection and 3D structure prediction. Here we describe NNcon, a fast and reliable contact map prediction server and software. NNcon was ranked among the most accurate residue contact predictors in the Eighth Critical Assessment of Techniques for Protein Structure Prediction (CASP8), 2008. Both NNcon server and software are available at http://casp.rnet.missouri.edu/nncon.html.

References in zbMATH (referenced in 6 articles )

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  1. Carugo, Oliviero (ed.); Eisenhaber, Frank (ed.): Data mining techniques for the life sciences (2016)
  2. Santiesteban-Toca, Cosme E.; Aguilar-Ruiz, Jesús S.: A new multiple classifier system for the prediction of protein’s contacts map (2015) ioport
  3. Schmidhuber, Jürgen: Deep learning in neural networks: an overview (2015) ioport
  4. Marquez-Chamorro, Alfonso Eduardo; Asencio-Cortes, Gualberto; Divina, Federico; Aguilar-Ruiz, Jesus Salvador: Evolutionary decision rules for predicting protein contact maps (2014)
  5. Fonseca, Rasmus; Helles, Glennie; Winter, Pawel: Ranking beta sheet topologies with applications to protein structure prediction (2011)
  6. Tegge, Allison N.; Wang, Zheng; Eickholt, Jesse; Cheng, Jianlin: Nncon: improved protein contact map prediction using 2D-recursive neural networks (2009) ioport