ProtDL (Reading List)

Protein secondary structure prediction

• Guo Y¹, Li W², Wang B³, Liu H¹, Zhou D¹. DeepACLSTM: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction. BMC Bioinformatics. 2019 Jun 17;20(1):341.

• Sheng Wang, Jian Peng, Jianzhu Ma & Jinbo Xu. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields. Scientific Reports. volume 6, Article number: 18962 (2016).

• Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility. Heffernan, et al., Bioinformatics, Volume 33, Issue 18, 15 September 2017, Pages 2842–2849.

• Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction, J. Zhou, https://arxiv.org/abs/1403.1347

• Gianluca Pollastri,1 Darisz Przybylski,2 Burkhard Rost,2 and Pierre Baldi3*. Improving the Prediction of Protein Secondary Structure in Three and Eight Classes Using Recurrent Neural Networks and Profiles. PROTEINS: Structure, Function, and Genetics 47:228–235 (2002).

• BURKHARD ROST AND CHRIS SANDER. Improved prediction of protein secondary structure by use of sequence profiles and neural networks. Proc. Natl. Acad. Sci. USA. Vol. 90, pp. 7558-7562, August 1993.