FRSite: Protein drug binding site prediction based on faster R-CNN.

[1]  Zhi Wei,et al.  DeepPolyA: A Convolutional Neural Network Approach for Polyadenylation Site Prediction , 2018, IEEE Access.

[2]  Yuemin Bian,et al.  Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era , 2018, The AAPS Journal.

[3]  Tatsuya Takagi,et al.  Mordred: a molecular descriptor calculator , 2018, Journal of Cheminformatics.

[4]  Duolin Wang,et al.  MusiteDeep: A deep-learning framework for protein post-translational modification site prediction , 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[5]  Gianni De Fabritiis,et al.  DeepSite: protein‐binding site predictor using 3D‐convolutional neural networks , 2017, Bioinform..

[6]  Shaowen Yao,et al.  Protein secondary structure prediction: A survey of the state of the art. , 2017, Journal of molecular graphics & modelling.

[7]  Hasan Oğul,et al.  DeepMBS: Prediction of Protein Metal Binding-Site Using Deep Learning Networks , 2017, 2017 Fourth International Conference on Mathematics and Computers in Sciences and in Industry (MCSI).

[8]  Qin Lu,et al.  CNNsite: Prediction of DNA-binding residues in proteins using Convolutional Neural Network with sequence features , 2016, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[9]  Ruth Huey,et al.  Computational protein–ligand docking and virtual drug screening with the AutoDock suite , 2016, Nature Protocols.

[10]  Frank Noé,et al.  HTMD: High-Throughput Molecular Dynamics for Molecular Discovery. , 2016, Journal of chemical theory and computation.

[11]  Kaiming He,et al.  Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Didier Rognan,et al.  sc-PDB: a 3D-database of ligandable binding sites—10 years on , 2014, Nucleic Acids Res..

[13]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[14]  Trevor Darrell,et al.  Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[15]  Vincent Le Guilloux,et al.  Fpocket: An open source platform for ligand pocket detection , 2009, BMC Bioinformatics.

[16]  G. Schneider,et al.  PocketPicker: analysis of ligand binding-sites with shape descriptors , 2007, Chemistry Central Journal.

[17]  M. Schroeder,et al.  LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation , 2006, BMC Structural Biology.

[18]  Luc Van Gool,et al.  Efficient Non-Maximum Suppression , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[19]  Richard M. Jackson,et al.  Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites , 2005, Bioinform..

[20]  Paul Watson,et al.  A web-based platform for virtual screening. , 2003, Journal of molecular graphics & modelling.

[21]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[22]  M Hendlich,et al.  LIGSITE: automatic and efficient detection of potential small molecule-binding sites in proteins. , 1997, Journal of molecular graphics & modelling.

[23]  K Schulten,et al.  VMD: visual molecular dynamics. , 1996, Journal of molecular graphics.

[24]  P. Goodford.  A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. , 1985, Journal of medicinal chemistry.