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|Interface||Command line interface|
|Restrictions to use||None|
|Source code URL||https://ttic.uchicago.edu/~wangsheng/DeepCNF_D_package_v1.00.tar.gz|
No version available
- person_outline Sheng Wang
Publication for DeepCNF
Polymorphism in merozoite surface protein 7E of Plasmodium vivax in Thailand: Natural selection related to protein secondary structure
[…] epeats Finder version 4.0 program . Protein secondary structure prediction was determined by Deep Convolutional Neural Filed program (DeepCNF) implemented in the RaptorX-Property Web-Server . The DeepCNF method has been validated to outperform other methods that achieved >70% accuracy in eight-state protein structure prediction . Protein disordered or intrinsically unstructured regions were […]
Opportunities and obstacles for deep learning in biology and medicine
[…] networks. In 2014, Zhou & Troyanskaya  demonstrated that they could improve Q8 accuracy by using a deep supervised and convolutional generative stochastic network. In 2016, Wang et al. developed a DeepCNF model that improved Q3 and Q8 accuracy as well as prediction of solvent accessibility and disorder regions [,]. DeepCNF achieved a higher Q3 accuracy than the standard maintained by PSIPRED fo […]
DeepSF: deep convolutional neural network for mapping protein sequences to folds
[…] secondary structure, we analyzed how the different quality of predicted secondary structure influences the fold prediction. We generated predicted secondary structure using four methods: SCRATCH (), DeepCNF (), DNSS () and PSIPRED (), which were used for fold classification on the CASP dataset, respectively. The results are shown in . For top 1 fold prediction, higher secondary structure predicti […]
C terminal lysine repeats in Streptomyces topoisomerase I stabilize the enzyme–DNA complex and confer high enzyme processivity
[…] is consistent with the higher incidence of β-structures in the E. coli TopA CTD (32%, based on crystallographic data) compared to the S. coelicolor TopA CTD (16%, based on structure prediction using DeepCNF (Deep Convolutional Neural Fields) ()). The recent sequence and structure analysis of M. tuberculosis TopA revealed that its CTD encompasses four repeated subdomains and ends with a lysine-ric […]
Sixty five years of the long march in protein secondary structure prediction: the final stretch?
[…] twork (SPINE)  in 2007, 82% by Structural Property prediction with Integrated DEep neuRal network 2 (SPIDER2)  in 2015, to 84% for several test data sets by Deep Convolution Neural Field network (DeepCNF)  in 2016. Although accuracies reported by different methods are not always directly comparable because of different data sets being used, there is a clear trend of a slow but steady improve […]
Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields
[…] We have presented a new sequence labeling method, called DeepCNF (Deep Convolutional Neural Fields), for protein secondary structure prediction. This new method can not only model complex sequence-structure relationship by a deep hierarchical architecture, […]
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