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CEthreader (Contact Eigenvector-based threader) is a new threading algorithm that combines contact-map with profile-based alignments for protein fold recognition. Starting from a query sequence, CEthreader first creates ab initio contact prediction by coupling deep MSA and convolutional residual network training through ResPRE. The predicted 2D contact-map is then converted to a set of single-body Eigenvectors through the Eigen-decomposition technique, which are subsequently integrated with the profile and secondary structure scoring function to guide the dynamic programming alignment process. Large-scale benchmark shows that the combination of contact-map and profile alignments can help improve the accuracy of fold-recognition in particular for proteins that lack close-homology templates in the PDB. If you have questions and comments on CEthreader, please post them at the Service System Discussion Board. ( >>more about CEthreader ...)


[About CEthreader]   [Example of Output]   [Download]   [Forum for Discussion]

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References:
  • W Zheng, Q Wuyun, Y Li, SM Mortuza, C Zhang, R Pearce, J Ruan, Y Zhang. Detecting distant-homology protein structures by aligning deep neural-network based contact maps. PLOS Computational Biology, 15: e1007411 (2019). [PDF] [Support Information].

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