Home Research COVID-19 Services Publications People Teaching Job Opening News Forum Lab Only
Online Services

I-TASSER I-TASSER-MTD C-I-TASSER CR-I-TASSER QUARK C-QUARK LOMETS MUSTER CEthreader SEGMER DeepFold DeepFoldRNA FoldDesign COFACTOR COACH MetaGO TripletGO IonCom FG-MD ModRefiner REMO DEMO DEMO-EM SPRING COTH Threpp PEPPI BSpred ANGLOR EDock BSP-SLIM SAXSTER FUpred ThreaDom ThreaDomEx EvoDesign BindProf BindProfX SSIPe GPCR-I-TASSER MAGELLAN ResQ STRUM DAMpred

TM-score TM-align US-align MM-align RNA-align NW-align LS-align EDTSurf MVP MVP-Fit SPICKER HAAD PSSpred 3DRobot MR-REX I-TASSER-MR SVMSEQ NeBcon ResPRE TripletRes DeepPotential WDL-RF ATPbind DockRMSD DeepMSA FASPR EM-Refiner GPU-I-TASSER

BioLiP E. coli GLASS GPCR-HGmod GPCR-RD GPCR-EXP Tara-3D TM-fold DECOYS POTENTIAL RW/RWplus EvoEF HPSF THE-DB ADDRESS Alpaca-Antibody CASP7 CASP8 CASP9 CASP10 CASP11 CASP12 CASP13 CASP14

NeBcon (Neural-network and Bayes-classifier based contact prediction) is a hierarchical algorithm for sequence-based protein contact map prediction. It first uses the naive Bayes classifier theorem to calculate the posterior probability of eight machine-learning and co-evoluation based contact prodiction programs (SVMSEQ, BETACON, SVMcon, PSICOV, CCMpred, FreeContact, MetaPSICOV, and STRUCTCH). Final contact maps are then created by neural network machine that trains the posterior probability scores with intrinsic structural features from secondary structure, solvent accessibility, and Shannon entropy of multiple sequence alignments.


NeBcon On-line (view an example of NeBcon output)

    Cut and paste your sequence ([20, 1000] residues in FASTA format) below: Example input

    Or upload the sequence from your local computer:

    Email: (mandatory, where results will be sent to)

    ID: (optional, your given name of the protein)


Download package:

    The standalone NeBcon package can be downloaded from NeBconpackage.tar.gz. To install the package, follow the instrunctions below:
    1. Decompress the NeBconpackage.tar.gz with the command: tar -zxvf NeBconpackage.tar.gz
    2. After decompressing, read the README.txt file, which is available in NeBconpackage, for further instructions.


References:
    B He, SM Mortuza, Y Wang, H Shen, Y Zhang. NeBcon: Protein contact map prediction using neural network training coupled with naïve Bayes classifiers. Bioinformatics, 33: 2296-2306 (2017). [PDF] [Support Information]
    Supporting Materials: A list of the training dataset (517 non-homolgous proteins) and the test dataset (98 proteins) can be found at here.

zhanglabzhanggroup.org | +65-6601-1241 | Computing 1, 13 Computing Drive, Singapore 117417