Recognizing disease-associated nsSNP mutations in human genome through a Bayes-guided artificial neural-network model built on BioUnit and protein structure predictions

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

DAMpred is a method to predict what gene mutations can cause human diseases and what mutations do not do so. Starting with a protein sequence and specified non-synonymous single nucleotide polymorphisms (nsSNPs), DAMpred calculates the probability of the mutations to be deleterious or neutral to human health. The calculation is built on a deep-learning model that integrates three sources of information from sequence profiles, biological assembly and 3D structure model (by I-TASSER), which is trained through a novel Bayes-guided artificial neural network (BANN) algorithm (>> more about DAMpred ...).

Our server will undergo maintenance from Oct. 7 to Oct. 21, 2019. You can submit jobs normally during this period, but the jobs will run after Oct. 21, 2019. We apologize for any inconvenience this may cause.

DAMpred On-line (View an example of output)

DAMpred Downloads

References

Lijun Quan, Hongjie Wu, Qiang Lyu, Yang Zhang. DAMpred: Recognizing disease-associated nsSNPs through Bayes-guided neural-network model built on low-resolution structure prediction of proteins and protein-protein interactions. J Mol Biol, in press (2019).