Sandhi M Barreto, Roberto M Ladeira, Bruce B Duncan, Maria Ines Schmidt, Antonio A Lopes, Isabela M Benseñor, Dora Chor, Rosane H Griep, Pedro G Vidigal, Antonio L Ribeiro, Paulo A Lotufo, José Geraldo Mill
Chronic kidney disease among adult participants of the ELSA-Brasil cohort: association with race and socioeconomic position
Journal of epidemiology and community health
present new method predicting secondary structure globular proteins based nonlinear neural network models network models learn existing protein structures predict secondary structure local sequences amino acids average success rate method testing set proteins nonhomologous corresponding training set 643 three types secondary structure alphahelix betasheet coil correlation coefficients c alpha 041 c beta 031 ccoil 041 quality indices higher previous methods prediction accuracy first 25 residues nterminal sequence significantly better conclude computational experiments real artificial structures method based solely local information protein sequence likely produce significantly better results nonhomologous proteins performance method homologous proteins much better nonhomologous proteins good simply assuming homologous sequences identical structures