%0 Report %1 j.murvai1997 %A Murvai, J. %A Szepesvári, Cs. %A Bachrati, Cs. %A Pongor, S. %C Szeged, HU-6700 %D 1997 %K application bioinformatics, domain networks, neural prediction, %N TR-98-117 %T Prediction of Protein Domain-Types by Backpropagation %X We propose a neural net solution for the recognition of the domain types of proteins, which is a hard and important problem in biology. We have found that using a clever preprocessing technique relatively small neural networks perform surprisingly well. The performances of the neural nets were measured by cross-validation and Hoeffding's inequality was utilized for the estimation of a confidence interval of the estimates.

@techreport{j.murvai1997, abstract = {We propose a neural net solution for the recognition of the domain types of proteins, which is a hard and important problem in biology. We have found that using a clever preprocessing technique relatively small neural networks perform surprisingly well. The performances of the neural nets were measured by cross-validation and Hoeffding's inequality was utilized for the estimation of a confidence interval of the estimates.}, added-at = {2020-03-17T03:03:01.000+0100}, address = {Szeged, HU-6700}, author = {Murvai, J. and Szepesv{\'a}ri, {Cs}. and Bachrati, Cs. and Pongor, S.}, biburl = {https://www.bibsonomy.org/bibtex/222d371491e09876184c0dea968ab8a4b/csaba}, date-modified = {2010-09-02 13:09:16 -0600}, institution = {``Attila J{\'o}zsef'' University, Research Group on Artificial Intelligence}, interhash = {e74aeb8d7721bbe4fe9f03a7c3886b17}, intrahash = {22d371491e09876184c0dea968ab8a4b}, keywords = {application bioinformatics, domain networks, neural prediction,}, number = {TR-98-117}, owner = {Beata}, pdf = {papers/RGAI-98-117.ps.pdf}, timestamp = {2020-03-17T03:03:01.000+0100}, title = {Prediction of Protein Domain-Types by Backpropagation}, year = 1997 }