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Bstj 30: 3. July 1951: Some Basic Concepts of Translators and Identifiers Used in Telephone Switching Systems. (Schneckloth, H.H.)

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2016年

Bstj 30: 3. July 1951: Some Basic Concepts of Translators and Identifiers Used in Telephone Switching Systems. (Schneckloth, H.H.) by published by

关键词： (schneckloth, basic bell system calling number code code marking coding coding element coding elements concepts h.h.) identifiers input input code output output code output codes switching switching systems system technical translation translator translators

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National :: Appnotes :: an-0271

引用

2016年

National :: Appnotes :: an-0271 by published by

关键词： an-0271 analog output appnotes bipolar output cmos current dac dac controlled digital digital input figure input input code linearity national national semiconductor output output current output voltage reference reference voltage voltage wave output

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Microsoft :: Cpm :: Xerox Cobol-80

引用

2016年

Microsoft :: Cpm :: Xerox Cobol-80 by published by

关键词： clause cobol cobol-80 code key data data division data input decimal point file format input input code input field key label microsoft procedure division program receiving field reference reference manual release statement xerox

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Bstj 35: 3. May 1956: a Laboratory Model Magnetic Drum Translator for Toll Switching Offices. (Buhrendorf, F.G.;Henning, H.A.;Murphy, O.J.)

引用

2016年

Bstj 35: 3. May 1956: a Laboratory Model Magnetic Drum Translator for Toll Switching Offices. (Buhrendorf, F.G.; Henning, H.A.; Murphy, O.J.) by published by

关键词： (buhrendorf, bell system card translator code drum drum translator f.g. h.a. henning, input code magnetic magnetic drum output output code pulse pulses switching switching offices system technical toll toll switching translation translation selecting translator

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Accurate prediction of protein enzymatic class by N-to-1 Neural Networks

引用

BMC BIOINFORMATICS 2013年第Sup1期14卷 1-7页

作者： Volpato, Viola Adelfio, Alessandro Pollastri, Gianluca Univ Coll Dublin Sch Comp Sci & Informat Dublin Ireland Univ Coll Dublin Complex & Adapt Syst Lab Dublin Ireland

We present a novel ab initio predictor of protein enzymatic class. The predictor can classify proteins, solely based on their sequences, into one of six classes extracted from the enzyme commission (EC) classification scheme and is trained on a large, curated database of over 6,000 non-redundant proteins which we have assembled in this work. The predictor is powered by an ensemble of N-to-1 Neural Network, a novel architecture which we have recently developed. N-to-1 Neural Networks operate on the full sequence and not on predefined features. All motifs of a predefined length (31 residues in this work) are considered and are compressed by an N-to-1 Neural Network into a feature vector which is automatically determined during training. We test our predictor in 10-fold cross-validation and obtain state of the art results, with a 96% correct classification and 86% generalized correlation. All six classes are predicted with a specificity of at least 80% and false positive rates never exceeding 7%. We are currently investigating enhanced input encoding schemes which include structural information, and are analyzing trained networks to mine motifs that are most informative for the prediction, hence, likely, functionally relevant.

关键词： Hide Unit Enzyme Commission Enzyme Commission Number Secondary Structure Information input code

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