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Synthesizing Regularity Exposing Attributes in Large Protein Databases (1993)  (Make Corrections)  (4 citations)
Michael de la Maza



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Abstract: This thesis describes a system that synthesizes regularity exposing attributes from large protein databases. After processing primary and secondary structure data, this system discovers an amino acid representation that captures what are thought to be the three most important amino acid characteristics (size, charge, and hydrophobicity) for tertiary structure prediction. A neural network trained using this 16 bit representation achieves a performance accuracy on the secondary structure... (Update)

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.... of Naval Medicine, 693] Kernforschungsanlage Karlsruhe, 779] Los Alamos National Laboratory, 394] Massachusets Institute of Technology, [1090] Naval Ocean Systems Center, 32] Ochanomizu University, 863] Ruhr Universit at Mannheim, 789] Sandia National Laboratories,...

.... Universite Paris VI, 364] Linkoping University, 68] Loughborough University of Technology, 828] Massachusets Institute of Technology, [694] Mitsubishi Electric Corp. 90] Mitsubishi Electric Research Laboratories, 88] NERAC inc. 489] National University of Singapore,...

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An Indexed Bibliography of Genetic Algorithms Papers of 1993 - Jarmo T. Alander (1996)   (Correct)

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BibTeX entry:   (Update)

Michael de la Maza. Synthesizing regularity exposing attributes in large protein databases. Technical Report AI TR 1444, Massachusets Institute of Technology, 1993. * Achilles/MIT ga:Maza93c. http://citeseer.ist.psu.edu/delamaza93synthesizing.html   More

@techreport{ maza93synthesizing,
    author = "Michael de la Maza",
    title = "Synthesizing Regularity Exposing Attributes in Large Protein Databases",
    number = "AITR-1444",
    pages = "90",
    year = "1993",
    url = "citeseer.ist.psu.edu/delamaza93synthesizing.html" }
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