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  • 1995-1999  (2)
  • 1985-1989
  • Bamboo mosaic potexvirus  (1)
  • Boltzmann Machines  (1)
  • 1
    Electronic Resource
    Electronic Resource
    A Defective RNA Associated with Bamboo Mosaic Virus and the Possible Common Mechanisms for RNA Recombination in Potexviruses (1999)
    Springer
    Virus genes 18 (1999), S. 121-128 
    Details
    ISSN: 1572-994X
    Keywords: Bamboo mosaic potexvirus ; defective RNA ; RNA combination
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine
    Notes: Abstract A naturally occurring 1.1 kb RNA was isolated from purified virions of bamboo mosaic potexvirus isolate S (BaMV-S). This RNA is a defective RNA (D RNA) derived from a single internal deletion of the BaMV genome. A cDNA clone representing the complete nucleotide sequence of the BaMV-S D RNA was generated and its nucleotide sequence was determined. The BaMV D cDNA is 1015 nts in length [excluding the poly(A) tail] and consists of two regions corresponding to 867 nts of the 5′ terminus and 148 nts of the 3′ terminus of the BaMV genomic RNA. BaMV D cDNA contains a single open reading frame (ORF) encoding a putative 29.7 kDa protein comprised of a fusion of the first 258 amino acids of BaMV ORF 1 and the last 2 amino acids of coat protein. The coding capacity of D RNA was verified by in vitro translation of native BaMV-S D RNA and of 1.1 kb RNA transcribed in vitro from the full-length D cDNA. BaMV D RNA can be reproducibly generated by serial passages of BaMV-S in Nicotiana benthamiana and is the first D RNA in the potexvirus group shown to be generated de novo. Alignments of sequences surrounding the 5′ and 3′ junction borders of reported potexvirus D RNAs reveal a 65.2–84.6% sequence identity, suggesting that common mechanisms for viral RNA recombination are involved in the generation of potexvirus D RNAs.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008008400653
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Experiments of Fast Learning with High Order Boltzmann Machines (1997)
    Springer
    Applied intelligence 7 (1997), S. 287-303 
    Details
    ISSN: 1573-7497
    Keywords: Neural Networks ; Boltzmann Machines ; High Order networks ; Classification Problems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This work reports the results obtained with the application of High Order Boltzmann Machines without hidden units to construct classifiers for some problems that represent different learning paradigms. The Boltzmann Machine weight updating algorithm remains the same even when some of the units can take values in a discrete set or in a continuous interval. The absence of hidden units and the restriction to classification problems allows for the estimation of the connection statistics, without the computational cost involved in the application of simulated annealing. In this setting, the learning process can be sped up several orders of magnitude with no appreciable loss of quality of the results obtained.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008257203142
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
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