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Titlebook: Lesser Known Large dsDNA Viruses; James L. Etten Book 2009 The Editor(s) (if applicable) and The Author(s), under exclusive license to Spr

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發(fā)表于 2025-3-21 18:00:24 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Lesser Known Large dsDNA Viruses
編輯James L. Etten
視頻videohttp://file.papertrans.cn/586/585213/585213.mp4
概述Includes supplementary material:
叢書名稱Current Topics in Microbiology and Immunology
圖書封面Titlebook: Lesser Known Large dsDNA Viruses;  James L. Etten Book 2009 The Editor(s) (if applicable) and The Author(s), under exclusive license to Spr
描述.Several large dsDNA-containing viruses such as poxviruses (smallpox) and herpes viruses are well known among the scientific community, as well as the general populace, because they cause human diseases. The large dsDNA insect-infecting baculoviruses are also well known in the scientific community because they are used both as biological control agents and as protein expression systems. However, there are other large dsDNA-containing viruses, including the giant 1.2 Mb mimivirus, which are less well known despite the fact that all of them play important roles in every day life. Seven of these virus families are reviewed in this book. .
出版日期Book 2009
關(guān)鍵詞African Swine Fever Virus; Ascovirus; DNA viruses; Iridoviridae; Jumbo Bacteriophages; Mimivirus; Phycodna
版次1
doihttps://doi.org/10.1007/978-3-540-68618-7
isbn_softcover978-3-642-08814-8
isbn_ebook978-3-540-68618-7Series ISSN 0070-217X Series E-ISSN 2196-9965
issn_series 0070-217X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE
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Mimivirus,uses, such as phycodnaviruses and iridoviruses, and most likely share a common ancestry with all nucleocytoplasmic large DNA viruses. Postgenomic studies have now started in various laboratories, slowly shedding some light on the physiology of the largest and most complex virus isolated to date. Thi
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J. -M. Claverie,C. Abergel,H. Ogatagnals. The approaches were evaluated on publicly available dataset II of BCI competition III. Another dataset was recorded locally using audio beeps as stimuli to validate these approaches. The ensemble models based on CNNs and ConvLSTM are also proposed. These models perform better than individual
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