生物物理
Online ISSN : 1347-4219
Print ISSN : 0582-4052
ISSN-L : 0582-4052
51 巻 , 4 号
通巻296号
選択された号の論文の20件中1~20を表示しています
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  • 小柴 琢己, 久保山 美彩
    2011 年 51 巻 4 号 p. 174-177
    発行日: 2011年
    公開日: 2011/07/25
    ジャーナル フリー
    Mitochondria, dynamic organelles that undergo continuous cycles of fusion and fission events, are believed to play an important role in controlling organelle morphology, copy number, mitochondrial DNA maintenance and are also involved in cellular innate antiviral immunity. In mammals, mitochondrial dynamics rely on high molecular weight GTPases, mitofusin (Mfn1 and Mfn2), OPA1, and Drp1. Recently our studies revealed that Mfn2, a mediator of mitochondrial fusion, acts as an inhibitor of mitochondria-mediated antiviral immunity, which leads us to a linkage between mitochondrial dynamics and antiviral immunity in mammals. In this review, we discuss the participation of mitochondrial dynamics in antiviral immune responses and also show the evidence that the physiological function of mitochondria plays a key role in innate antiviral immunity.
  • 伊藤 賢太郎, 中垣 俊之
    2011 年 51 巻 4 号 p. 178-181
    発行日: 2011年
    公開日: 2011/07/25
    ジャーナル フリー
    The origin of information processing is a fundamental problem in evolutionary biology. True slime mold, Physarum, has become a model organism for study of problem solving by single-celled organisms. Here we report its ability to find a smart network by describing its aptitude in maze solving, multi purpose optimization for transportation network and risk management in a spatio-temporally varying field. We discuss these results in the context of a risk management strategy.
  • 荒木 啓充, HURLEY Daniel, CRAMPIN Edmund, PRINT Cristin, 久原 哲
    2011 年 51 巻 4 号 p. 182-185
    発行日: 2011年
    公開日: 2011/07/25
    ジャーナル フリー
    In the post-genome era, with the availability of high-throughput data, our biological focus makes a shift from a behavior of individual components to their regulatory/causative/interactive relationships. Gene network, which is inferred from microarray data by using reverse engineering algorithms, gives valuable information about the regulation of genes in the living cells under the certain conditions. In particular, this technology is applied to the biomedical research fields, e.g. identification of drug targets and prognosis markers. In this short review, we summarize what gene network is and how it is inferred. We also show our work that identified new drug target of well-known compound in human endothelial cells by gene network analysis.
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