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- 저자 : Stephane Bressan (검색결과 2 건)
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Hisashi Koiwa,,Stephane Hausmann,Bang, Woo-Young,Akihiro Ueda,Naoko Kondo,Akihiro Hiraguri,Toshiyuki Fuku,hara,Bahk, Jeong-Dong,Yun, Dae-Jin,Ray A. Bressan,Paul M. Hasegawa,Stewart Shuman Plant molecular biology and biotechnology research 2004 Plant molecular biology and biotechnology research Vol.2004 No.-
Transcription and mRNA processing are regulated by phosphorylation and dephosphorylation of the C-terminal domain (CTD) of RNA polymerase Ⅱ, which consists of tandem repeats of a Y^(1)S^(2)P^(3)T^(4)S^(5)P^(6)S^(7) heptapeptide. Previous studies showed that members of the plant CTD phosphatase-like (CPL) protein family differentially regulate osmotic stress-responsive and abscisic acid-responsive transcription in Arabidopsis thaliana. Here we report that AtCPL1 and AtCPL2 specifically dephosphorylate Ser-5 of the CTD heptad in Arabidopsis RNA polymerase Ⅱ, but not Ser-2. An N-terminal catalytic domain of CPL1, which suffices for CTD Ser-5 phosphatase activity in virto, includes a signature DXDXT acylphosphatase motif, but lacks a breast cancer 1 CTD, which is an essential component of the fungal and metazoan Fcp1 CTD phosphatase enzymes. The CTD of CPL1, which contains two putative double-stranded RNA binding motifs, is essential for the in vivo function of CPL1 and includes a C-terminal 23-aa signal responsible for its nuclear targeting. CPL2 has a similar domain structure but contains only one double-stranded RNA binding motif. Combining mutant alleles of CPL1 and CPL2 causes synthetic lethality of the male but not the female gametes. These results indicate that CPL1 and CPL2 exemplify a unique family of CTD Ser-5-specific phosphatases with an essential role in plant growth and development.
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Mohammad Reza Zare Mirakabad,Aman Jantan,Stephane Bressan 보안공학연구지원센터 2009 International Journal of Security and Its Applicat Vol.3 No.1
Many efforts have been done in the field of privacy preservation to devise algorithms for data k-anonymization and l-diversification trying to protect privacy, by modification of data, for example. Fewer efforts have been made for devising techniques, tools and methodologies for investigation and evaluation of privacy risks. We are concerned about privacy diagnosis before starting protection. Actually we show privacy leakages threaten data publication. We introduce a Privacy Diagnosis Centre for this purpose. In this paper toward this diagnosis centre we focus on anonymity and, in particular, k-anonymity. Then we aim at k-anonymity diagnosis system. Such a system explores various questions about k-anonymity of data. “For which k is my data k-anonymous?”, “is my data sufficiently k-anonymous?”, “which subset and projection of data can be safely published to guarantee given k?”, “which information, if available from an outside source, threatens the k-anonymity of my data?” are examples of questions can be answered. We leverage two properties of k-anonymity that we express in the form of two lemmas. The first lemma is a monotonicity property that enables us to adapt the a-priori algorithm for k-anonymity. The second lemma, however, is a determinism property that enables us to devise an efficient algorithm for δ-suppression. We illustrate and empirically analyze the performance of the proposed algorithms.
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