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101.
Odds FC  Gow NA  Brown AJ 《Genome biology》2001,2(3):reviews1009.1-reviews10094
Sophisticated molecular biological research has revealed many virulence attributes in at least four pathogenic fungi, but the future study of fungal virulence requires investigators to distinguish between molecules that directly interact with the host, molecules that regulate these, and molecules that are always required for fungal growth and survival, independent of the host.  相似文献   
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We previously identified mutations in the Lpin1 gene, encoding lipin-1, as the underlying cause of lipodystrophy in the fatty liver dystrophy (fld) mutant mouse. Lipin-1 is normally expressed at high levels in adipose tissue and skeletal muscle, and deficiency in the fld mouse causes impaired adipose tissue development, insulin resistance, and altered energy expenditure. We also identified two additional lipin protein family members of unknown function, lipin-2 and lipin-3. Han et al. (Han, G. S., Wu, W. I., and Carman, G. M. (2006) J. Biol. Chem. 281, 9210-9218) recently demonstrated that the single lipin homolog in yeast, Smp2, exhibits phosphatidate phosphatase type-1 (PAP1) activity, which has a key role in glycerolipid synthesis. Here we demonstrate that lipin-1 accounts for all of the PAP1 activity in white and brown adipose tissue and skeletal muscle. However, livers of lipin-1-deficient mice exhibited normal PAP1 activity, indicating that other members of the lipin protein family could have PAP1 activity. Consistent with this possibility, recombinant lipin-2 and lipin-3 possess PAP1 activity. Each of the three lipin family members showed Mg2+-dependent activity that was specific for phosphatidate under the conditions employed. The different lipins showed distinct tissue expression patterns. Our results establish the three mammalian lipin proteins as PAP1 enzymes and explain the biochemical basis for lipodystrophy in the lipin-1-deficient fld mouse.  相似文献   
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Background  

The Distributed Annotation System (DAS) is a network protocol for exchanging biological data. It is frequently used to share annotations of genomes and protein sequence.  相似文献   
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Background  

Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law). Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented.  相似文献   
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