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      Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease

      Nature Communications
      Springer Nature

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          Lipid droplets finally get a little R-E-S-P-E-C-T.

          Long underappreciated as important cellular organelles, lipid droplets are finally being recognized as dynamic structures with a complex and interesting biology. In light of this newfound respect, we discuss emerging views on lipid droplet biology and speculate on the major advances to come.
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            Ongoing and future developments at the Universal Protein Resource

            The primary mission of Universal Protein Resource (UniProt) is to support biological research by maintaining a stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces freely accessible to the scientific community. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is updated and distributed every 4 weeks and can be accessed online for searches or download at http://www.uniprot.org.
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              Network-based prediction of human tissue-specific metabolism.

              Direct in vivo investigation of mammalian metabolism is complicated by the distinct metabolic functions of different tissues. We present a computational method that successfully describes the tissue specificity of human metabolism on a large scale. By integrating tissue-specific gene- and protein-expression data with an existing comprehensive reconstruction of the global human metabolic network, we predict tissue-specific metabolic activity in ten human tissues. This reveals a central role for post-transcriptional regulation in shaping tissue-specific metabolic activity profiles. The predicted tissue specificity of genes responsible for metabolic diseases and tissue-specific differences in metabolite exchange with biofluids extend markedly beyond tissue-specific differences manifest in enzyme-expression data, and are validated by large-scale mining of tissue-specificity data. Our results establish a computational basis for the genome-wide study of normal and abnormal human metabolism in a tissue-specific manner.
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                10.1038/ncomms4083

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