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- Clermont, Gilles, et al.
(författare)
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Bridging the gap between systems biology and medicine
- 2009
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Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 1:9
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Tidskriftsartikel (refereegranskat)abstract
- ABSTRACT : Systems biology has matured considerably as a discipline over the last decade, yet some of the key challenges separating current research efforts in systems biology and clinically useful results are only now becoming apparent. As these gaps are better defined, the new discipline of systems medicine is emerging as a translational extension of systems biology. How is systems medicine defined? What are relevant ontologies for systems medicine? What are the key theoretic and methodologic challenges facing computational disease modeling? How are inaccurate and incomplete data, and uncertain biologic knowledge best synthesized in useful computational models? Does network analysis provide clinically useful insight? We discuss the outstanding difficulties in translating a rapidly growing body of data into knowledge usable at the bedside. Although core-specific challenges are best met by specialized groups, it appears fundamental that such efforts should be guided by a roadmap for systems medicine drafted by a coalition of scientists from the clinical, experimental, computational, and theoretic domains.
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| 4. |
- Larsson, Erik, 1975, et al.
(författare)
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Discovery of microvascular miRNAs using public gene expression data : miR-145 is expressed in pericytes and is a regulator of Fli1
- 2009
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Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X .- 1756-994X. ; 1:11, s. 108-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUNDA function for the microRNA (miRNA) pathway in vascular development and angiogenesis has been firmly established. miRNAs with selective expression in the vasculature are attractive as possible targets in miRNA-based therapies. However, little is known about the expression of miRNAs in microvessels in vivo. Here, we identified candidate microvascular-selective miRNAs by screening public miRNA expression datasets.METHODSBioinformatics predictions of microvascular-selective expression were validated with real-time quantitative reverse transcription PCR on purified microvascular fragments from mouse. Pericyte expression was shown with in situ hybridization on tissue sections. Target sites were identified with 3' UTR luciferase assays, and migration was tested in a microfluid chemotaxis chamber.RESULTSmiR-145, miR-126, miR-24, and miR-23a were selectively expressed in microvascular fragments isolated from a range of tissues. In situ hybridization and analysis of Pdgfb retention motif mutant mice demonstrated predominant expression of miR-145 in pericytes. We identified the Ets transcription factor Friend leukemia virus integration 1 (Fli1) as a miR-145 target, and showed that elevated levels of miR-145 reduced migration of microvascular cells in response to growth factor gradients in vitro.CONCLUSIONSmiR-126, miR-24 and miR-23a are selectively expressed in microvascular endothelial cells in vivo, whereas miR-145 is expressed in pericytes. miR-145 targets the hematopoietic transcription factor Fli1 and blocks migration in response to growth factor gradients. Our findings have implications for vascular disease and provide necessary information for future drug design against miRNAs with selective expression in the microvasculature.
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| 5. |
- Tang, Jing, et al.
(författare)
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Integrating post-genomic approaches as a strategy to advance our understanding of health and disease
- 2009
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Ingår i: Genome Medicine. - : BioMed Central (BMC). - 1756-994X .- 1756-994X. ; 1:3
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Forskningsöversikt (refereegranskat)abstract
- Following the publication of the complete human genomic sequence, the post-genomic era is driven by the need to extract useful information from genomic data. Genomics, transcriptomics, proteomics, metabolomics, epidemiological data and microbial data provide different angles to our understanding of gene-environment interactions and the determinants of disease and health. Our goal and our challenge are to integrate these very different types of data and perspectives of disease into a global model suitable for dissecting the mechanisms of disease and for predicting novel therapeutic strategies. This review aims to highlight the need for and problems with complex data integration, and proposes a framework for data integration. While there are many obstacles to overcome, biological models based upon multiple datasets will probably become the basis that drives future biomedical research.
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