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Sökning: WFRF:(Moreau Yves) > Refereegranskat

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1.
  • Clermont, Gilles, et al. (författare)
  • Bridging the gap between systems biology and medicine
  • 2009
  • Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 1:9
  • 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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2.
  • Fayers, Peter M., et al. (författare)
  • Thalidomide for previously untreated elderly patients with multiple myeloma: meta-analysis of 1685 individual patient data from 6 randomized clinical trials
  • 2011
  • Ingår i: Blood. - : American Society of Hematology. - 1528-0020 .- 0006-4971. ; 118:5, s. 1239-1247
  • Tidskriftsartikel (refereegranskat)abstract
    • The role of thalidomide for previously untreated elderly patients with multiple myeloma remains unclear. Six randomized controlled trials, launched in or after 2000, compared melphalan and prednisone alone (MP) and with thalidomide (MPT). The effect on overall survival (OS) varied across trials. We carried out a meta-analysis of the 1685 individual patients in these trials. The primary endpoint was OS, and progression-free survival (PFS) and 1-year response rates were secondary endpoints. There was a highly significant benefit to OS from adding thalidomide to MP (hazard ratio = 0.83; 95% confidence interval 0.73-0.94, P = .004), representing increased median OS time of 6.6 months, from 32.7 months (MP) to 39.3 months (MPT). The thalidomide regimen was also associated with superior PFS (hazard ratio = 0.68, 95% confidence interval 0.61-0.76, P < .0001) and better 1-year response rates (partial response or better was 59% on MPT and 37% on MP). Although the trials differed in terms of patient baseline characteristics and thalidomide regimens, there was no evidence that treatment affected OS differently according to levels of the prognostic factors. We conclude that thalidomide added to MP improves OS and PFS in previously untreated elderly patients with multiple myeloma, extending the median survival time by on average 20%. (Blood. 2011;118(5):1239-1247)
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4.
  • Klionsky, Daniel J., et al. (författare)
  • Guidelines for the use and interpretation of assays for monitoring autophagy
  • 2012
  • Ingår i: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
  • Forskningsöversikt (refereegranskat)abstract
    • In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
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5.
  • Lage, Kasper, et al. (författare)
  • A human phenome-interactome network of protein complexes implicated in genetic disorders
  • 2007
  • Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1546-1696 .- 1087-0156. ; 25:3, s. 309-316
  • Tidskriftsartikel (refereegranskat)abstract
    • We performed a systematic, large-scale analysis of human protein complexes comprising gene products implicated in many different categories of human disease to create a phenome-interactome network. This was done by integrating quality-controlled interactions of human proteins with a validated, computationally derived phenotype similarity score, permitting identification of previously unknown complexes likely to be associated with disease. Using a phenomic ranking of protein complexes linked to human disease, we developed a Bayesian predictor that in 298 of 669 linkage intervals correctly ranks the known disease-causing protein as the top candidate, and in 870 intervals with no identified disease-causing gene, provides novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type 2 diabetes and coronary heart disease. Our publicly available draft of protein complexes associated with pathology comprises 506 complexes, which reveal functional relationships between disease-promoting genes that will inform future experimentation.
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6.
  • Oldenhof, Martijn, et al. (författare)
  • Industry-Scale Orchestrated Federated Learning for Drug Discovery
  • 2023
  • Ingår i: Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023. ; 37, s. 15576-15584
  • Konferensbidrag (refereegranskat)abstract
    • To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n°831472), which was comprised of 10 pharmaceutical companies, academic research labs, large industrial companies and startups. The MELLODDY platform was the first industry-scale platform to enable the creation of a global federated model for drug discovery without sharing the confidential data sets of the individual partners. The federated model was trained on the platform by aggregating the gradients of all contributing partners in a cryptographic, secure way following each training iteration. The platform was deployed on an Amazon Web Services (AWS) multi-account architecture running Kubernetes clusters in private subnets. Organisationally, the roles of the different partners were codified as different rights and permissions on the platform and administrated in a decentralized way. The MELLODDY platform generated new scientific discoveries which are described in a companion paper.
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7.
  • Ripatti, Samuli, et al. (författare)
  • GENESTAT : an information portal for design and analysis of genetic association studies
  • 2009
  • Ingår i: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 17:4, s. 533-536
  • Tidskriftsartikel (refereegranskat)abstract
    • We present the rationale, the background and the structure for version 2.0 of the GENESTAT information portal (www.genestat.org) for statistical genetics. The fast methodological advances, coupled with a range of standalone software, makes it difficult for expert as well as non-expert users to orientate when designing and analysing their genetic studies. The ultimate ambition of GENESTAT is to guide on statistical methodology related to the broad spectrum of research in genetic epidemiology. GENESTAT 2.0 focuses on genetic association studies. Each entry provides a summary of a topic and gives links to key papers, websites and software. The flexibility of the internet is utilised for cross-referencing and for open editing. This paper gives an overview of GENESTAT and gives short introductions to the current main topics in GENESTAT, with additional entries on the website. Methods and software developers are invited to contribute to the portal, which is powered by a Wikipedia-type engine and allows easy additions and editing.
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