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báo cáo khoa học: " Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme | Ovaska et al. Genome Medicine 2010 2 65 http genomemedicine.eom content 2 9 65 Genome Medicine RESEARCH Open Access Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme 1 1Ỷ 2Ỷ 1 1 1 Kristian Ovaska Marko Laakso Saija Haapa-Paananen Riku Louhimo Ping Chen Viljami Aittomaki Erkka Valo1 Javier Núhez-Fontarnau1 Ville Rantanen1 Sirkku Karinen1 Kari Nousiainen1 Anna-Maria Lahesmaa-Korpinen1 Minna Miettinen1 Lilli Saarinen1 Pekka Kohonen2 Jianmin Wu1 Jukka Westermarck3 4 Sampsa Hautaniemi1 Abstract Background Coordinated efforts to collect large-scale data sets provide a basis for systems level understanding of complex diseases. In order to translate these fragmented and heterogeneous data sets into knowledge and medical benefits advanced computational methods for data analysis integration and visualization are needed. Methods We introduce a novel data integration framework Anduril for translating fragmented large-scale data into testable predictions. The Anduril framework allows rapid integration of heterogeneous data with state-of-the-art computational methods and existing knowledge in bio-databases. Anduril automatically generates thorough summary reports and a website that shows the most relevant features of each gene at a glance allows sorting of data based on different parameters and provides direct links to more detailed data on genes transcripts or genomic regions. Anduril is open-source all methods and documentation are freely available. Results We have integrated multidimensional molecular and clinical data from 338 subjects having glioblastoma multiforme one of the deadliest and most poorly understood cancers using Anduril. The central objective of our approach is to identify genetic loci and genes that have significant survival effect. Our results suggest several novel genetic alterations linked to glioblastoma multiforme progression and more specifically reveal Moesin as a novel glioblastoma multiforme-associated .