Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: Translational disease interpretation with molecular networks | Review Translational disease interpretation with molecular networks Anais Baudot Gonzalo Gómez-López and Alfonso Valencia These authors contributed equally to this work Address Structural Biology and Biocomputing Programme Spanish National Cancer Research Centre CNIO C Melchor Fernandez Almagro 3 E-28029 Madrid Spain. Correspondence Alfonso Valencia. Email avalencia@ Published 29 June 2009 Genome Biology2009 10 221 doi gb-2009-l0-6-22l The electronic version of this article is the complete one and can be found online at http 2009 l0 6 22l 2009 BioMed Central Ltd Abstract Molecular networks are being used to reconcile genotypes and phenotypes by integrating medical information. In this context networks will be instrumental for the interpretation of disease at the personalized medicine level. Genes and proteins do not function in isolation in the cell but are integrated into a global network of interactions between cellular components. Even if current networks mainly describe protein-protein interactions other biological relations including gene regulation control by small RNAs enzymatic reactions and other interactions are progressively being integrated. The complete network of interactions along with addition of the fundamental dimensions of time and space will ultimately provide a complete picture of cellular functions. As phenotypic disorders can arise from abnormalities in genes knowing the functions of the corresponding proteins can provide clues to understanding the molecular basis of disease especially of complex diseases such as diabetes and cancer. High-throughput genomic analyses have been applied to study these complex multifactorial diseases. They produce a tremendous amount of raw data that are however difficult to interpret due for instance to problems of reproducibility functional interpretation and statistical shortcomings which have often led to controversial findings 1 . To better interpret such high-throughput .
