Furney Simon J, Higgins Desmond G, Ouzounis Christos A, López-Bigas Núria
Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.
BMC Genomics. 2006 Jan 11;7:3. doi: 10.1186/1471-2164-7-3.
One of the main goals of cancer genetics is to identify the causative elements at the molecular level leading to cancer.
We have conducted an analysis of a set of genes known to be involved in cancer in order to unveil their unique features that can assist towards the identification of new candidate cancer genes.
We have detected key patterns in this group of genes in terms of the molecular function or the biological process in which they are involved as well as sequence properties. Based on these features we have developed an accurate Bayesian classification model with which human genes have been scored for their likelihood of involvement in cancer.
癌症遗传学的主要目标之一是在分子水平上识别导致癌症的致病因素。
我们对一组已知与癌症相关的基因进行了分析,以揭示它们的独特特征,这些特征有助于识别新的候选癌症基因。
我们已经在这组基因中检测到了关键模式,这些模式涉及它们所参与的分子功能或生物学过程以及序列特性。基于这些特征,我们开发了一个准确的贝叶斯分类模型,通过该模型对人类基因参与癌症的可能性进行了评分。