Dopazo Joaquín
Bioinformatics Department, Centro de Investigación Príncipe Felipe, Valencio, Spain.
Methods Mol Biol. 2010;576:363-74. doi: 10.1007/978-1-59745-545-9_19.
The introduction of new high-throughput methodologies such as DNA microarrays constitutes a major breakthrough in cancer research. The unprecedented amount of data produced by such technologies has opened new avenues for interrogating living systems although, at the same time, it has demanded of the development of new data analytical methods as well as new strategies for testing hypotheses. A history of early successful applications in cancer boosted the use of microarrays and fostered further applications in other fields. Keeping the pace with these technologies, bioinformatics offers new solutions for data analysis and, what is more important, permits the formulation of a new class of hypotheses inspired in systems biology, more oriented to pathways or, in general, to modules of functionally related genes. Although these analytical methodologies are new, some options are already available and are discussed in this chapter.
诸如DNA微阵列等新型高通量方法的引入是癌症研究中的一项重大突破。此类技术产生的前所未有的大量数据为研究生命系统开辟了新途径，不过与此同时，也需要开发新的数据分析方法以及检验假设的新策略。早期在癌症研究中的成功应用历史推动了微阵列的使用，并促进了其在其他领域的进一步应用。为跟上这些技术的步伐，生物信息学为数据分析提供了新的解决方案，更重要的是，它允许提出一类受系统生物学启发的新假设，这类假设更侧重于通路，或者总体上侧重于功能相关基因的模块。尽管这些分析方法很新颖，但本章已经讨论了一些可用的选项。
