关键词：芯片；生物医学；高维数据集
摘 要：The analysis of microarray and similar high-dimensional datasets requires advanced visualization techniques that are now more readily available in standard analysis tools of choice for most life scientists. While the above-described visualization techniques may help confirm and/or form new hypotheses, it is important to stress that other sources of data such as pathways, ontologies, and external and previously published data can augment primary microarray experiment data, making it more complex, but in many ways easier to comprehend. We should not neglect the domain expertise that can play a major role in microarray data analysis since only a domain expert may be able to determine whether identified patterns or lists of genes carry biological significance, and has the capacity to test them in a wet lab setting. In any case, microarrays proved to be an indispensable technology for studies related to the behavior of genes under various conditions. The techniques described above represent the basis for the visual analysis of microarray experiment data and are an important step of its general analysis. At the same time, they serve as a stepping stone for further utilization with advanced and novel visual techniques in the rapidly evolving field of biomedical visualization.