Biclustering has emerged as a powerful approach to identifying functional patterns in complex biological data. However, existing tools are limited by their accuracy and efficiency to recognize various kinds of complex biclusters submerged in ever large datasets. We introduce a novel fast and highly accurate algorithm RecBic to identify various forms of complex biclusters in gene expression datasets.

中文翻译：

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RecBic：一种快速，准确的算法，可识别保持趋势的双曲线。

比对已经成为一种在复杂的生物数据中识别功能模式的强大方法。但是，现有工具的准确性和效率受到限制，无法识别淹没在越来越大的数据集中的各种复杂的二类聚类。我们介绍了一种新颖，快速，准确的算法RecBic，用于识别基因表达数据集中各种形式的复杂双簇。