Nim Hieu T, Furtado Milena B, Costa Mauro W, Rosenthal Nadia A, Kitano Hiroaki, Boyd Sarah E
Systems Biology Institute (SBI) Australia, Monash University, Clayton, VIC, 3800, Australia.
Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, 3800, Australia.
BMC Bioinformatics. 2015 May 1;16(1):141. doi: 10.1186/s12859-015-0578-0.
Existing de novo software platforms have largely overlooked a valuable resource, the expertise of the intended biologist users. Typical data representations such as long gene lists, or highly dense and overlapping transcription factor networks often hinder biologists from relating these results to their expertise.
VISIONET, a streamlined visualisation tool built from experimental needs, enables biologists to transform large and dense overlapping transcription factor networks into sparse human-readable graphs via numerically filtering. The VISIONET interface allows users without a computing background to interactively explore and filter their data, and empowers them to apply their specialist knowledge on far more complex and substantial data sets than is currently possible. Applying VISIONET to the Tbx20-Gata4 transcription factor network led to the discovery and validation of Aldh1a2, an essential developmental gene associated with various important cardiac disorders, as a healthy adult cardiac fibroblast gene co-regulated by cardiogenic transcription factors Gata4 and Tbx20.
We demonstrate with experimental validations the utility of VISIONET for expertise-driven gene discovery that opens new experimental directions that would not otherwise have been identified.
现有的从头开始构建的软件平台在很大程度上忽略了一个宝贵的资源，即目标生物学家用户的专业知识。典型的数据表示形式，如长长的基因列表，或高度密集且相互重叠的转录因子网络，常常阻碍生物学家将这些结果与他们的专业知识联系起来。
VISIONET是一个根据实验需求构建的简化可视化工具，它使生物学家能够通过数值过滤将大型且密集的重叠转录因子网络转化为稀疏的、人类可读的图表。VISIONET界面允许没有计算背景的用户交互式地探索和过滤他们的数据，并使他们能够将自己的专业知识应用于比目前可能的情况复杂得多且规模大得多的数据集。将VISIONET应用于Tbx20 - Gata4转录因子网络，发现并验证了Aldh1a2，这是一个与各种重要心脏疾病相关的关键发育基因，是由心脏发生转录因子Gata4和Tbx20共同调控的健康成年心脏成纤维细胞基因。
我们通过实验验证证明了VISIONET在专业知识驱动的基因发现中的效用，它开辟了新的实验方向，否则这些方向是无法被识别的。
