Zeyu Lu, Xue Xiao, Qiang Zheng, Xinlei Wang, Lin Xu
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引用次数: 0
摘要
本文深入评述了利用查询基因组预测转录调控因子(TRs)的计算方法。转录调节因子的鉴定在许多生物学应用中都至关重要,包括但不限于阐明生物发展机制、鉴定关键疾病基因和预测治疗靶点。在过去十年中,基于新一代测序(NGS)数据的各种计算方法相继问世,但尚未对基于 NGS 的方法进行系统评估。我们根据这些方法的共同特点将其分为两类,即基于文库的方法和基于区域的方法。我们进一步开展了基准研究,利用分子实验数据集评估基于 NGS 方法的准确性、灵敏度、覆盖率和可用性。结果表明,BART、ChIP-Atlas 和 Lisa 的性能相对较好。此外,我们还指出了基于 NGS 方法的局限性,并探讨了进一步改进的潜在方向。
Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets.
This article provides an in-depth review of computational methods for predicting transcriptional regulators (TRs) with query gene sets. Identification of TRs is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement.
期刊介绍:
Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data.
The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.