Evaluation of computational metabolic-pathway predictions for Helicobacter pylori
Evaluation of computational metabolic-pathway predictions for Helicobacter pylori
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DOI：
10.1093/bioinformatics/18.5.715
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发表时间：
2002-05-01
期刊：
影响因子：
5.8
通讯作者：
Karp, PD
中科院分区：
文献类型：
--
作者：
Paley, SM;Karp, PD
动机：我们试图确定在测序基因组中预测代谢途径的计算方法的准确性，并了解预测算法和这些算法使用的参考途径数据库对预测准确性的贡献。结果：我们进行的比较如下。(1)我们比较了我们早期版本的途径预测算法对幽门螺杆菌途径补体的两种预测：预测A使用EcoCyc大肠杆菌途径DB作为参考数据库（DB）进行预测，预测B使用MetaCyc途径DB （EcoCyc的超集）作为参考途径DB。基于metacyc的预测包含75%以上的路径预测，但我们认为这些预测中有相当一部分是假阳性。(2)我们比较了两种使用MetaCyc作为参考通路DB的幽门螺杆菌途径补体预测，但使用不同的算法：原始的PathoLogic算法和旨在消除假阳性途径预测的增强版本算法。与原始算法相比，改进算法预测的代谢途径减少30%；所有被淘汰的路径都被认为是假阳性预测。(3)我们将增强算法预测的98条路径与人工幽门螺杆菌路径分析的结果进行了比较。结果：40条计算预测路径与人工分析一致，13条路径被认为是假阳性预测，4条路径部分重叠拓扑。26条预测通路在人工分析中未被提及；我们相信这些是病理学的正确预测，而不是人工分析发现的。人工分析的5条路径没有通过计算找到。计算和人工预测之间的一致性总体上是好的，计算分析推断了许多人工分析没有确定的途径。最终，手工分析也是部分推测性的，因此不是对正确性的绝对度量。该算法的设计倾向于出现更多误报，从而为用户带来更多潜在的关注途径。所得的幽门螺杆菌路径数据库可在http://ecocyc.org:1555/HPY/organism-summary?object=HPY免费获得。
Motivation: We seek to determine the accuracy of computational methods for predicting metabolic pathways in sequenced genomes, and to understand the contributions of both the prediction algorithms, and the reference pathway databases used by those algorithms, to the prediction accuracy.Results: The comparisons we performed were as follows. (1) We compared two predictions of the pathway complements of Helicobacter pylori that were computed by an early version of our pathway-prediction algorithm: prediction A used the EcoCyc E. coli pathway DB as the reference database (DB) for prediction, and prediction B used the MetaCyc pathway DB (a superset of EcoCyc) as the reference pathway DB. The MetaCyc-based prediction contained 75% more pathway predictions, but we believe a significant number of those predictions were false positives. (2) We compared two predictions of the pathway complement of H. pylori that used MetaCyc as the reference pathway DB, but that used different algorithms: the original PathoLogic algorithm, and an enhanced version of the algorithm designed to eliminate false-positive pathway predictions. The improved algorithm predicted 30\% fewer metabolic pathways than the original algorithm; all of the eliminated pathways are believed to be false-positive predictions. (3) We compared the 98 pathways predicted by the enhanced algorithm with the results of a manual analysis of the pathways of H. pylori. Results: 40 of the computationally predicted pathways were consistent with the manual analysis, 13 pathways are considered false-positive predictions, and four pathways had partially overlapping topologies. Twenty-six predicted pathways were not mentioned in the manual analysis; we believe these are correct predictions by PathoLogic that were not found by the manual analysis. Five pathways from the manual analysis were not found computationally. Agreement between the computational and manual predictions was good overall, with the computational analysis inferring many pathways that the manual analysis did not identify. Ultimately the manual analysis is also partially speculative, and therefore is not an absolute measure of correctness. The algorithm is designed to err on the side of more false positives to bring more potential pathways to the user's attention. The resulting H. pylori pathway DB is freely available at http://ecocyc.org:1555/HPY/organism-summary?object=HPY.