A text-mining system for extracting metabolic reactions from full-text articles.
A text-mining system for extracting metabolic reactions from full-text articles.
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一种用于从全文文章中提取代谢反应的文本挖掘系统。
DOI：
10.1186/1471-2105-13-172
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发表时间：
2012-07-23
影响因子：
3
通讯作者：
Shepherd AJ
中科院分区：
文献类型：
--
作者：
Czarnecki J;Nobeli I;Smith AM;Shepherd AJ
越来越多的生物文本挖掘研究集中在提取与生物网络和途径的构建和管理相关的复杂关系。然而，一类重要的途径-代谢途径-在很大程度上被忽视了。在这里，我们提出了一个相对简单的方法，用于从自由文本中提取代谢反应信息，该自由文本基于词干关键字的存在和位置，在给定的句子中对指定实体（酶和代谢物）的不同排列进行评分。该方法扩展了在蛋白质-蛋白质相互作用提取的背景下已被证明有效的方法。当使用标准性能标准对一组手动管理的代谢途径进行评估时，我们的方法表现得令人惊讶地好。精确度和召回率与以前众所周知的蛋白质-蛋白质相互作用提取任务所达到的水平相当。我们的结论是，自动化的代谢途径的建设是更容易处理的比通常被认为是，（在蛋白质-蛋白质相互作用提取的情况下）相对简单的文本挖掘方法可以证明是令人惊讶的有效。希望这些结果将为进一步的研究提供动力，并作为一个有用的基准来判断尚待开发的更复杂的方法的性能。
Increasingly biological text mining research is focusing on the extraction of complex relationships relevant to the construction and curation of biological networks and pathways. However, one important category of pathway — metabolic pathways — has been largely neglected. Here we present a relatively simple method for extracting metabolic reaction information from free text that scores different permutations of assigned entities (enzymes and metabolites) within a given sentence based on the presence and location of stemmed keywords. This method extends an approach that has proved effective in the context of the extraction of protein–protein interactions. When evaluated on a set of manually-curated metabolic pathways using standard performance criteria, our method performs surprisingly well. Precision and recall rates are comparable to those previously achieved for the well-known protein-protein interaction extraction task. We conclude that automated metabolic pathway construction is more tractable than has often been assumed, and that (as in the case of protein–protein interaction extraction) relatively simple text-mining approaches can prove surprisingly effective. It is hoped that these results will provide an impetus to further research and act as a useful benchmark for judging the performance of more sophisticated methods that are yet to be developed.
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影响因子：
6.4
作者：
Blaschke, C;Valencia, A
通讯作者：
Valencia, A
影响因子：
3
作者：
Kabiljo R;Clegg AB;Shepherd AJ
通讯作者：
Shepherd AJ
影响因子：
5.8
作者：
Novichkova, S;Egorov, S;Daraselia, N
通讯作者：
Daraselia, N
DOI：
10.1109/icimw.2009.5324773
发表时间：
2009-01-01
期刊：
METHODS IN BIOENGINEERING: SYSTEMS ANALYSIS OF BIOLOGICAL NETWORKS
影响因子：
--
作者：
Kim, Jin-Hong;Asthagiri, Anand R.
通讯作者：
Asthagiri, Anand R.
影响因子：
3
作者：
Kim JD;Ohta T;Tsujii J
通讯作者：
Tsujii J