Large-scale automated machine reading discovers new cancer-driving mechanisms.

Large-scale automated machine reading discovers new cancer-driving mechanisms.
复制标题

DOI:
10.1093/database/bay098
复制
发表时间:
2018-01-01
期刊:
Database : the journal of biological databases and curation
影响因子:
--
通讯作者:
Morrison CT
Morrison CT
中科院分区:
其他
文献类型:
--
作者:
Valenzuela-Escárcega MA;Babur Ö;Hahn-Powell G;Bell D;Hicks T;Noriega-Atala E;Wang X;Surdeanu M;Demir E;Morrison CT

文献摘要

参考文献

被引文献

相似文献

PubMed是一个生物医学文献资源库和搜索引擎,现在每年索引100万篇文章。这超出了人类领域专家的处理能力,限制了我们真正了解许多疾病的能力。我们提出了Reach,一个用于生物医学论文的自动化大规模机器阅读系统,可以在高通量下以相对较高的精度提取生物过程的机制描述。我们证明,将提取的途径片段与现有的生物数据分析算法相结合,这些算法依赖于精心设计的模型,有助于识别和解释7种不同癌症类型中大量以前未识别的互斥改变的信号通路。这项工作表明,将人类策划的“大机制”与提取的“大数据”相结合,可以导致对细胞过程的因果性、预测性理解,并解锁重要的下游应用。
PubMed, a repository and search engine for biomedical literature, now indexes >1 million articles each year. This exceeds the processing capacity of human domain experts, limiting our ability to truly understand many diseases. We present Reach, a system for automated, large-scale machine reading of biomedical papers that can extract mechanistic descriptions of biological processes with relatively high precision at high throughput. We demonstrate that combining the extracted pathway fragments with existing biological data analysis algorithms that rely on curated models helps identify and explain a large number of previously unidentified mutually exclusive altered signaling pathways in seven different cancer types. This work shows that combining human-curated ‘big mechanisms’ with extracted ‘big data’ can lead to a causal, predictive understanding of cellular processes and unlock important downstream applications.
DOI: 10.1093/nar/gkq287
发表时间: 2010-09
影响因子: 14.9
作者:
Babur O;Demir E;Gönen M;Sander C;Dogrusoz U
通讯作者: Dogrusoz U
推断因果分子网络:通过基于社区的努力进行的经验评估。
DOI: 10.1038/nmeth.3773
发表时间: 2016-04
期刊: Nature methods
影响因子: 48
作者:
Hill SM;Heiser LM;Cokelaer T;Unger M;Nesser NK;Carlin DE;Zhang Y;Sokolov A;Paull EO;Wong CK;Graim K;Bivol A;Wang H;Zhu F;Afsari B;Danilova LV;Favorov AV;Lee WS;Taylor D;Hu CW;Long BL;Noren DP;Bisberg AJ;HPN-DREAM Consortium;Mills GB;Gray JW;Kellen M;Norman T;Friend S;Qutub AA;Fertig EJ;Guan Y;Song M;Stuart JM;Spellman PT;Koeppl H;Stolovitzky G;Saez-Rodriguez J;Mukherjee S
通讯作者: Mukherjee S
DOI: 10.1152/ajpcell.00177.2017
发表时间: 2018-05-01
影响因子: 5.5
作者:
Babur, Ozgun;Ngo, Anh T. P.;Aslan, Joseph E.
通讯作者: Aslan, Joseph E.
DOI: 10.1093/bioinformatics/btu164
发表时间: 2014-07-15
期刊: Bioinformatics (Oxford, England)
影响因子: --
作者:
Aksoy BA;Demir E;Babur Ö;Wang W;Jing X;Schultz N;Sander C
通讯作者: Sander C
生物公约概述:生物学信息提取的批判性评估。
DOI: 10.1186/1471-2105-6-s1-s1
发表时间: 2005
期刊: BMC bioinformatics
影响因子: 3
作者:
Hirschman L;Yeh A;Blaschke C;Valencia A
通讯作者: Valencia A