Benchmarking ortholog identification methods using functional genomics data.
Benchmarking ortholog identification methods using functional genomics data.
复制标题
使用功能基因组学数据的基准测试直系同源识别方法。
DOI:
10.1186/gb-2006-7-4-r31
复制
发表时间:
2006
期刊:
影响因子:
12.3
通讯作者:
Groenen PM
中科院分区:
文献类型:
--
作者:
Hulsen T;Huynen MA;de Vlieg J;Groenen PM
A benchmarking of the most popular orthologous identification methods using functional genomics data identifies the two best methods. The transfer of functional annotations from model organism proteins to human proteins is one of the main applications of comparative genomics. Various methods are used to analyze cross-species orthologous relationships according to an operational definition of orthology. Often the definition of orthology is incorrectly interpreted as a prediction of proteins that are functionally equivalent across species, while in fact it only defines the existence of a common ancestor for a gene in different species. However, it has been demonstrated that orthologs often reveal significant functional similarity. Therefore, the quality of the orthology prediction is an important factor in the transfer of functional annotations (and other related information). To identify protein pairs with the highest possible functional similarity, it is important to qualify ortholog identification methods. To measure the similarity in function of proteins from different species we used functional genomics data, such as expression data and protein interaction data. We tested several of the most popular ortholog identification methods. In general, we observed a sensitivity/selectivity trade-off: the functional similarity scores per orthologous pair of sequences become higher when the number of proteins included in the ortholog groups decreases. By combining the sensitivity and the selectivity into an overall score, we show that the InParanoid program is the best ortholog identification method in terms of identifying functionally equivalent proteins.
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DOI:
10.1073/pnas.0402591101
发表时间:
2004-06-15
影响因子:
11.1
作者:
Fraser, HB;Hirsh, AE;Eisen, MB
通讯作者:
Eisen, MB
影响因子:
5.8
作者:
Sjölander, K
通讯作者:
Sjölander, K
影响因子:
14.9
作者:
Harris, MA;Clark, J;White, R
通讯作者:
White, R
影响因子:
120.7
作者:
COTE, RA;ROBBOY, S
通讯作者:
ROBBOY, S
影响因子:
7
作者:
Curwen, V;Eyras, E;Clamp, M
通讯作者:
Clamp, M