In-silico prediction of blood-secretory human proteins using a ranking algorithm.
In-silico prediction of blood-secretory human proteins using a ranking algorithm.
复制标题
使用排名算法对血液分泌的人类蛋白质进行计算机预测
DOI：
10.1186/1471-2105-11-250
复制
发表时间：
2010-05-14
影响因子：
3
通讯作者：
Xu Y
中科院分区：
文献类型：
--
作者：
Liu Q;Cui J;Yang Q;Xu Y
背景
Background
Computational identification of blood-secretory proteins, especially proteins with differentially expressed genes in diseased tissues, can provide highly useful information in linking transcriptomic data to proteomic studies for targeted disease biomarker discovery in serum.
Results
A new algorithm for prediction of blood-secretory proteins is presented using an information-retrieval technique, called manifold ranking. On a dataset containing 305 known blood-secretory human proteins and a large number of other proteins that are either not blood-secretory or unknown, the new method performs better than the previous published method, measured in terms of the area under the recall-precision curve (AUC). A key advantage of the presented method is that it does not explicitly require a negative training set, which could often be noisy or difficult to derive for most biological problems, hence making our method more applicable than classification-based data mining methods in general biological studies.
Conclusion
We believe that our program will prove to be very useful to biomedical researchers who are interested in finding serum markers, especially when they have candidate proteins derived through transcriptomic or proteomic analyses of diseased tissues. A computer program is developed for prediction of blood-secretory proteins based on manifold ranking, which is accessible at our website http://csbl.bmb.uga.edu/publications/materials/qiliu/blood_secretory_protein.html.
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影响因子：
5.8
作者：
Cui, Juan;Liu, Qi;Xu, Ying
通讯作者：
Xu, Ying
DOI：
10.1093/bioinformatics/btn175
发表时间：
2008-07-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Xu Y;Zhou X;Zhang W
通讯作者：
Zhang W
DOI：
10.3109/00365519509090559
发表时间：
1995-01-01
影响因子：
2.1
作者：
MALM, J;LILJA, H
通讯作者：
LILJA, H
影响因子：
3
作者：
Xue C;Li F;He T;Liu GP;Li Y;Zhang X
通讯作者：
Zhang X
影响因子：
8.8
作者：
通讯作者：
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