Kinannote, a computer program to identify and classify members of the eukaryotic protein kinase superfamily.
Kinannote, a computer program to identify and classify members of the eukaryotic protein kinase superfamily.
复制标题
DOI：
10.1093/bioinformatics/btt419
复制
发表时间：
2013-10-01
期刊：
影响因子：
--
通讯作者：
Zeng Q
中科院分区：
文献类型：
--
作者：
Goldberg JM;Griggs AD;Smith JL;Haas BJ;Wortman JR;Zeng Q
动机：真核蛋白激酶超家族的激酶是真核细胞行为大多数方面的关键调节因子，并提供了多种药物靶点，包括癌症中失调的激酶。基因组序列数量的快速增加迫切需要有效、准确地识别和分类这一重要酶类的成员。结果：Kinannote 使用单行命令生成激酶组草案并对预测的蛋白质组进行比较分析，它是目前唯一使用 Hanks 和 Hunter 的受控词汇自动分类蛋白激酶的工具 [Hanks and Hunter (1995)]。 Kinannote 使用隐藏马尔可夫模型与位置特异性评分矩阵相结合来识别激酶，随后使用与 KinBase（来自 www.kinase.com 的精选蛋白激酶数据集）本地版本的 BLAST 比较进行分类。 Kinannote 对来自四个不同物种的预测蛋白质组进行了测试。测试物种激酶组检索的平均灵敏度和精确度分别为 94.4% 和 96.8%。还评估了 Kinannote 对已识别激酶进行分类的能力，对保守激酶进行完全分类的平均灵敏度和精确度分别为 71.5% 和 82.5%。 Kinannote 对真核基因组注释产生了重大影响，为 Broad Institute 从 2009 年至今公开的 36 个基因组提供了蛋白激酶注释。可用性：Kinannote 可在 http://sourceforge.net/projects/kinannote 免费获取。联系方式：jmgold@broadinstitute.org 补充信息：补充数据可在生物信息学在线获取。
Motivation: Kinases of the eukaryotic protein kinase superfamily are key regulators of most aspects eukaryotic cellular behavior and have provided several drug targets including kinases dysregulated in cancers. The rapid increase in the number of genomic sequences has created an acute need to identify and classify members of this important class of enzymes efficiently and accurately. Results: Kinannote produces a draft kinome and comparative analyses for a predicted proteome using a single line command, and it is currently the only tool that automatically classifies protein kinases using the controlled vocabulary of Hanks and Hunter [Hanks and Hunter (1995)]. A hidden Markov model in combination with a position-specific scoring matrix is used by Kinannote to identify kinases, which are subsequently classified using a BLAST comparison with a local version of KinBase, the curated protein kinase dataset from www.kinase.com. Kinannote was tested on the predicted proteomes from four divergent species. The average sensitivity and precision for kinome retrieval from the test species are 94.4 and 96.8%. The ability of Kinannote to classify identified kinases was also evaluated, and the average sensitivity and precision for full classification of conserved kinases are 71.5 and 82.5%, respectively. Kinannote has had a significant impact on eukaryotic genome annotation, providing protein kinase annotations for 36 genomes made public by the Broad Institute in the period spanning 2009 to the present. Availability: Kinannote is freely available at http://sourceforge.net/projects/kinannote. Contact: jmgold@broadinstitute.org Supplementary information: Supplementary data are available at Bioinformatics online.
登录
查看更多内容
DOI：
10.1073/pnas.89.22.10915
发表时间：
1992-11-15
影响因子：
11.1
作者：
HENIKOFF, S;HENIKOFF, JG
通讯作者：
HENIKOFF, JG
毛磷脂和相关皮肤植物的比较基因组分析揭示了参与感染的候选基因。
影响因子：
6.4
作者：
Martinez DA;Oliver BG;Gräser Y;Goldberg JM;Li W;Martinez-Rossi NM;Monod M;Shelest E;Barton RC;Birch E;Brakhage AA;Chen Z;Gurr SJ;Heiman D;Heitman J;Kosti I;Rossi A;Saif S;Samalova M;Saunders CW;Shea T;Summerbell RC;Xu J;Young S;Zeng Q;Birren BW;Cuomo CA;White TC
通讯作者：
White TC
Prokino：癌症蛋白激酶综合分析的本体。
影响因子：
3.7
作者：
Gosal G;Kochut KJ;Kannan N
通讯作者：
Kannan N
影响因子：
4.5
作者：
Goldberg, Jonathan M.;Manning, Gerard;Liu, Allen;Fey, Petra;Pilcher, Karen E.;Xu, Yanji;Smith, Janet L.
通讯作者：
Smith, Janet L.
影响因子：
30.8
作者：
Desjardins, Christopher A.;Cerqueira, Gustavo C.;Goldberg, Jonathan M.;Hotopp, Julie C. Dunning;Haas, Brian J.;Zucker, Jeremy;Ribeiro, Jose M. C.;Saif, Sakina;Levin, Joshua Z.;Fan, Lin;Zeng, Qiandong;Russ, Carsten;Wortman, Jennifer R.;Fink, Doran L.;Birren, Bruce W.;Nutman, Thomas B.
通讯作者：
Nutman, Thomas B.