A transversal approach to predict gene product networks from ontology-based similarity.
A transversal approach to predict gene product networks from ontology-based similarity.
复制标题
一种从基于本体的相似性预测基因产品网络的横向方法。
DOI：
10.1186/1471-2105-8-235
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发表时间：
2007-07-02
影响因子：
3
通讯作者：
Burgun A
中科院分区：
文献类型：
--
作者：
Chabalier J;Mosser J;Burgun A
转录组学数据的解释通常通过“标准”方法进行，该方法包括根据基因的表达模式对基因进行聚类，并利用每个表达簇中的基因本体（GO）注释。这种方法很难强调属于不同表达簇的基因产物之间的功能关系。为了解决这个问题，我们提出了一个横向分析，旨在基于GO过程和数据表达的组合来预测功能网络。本文提出的横向方法是在向量空间模型中计算基因产物之间的语义相似度。通过对注释的加权方案，我们考虑到注释基因产物的术语的代表性。比较标注向量得到基因产物相似性矩阵。结合表达数据，矩阵显示为一组功能基因网络。横向方法应用于186个与肠细胞分化阶段相关的基因。这种方法导致18个功能网络被证明具有生物学相关性。这些结果与通过标准方法和基于信息内容相似度的方法获得的结果进行了比较。作为标准方法的补充，横向方法通过结合基于语义相似性和数据表达的基因产物网络，提供了对细胞机制的新见解，并揭示了新的研究假设。
Interpretation of transcriptomic data is usually made through a "standard" approach which consists in clustering the genes according to their expression patterns and exploiting Gene Ontology (GO) annotations within each expression cluster. This approach makes it difficult to underline functional relationships between gene products that belong to different expression clusters. To address this issue, we propose a transversal analysis that aims to predict functional networks based on a combination of GO processes and data expression. The transversal approach presented in this paper consists in computing the semantic similarity between gene products in a Vector Space Model. Through a weighting scheme over the annotations, we take into account the representativity of the terms that annotate a gene product. Comparing annotation vectors results in a matrix of gene product similarities. Combined with expression data, the matrix is displayed as a set of functional gene networks. The transversal approach was applied to 186 genes related to the enterocyte differentiation stages. This approach resulted in 18 functional networks proved to be biologically relevant. These results were compared with those obtained through a standard approach and with an approach based on information content similarity. Complementary to the standard approach, the transversal approach offers new insight into the cellular mechanisms and reveals new research hypotheses by combining gene product networks based on semantic similarity, and data expression.
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影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
影响因子：
6.8
作者：
Gerstein, M;Jansen, R
通讯作者：
Jansen, R
影响因子：
30.8
作者：
Jenssen, TK;Lægreid, A;Hovig, E
通讯作者：
Hovig, E
影响因子：
7
作者：
Gibbons, FD;Roth, FP
通讯作者：
Roth, FP
NCBI GEO：开采数以百万计的表达概况 - 数据库和工具更新。
影响因子：
14.9
作者：
Barrett, Tanya;Troup, Dennis B.;Wilhite, Stephen E.;Ledoux, Pierre;Rudnev, Dmitry;Evangelista, Carlos;Kim, Irene F.;Soboleva, Alexandra;Tomashevsky, Maxim;Edgar, Ron
通讯作者：
Edgar, Ron