Sevilla José L, Segura Víctor, Podhorski Adam, Guruceaga Elizabeth, Mato José M, Martínez-Cruz Luis A, Corrales Fernando J, Rubio Angel
Strathmore University, Ole Sangale Road, Madaraka Estate, PO Box 59857, 00200 Nairobi, Kenya.
IEEE/ACM Trans Comput Biol Bioinform. 2005 Oct-Dec;2(4):330-8. doi: 10.1109/TCBB.2005.50.
This research analyzes some aspects of the relationship between gene expression, gene function, and gene annotation. Many recent studies are implicitly based on the assumption that gene products that are biologically and functionally related would maintain this similarity both in their expression profiles as well as in their Gene Ontology (GO) annotation. We analyze how accurate this assumption proves to be using real publicly available data. We also aim to validate a measure of semantic similarity for GO annotation. We use the Pearson correlation coefficient and its absolute value as a measure of similarity between expression profiles of gene products. We explore a number of semantic similarity measures (Resnik, Jiang, and Lin) and compute the similarity between gene products annotated using the GO. Finally, we compute correlation coefficients to compare gene expression similarity against GO semantic similarity. Our results suggest that the Resnik similarity measure outperforms the others and seems better suited for use in Gene Ontology. We also deduce that there seems to be correlation between semantic similarity in the GO annotation and gene expression for the three GO ontologies. We show that this correlation is negligible up to a certain semantic similarity value; then, for higher similarity values, the relationship trend becomes almost linear. These results can be used to augment the knowledge provided by clustering algorithms and in the development of bioinformatic tools for finding and characterizing gene products.
本研究分析了基因表达、基因功能和基因注释之间关系的若干方面。许多近期研究隐含地基于这样一种假设，即具有生物学和功能相关性的基因产物在其表达谱以及基因本体论（GO）注释方面都将保持这种相似性。我们使用真实的公开可用数据来分析这一假设的准确程度。我们还旨在验证一种用于GO注释的语义相似性度量。我们使用皮尔逊相关系数及其绝对值作为基因产物表达谱之间相似性的度量。我们探索了多种语义相似性度量（雷斯尼克、蒋和林），并计算了使用GO注释的基因产物之间的相似性。最后，我们计算相关系数以比较基因表达相似性与GO语义相似性。我们的结果表明，雷斯尼克相似性度量优于其他度量，似乎更适合用于基因本体论。我们还推断，对于三种GO本体，GO注释中的语义相似性与基因表达之间似乎存在相关性。我们表明，在达到某个语义相似性值之前，这种相关性可以忽略不计；然后，对于更高的相似性值，关系趋势几乎变为线性。这些结果可用于扩充聚类算法提供的知识，并用于开发用于查找和表征基因产物的生物信息学工具。
