Functional Interpretation of Gene Sets: Semantic-Based Clustering of Gene Ontology Terms on the BioTest Platform

被引:3
作者
Gruca, Aleksandra [1 ]
Jaksik, Roman [2 ]
Psiuk-Maksymowicz, Krzysztof [2 ]
机构
[1] Silesian Tech Univ, Inst Informat, Ul Akad 16, PL-44100 Gliwice, Poland
[2] Silesian Tech Univ, Inst Automat Control, Ul Akad 16, PL-44100 Gliwice, Poland
来源
MAN-MACHINE INTERACTIONS 5, ICMMI 2017 | 2018年 / 659卷
关键词
Gene Ontology; Clustering; Semantic similarity; BioTest platform; DNA microarrays; Molecular profiling; Functional interpretation; SIMILARITY;
D O I
10.1007/978-3-319-67792-7_13
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Modern high-throughput technologies based on genome, transcriptome or proteome profiling provide abundance of data that needs to be processed, analyzed and, finally, interpreted. Effective and efficient analysis of data coming from molecular profiling is crucial for a detailed diagnosis, prognosis, and prediction of therapy outcome. Meaningful conclusions can be drawn only by the use of sophisticated methods for biomedical and molecular data analysis and interpretation. In this study we present the approach for functional interpretation of gene or protein sets with clusters of Gene Ontology terms. We analyze transcription profiles of human cell line K562 and we show that clustering allows grouping functionally related GO terms and therefore obtaining more concise and comprehensive description. By applying cluster-specific data aggregation tool we are able to calculate statistics for the individual clusters of GO terms and compare the number of differentially expressed genes between two sample pairs. The presented tool is implemented as a part of annotation module available on the BioTest remote platform for hypothesis testing and analysis of biomedical data.
引用
收藏
页码:125 / 136
页数:12
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