A Multiobjective Evolutionary Conceptual Clustering Methodology for Gene Annotation Within Structural Databases: A Case of Study on the Gene Ontology Database

2008 ◽  
Vol 12 (6) ◽  
pp. 679-701 ◽  
Author(s):  
R.C. Romero-Zaliz ◽  
C. Rubio-Escudero ◽  
J.P. Cobb ◽  
F. Herrera ◽  
O. Cordon ◽  
...  
2004 ◽  
Vol 20 (18) ◽  
pp. 3442-3454 ◽  
Author(s):  
E. Shoop ◽  
P. Casaes ◽  
G. Onsongo ◽  
L. Lesnett ◽  
E. O. Petursdottir ◽  
...  

Author(s):  
R. Romero-Zaliz ◽  
C. Rubio-Escudero ◽  
O. Cordón ◽  
O. Harari ◽  
C. del Val ◽  
...  

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Casper van Mourik ◽  
Rezvan Ehsani ◽  
Finn Drabløs

Abstract Objective Properties of gene products can be described or annotated with Gene Ontology (GO) terms. But for many genes we have limited information about their products, for example with respect to function. This is particularly true for long non-coding RNAs (lncRNAs), where the function in most cases is unknown. However, it has been shown that annotation as described by GO terms to some extent can be predicted by enrichment analysis on properties of co-expressed genes. Results GAPGOM integrates two relevant algorithms, lncRNA2GOA and TopoICSim, into a user-friendly R package. Here lncRNA2GOA does annotation prediction by co-expression, whereas TopoICSim estimates similarity between GO graphs, which can be used for benchmarking of prediction performance, but also for comparison of GO graphs in general. The package provides an improved implementation of the original tools, with substantial improvements in performance and documentation, unified interfaces, and additional features.


BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Audrey Gloux ◽  
Michel J. Duclos ◽  
Aurélien Brionne ◽  
Marie Bourin ◽  
Yves Nys ◽  
...  

Abstract Background At sexual maturity, the liver of laying hens undergoes many metabolic changes to support vitellogenesis. In published transcriptomic approaches, hundreds of genes were reported to be overexpressed in laying hens and functional gene annotation using gene ontology tools have essentially revealed an enrichment in lipid and protein metabolisms. We reanalyzed some data from a previously published article comparing 38-week old versus 10-week old hens to give a more integrative view of the functions stimulated in the liver at sexual maturity and to move beyond current physiological knowledge. Functions were defined based on information available in Uniprot database and published literature. Results Of the 516 genes previously shown to be overexpressed in the liver of laying hens, 475 were intracellular (1.23–50.72 fold changes), while only 36 were predicted to be secreted (1.35–66.93 fold changes) and 5 had no related information on their cellular location. Besides lipogenesis and protein metabolism, we demonstrated that the liver of laying hens overexpresses several clock genes (which supports the circadian control of liver metabolic functions) and was likely to be involved in a liver/brain/liver circuit (neurotransmitter transport), in thyroid and steroid hormones metabolisms. Many genes were associated with anatomical structure development, organ homeostasis but also regulation of blood pressure. As expected, several secreted proteins are incorporated in yolky follicles but we also evidenced that some proteins are likely participating in fertilization (ZP1, MFGE8, LINC00954, OVOCH1) and in thyroid hormone maturation (CPQ). We also proposed that secreted proteins (PHOSPHO1, FGF23, BMP7 but also vitamin-binding proteins) may contribute to the development of peripheral organs including the formation of medullar bones to provide labile calcium for eggshell formation. Thirteen genes are uniquely found in chicken/bird but not in human species, which strengthens that some of these genes may be specifically related to avian reproduction. Conclusions This study gives additional hypotheses on some molecular actors and mechanisms that are involved in basic physiological function of the liver at sexual maturity of hen. It also revealed some additional functions that accompany reproductive capacities of laying hens, and that are usually underestimated when using classical gene ontology approaches.


2018 ◽  
Author(s):  
Eugene W. Hinderer ◽  
Robert M. Flight ◽  
Rashmi Dubey ◽  
James N. MacLeod ◽  
Hunter N.B. Moseley

AbstractGene-annotation enrichment is a common method for utilizing ontology-based annotations in these gene and gene-product centric knowledgebases. Effective utilization of these annotations requires inferring semantic linkages by tracing paths through the ontology through edges in the ontological graph, referred to as relations. However, some relations are semantically problematic with respect to scope, necessitating their omission lest erroneous term mappings occur. To address these issues, we present GOcats, a novel tool that organizes the Gene Ontology (GO) into subgraphs representing user-defined concepts, while ensuring that all appropriate relations are congruent with respect to scoping semantics. Here, we demonstrate the improvements in annotation enrichment by re-interpreting edges that would otherwise be omitted by traditional ancestor path-tracing methods.We demonstrate that GOcats’ unique handling of relations improves enrichment over conventional methods in the analysis of two different gene-expression datasets: a breast cancer microarray dataset and several horse cartilage development RNAseq datasets. With the breast cancer microarray dataset, we observed significant improvement (one-sided binomial test p-value=1.86E-25) in 182 of 217 significantly enriched GO terms identified from the conventional path traversal method when GOcats’ path traversal was used. We also found new significantly enriched terms using GOcats, whose biological relevancy has been experimentally demonstrated elsewhere. Likewise, on the horse RNAseq datasets, we observed a significant improvement in GO term enrichment when using GOcat’s path traversal: one-sided binomial test p-values range from 1.32E-03 to 2.58E-44.


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