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Systematic Analysis of the Molecular Mechanism Underlying Decidualization Using a Text Mining Approach.

Liu JL, Wang TS - PLoS ONE (2015)

Bottom Line: Decidualization is a crucial process for successful embryo implantation and pregnancy in humans.We prioritized genes in this network and identified 12 genes that may be key regulators of decidualization.These findings would provide some clues for further research on the mechanism underlying decidualization.

View Article: PubMed Central - PubMed

Affiliation: College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China.

ABSTRACT
Decidualization is a crucial process for successful embryo implantation and pregnancy in humans. Defects in decidualization during early pregnancy are associated with several pregnancy complications, such as pre-eclampsia, intrauterine growth restriction and recurrent pregnancy loss. However, the mechanism underlying decidualization remains poorly understood. In the present study, we performed a systematic analysis of decidualization-related genes using text mining. We identified 286 genes for humans and 287 genes for mice respectively, with an overlap of 111 genes shared by both species. Through enrichment test, we demonstrated that although divergence was observed, the majority of enriched gene ontology terms and pathways were shared by both species, suggesting that functional categories were more conserved than individual genes. We further constructed a decidualization-related protein-protein interaction network consisted of 344 nodes connected via 1,541 edges. We prioritized genes in this network and identified 12 genes that may be key regulators of decidualization. These findings would provide some clues for further research on the mechanism underlying decidualization.

No MeSH data available.


Related in: MedlinePlus

Systematic identification of genes associated with decidualization in humans and mice through text mining.(A) Overview of the text mining process. (B) The cumulative number of publications on decidualization. The PubMed database was used to identify publications related to decidualization from 1980-Jan to 2014-Aug. (C) Venn diagram comparing the gene sets associated with decidualization in humans and mice, respectively.
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pone.0134585.g001: Systematic identification of genes associated with decidualization in humans and mice through text mining.(A) Overview of the text mining process. (B) The cumulative number of publications on decidualization. The PubMed database was used to identify publications related to decidualization from 1980-Jan to 2014-Aug. (C) Venn diagram comparing the gene sets associated with decidualization in humans and mice, respectively.

Mentions: Gene mention recognition was performed using two different gene mention taggers, the hidden Markov model (HMM) tagger implemented in LingPipe and the ABNER tagger [18] based on a machine learning system of conditional random fields (CRF). Gene mentions detected by both taggers were merged. Because researchers name the genes in a highly variable manner, we built a gene synonym dictionary from Entrez gene database [19]. This dictionary was used for the gene name normalization process during which gene mentions were mapped to unique Entrez genes using exact string match. If multiple Entrez genes were linked to the same gene mention, the ambiguity was resolved manually. In order to reduce false positives, we required co-occurrence of decidualization mention and gene mention within a single sentence. In general, the abstract is sufficient for our text mining task, as it contains the most important findings of an article. However, articles on high throughput experiments often reveal a large number of genes which cannot be fully listed in the abstracts. For these articles, we downloaded full texts (as well as supplementary files if needed) and extracted gene mentions by hands. Finally, we compiled two gene sets: one is associated with human decidualization and the other one is associated with mouse decidualization. To ensure accurate and complete recording, each gene was checked manually and additional references were provided if possible. A flow chart illustrating the text mining procedure is shown in Fig 1A.


Systematic Analysis of the Molecular Mechanism Underlying Decidualization Using a Text Mining Approach.

Liu JL, Wang TS - PLoS ONE (2015)

Systematic identification of genes associated with decidualization in humans and mice through text mining.(A) Overview of the text mining process. (B) The cumulative number of publications on decidualization. The PubMed database was used to identify publications related to decidualization from 1980-Jan to 2014-Aug. (C) Venn diagram comparing the gene sets associated with decidualization in humans and mice, respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4519252&req=5

pone.0134585.g001: Systematic identification of genes associated with decidualization in humans and mice through text mining.(A) Overview of the text mining process. (B) The cumulative number of publications on decidualization. The PubMed database was used to identify publications related to decidualization from 1980-Jan to 2014-Aug. (C) Venn diagram comparing the gene sets associated with decidualization in humans and mice, respectively.
Mentions: Gene mention recognition was performed using two different gene mention taggers, the hidden Markov model (HMM) tagger implemented in LingPipe and the ABNER tagger [18] based on a machine learning system of conditional random fields (CRF). Gene mentions detected by both taggers were merged. Because researchers name the genes in a highly variable manner, we built a gene synonym dictionary from Entrez gene database [19]. This dictionary was used for the gene name normalization process during which gene mentions were mapped to unique Entrez genes using exact string match. If multiple Entrez genes were linked to the same gene mention, the ambiguity was resolved manually. In order to reduce false positives, we required co-occurrence of decidualization mention and gene mention within a single sentence. In general, the abstract is sufficient for our text mining task, as it contains the most important findings of an article. However, articles on high throughput experiments often reveal a large number of genes which cannot be fully listed in the abstracts. For these articles, we downloaded full texts (as well as supplementary files if needed) and extracted gene mentions by hands. Finally, we compiled two gene sets: one is associated with human decidualization and the other one is associated with mouse decidualization. To ensure accurate and complete recording, each gene was checked manually and additional references were provided if possible. A flow chart illustrating the text mining procedure is shown in Fig 1A.

Bottom Line: Decidualization is a crucial process for successful embryo implantation and pregnancy in humans.We prioritized genes in this network and identified 12 genes that may be key regulators of decidualization.These findings would provide some clues for further research on the mechanism underlying decidualization.

View Article: PubMed Central - PubMed

Affiliation: College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China.

ABSTRACT
Decidualization is a crucial process for successful embryo implantation and pregnancy in humans. Defects in decidualization during early pregnancy are associated with several pregnancy complications, such as pre-eclampsia, intrauterine growth restriction and recurrent pregnancy loss. However, the mechanism underlying decidualization remains poorly understood. In the present study, we performed a systematic analysis of decidualization-related genes using text mining. We identified 286 genes for humans and 287 genes for mice respectively, with an overlap of 111 genes shared by both species. Through enrichment test, we demonstrated that although divergence was observed, the majority of enriched gene ontology terms and pathways were shared by both species, suggesting that functional categories were more conserved than individual genes. We further constructed a decidualization-related protein-protein interaction network consisted of 344 nodes connected via 1,541 edges. We prioritized genes in this network and identified 12 genes that may be key regulators of decidualization. These findings would provide some clues for further research on the mechanism underlying decidualization.

No MeSH data available.


Related in: MedlinePlus