Limits...
A hybrid computational method for the discovery of novel reproduction-related genes.

Chen L, Chu C, Kong X, Huang G, Huang T, Cai YD - PLoS ONE (2015)

Bottom Line: In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research.Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST.The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

View Article: PubMed Central - PubMed

Affiliation: College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, People's Republic of China.

ABSTRACT
Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

No MeSH data available.


The workflow of hybrid method for novel reproduction gene identification.(A-E) were the steps of graph-based method, (F) was to filter candidates of the graph based method with similarity-based method and interaction-based method. (A) The known reproduction genes (red nodes) were mapped onto network. (B) The shortest path genes (green nodes) on shortest paths (dash line) were identified. (C) The known reproduction genes were permuted. (D) The shortest path genes on the shortest path between permuted reproduction genes were identified. (E) The actual betweenness of shortest path genes were compared with permuted betweenness and the genes that were not specific to reproduction were removed. (F) The candidates of the graph based method were further filtered by checking alignment score and interaction confidence score with known reproduction genes and novel candidate reproduction genes were selected if they were selected by graph-based method, similarity-based method and interaction-based method.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4358884&req=5

pone.0117090.g001: The workflow of hybrid method for novel reproduction gene identification.(A-E) were the steps of graph-based method, (F) was to filter candidates of the graph based method with similarity-based method and interaction-based method. (A) The known reproduction genes (red nodes) were mapped onto network. (B) The shortest path genes (green nodes) on shortest paths (dash line) were identified. (C) The known reproduction genes were permuted. (D) The shortest path genes on the shortest path between permuted reproduction genes were identified. (E) The actual betweenness of shortest path genes were compared with permuted betweenness and the genes that were not specific to reproduction were removed. (F) The candidates of the graph based method were further filtered by checking alignment score and interaction confidence score with known reproduction genes and novel candidate reproduction genes were selected if they were selected by graph-based method, similarity-based method and interaction-based method.

Mentions: The workflow of the hybrid method was shown in Fig. 1.


A hybrid computational method for the discovery of novel reproduction-related genes.

Chen L, Chu C, Kong X, Huang G, Huang T, Cai YD - PLoS ONE (2015)

The workflow of hybrid method for novel reproduction gene identification.(A-E) were the steps of graph-based method, (F) was to filter candidates of the graph based method with similarity-based method and interaction-based method. (A) The known reproduction genes (red nodes) were mapped onto network. (B) The shortest path genes (green nodes) on shortest paths (dash line) were identified. (C) The known reproduction genes were permuted. (D) The shortest path genes on the shortest path between permuted reproduction genes were identified. (E) The actual betweenness of shortest path genes were compared with permuted betweenness and the genes that were not specific to reproduction were removed. (F) The candidates of the graph based method were further filtered by checking alignment score and interaction confidence score with known reproduction genes and novel candidate reproduction genes were selected if they were selected by graph-based method, similarity-based method and interaction-based method.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4358884&req=5

pone.0117090.g001: The workflow of hybrid method for novel reproduction gene identification.(A-E) were the steps of graph-based method, (F) was to filter candidates of the graph based method with similarity-based method and interaction-based method. (A) The known reproduction genes (red nodes) were mapped onto network. (B) The shortest path genes (green nodes) on shortest paths (dash line) were identified. (C) The known reproduction genes were permuted. (D) The shortest path genes on the shortest path between permuted reproduction genes were identified. (E) The actual betweenness of shortest path genes were compared with permuted betweenness and the genes that were not specific to reproduction were removed. (F) The candidates of the graph based method were further filtered by checking alignment score and interaction confidence score with known reproduction genes and novel candidate reproduction genes were selected if they were selected by graph-based method, similarity-based method and interaction-based method.
Mentions: The workflow of the hybrid method was shown in Fig. 1.

Bottom Line: In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research.Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST.The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

View Article: PubMed Central - PubMed

Affiliation: College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, People's Republic of China.

ABSTRACT
Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

No MeSH data available.