2015
Cai, Hong; Lilburn, Timothy G; Hong, Changjin; Gu, Jianying; Kuang, Rui; Wang, Yufeng
Predicting and exploring network components involved in pathogenesis in the malaria parasite via novel subnetwork alignments Journal Article
In: BMC systems biology, vol. 9, no. 4, pp. 1, 2015.
BibTeX | Tags: Network Alignment, Protein-Protein Interaction Network
@article{cai2015predicting,
title = {Predicting and exploring network components involved in pathogenesis in the malaria parasite via novel subnetwork alignments},
author = {Cai, Hong and Lilburn, Timothy G and Hong, Changjin and Gu, Jianying and Kuang, Rui and Wang, Yufeng},
year = {2015},
date = {2015-01-01},
journal = {BMC systems biology},
volume = {9},
number = {4},
pages = {1},
publisher = {BioMed Central},
keywords = {Network Alignment, Protein-Protein Interaction Network},
pubstate = {published},
tppubtype = {article}
}
2013
Cai, Hong; Hong, Changjin; Lilburn, Timothy G; Rodriguez, Armando L; Chen, Sheng; Gu, Jianying; Kuang, Rui; Wang, Yufeng
A novel subnetwork alignment approach predicts new components of the cell cycle regulatory apparatus in Plasmodium falciparum Journal Article
In: BMC bioinformatics, vol. 14, no. 12, pp. 1, 2013, ISSN: 1471-2105.
Abstract | Links | BibTeX | Tags: Network Alignment
@article{cai2013novel,
title = {A novel subnetwork alignment approach predicts new components of the cell cycle regulatory apparatus in Plasmodium falciparum},
author = {Hong Cai and Changjin Hong and Timothy G Lilburn and Armando L Rodriguez and Sheng Chen and Jianying Gu and Rui Kuang and Yufeng Wang},
url = {http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-S12-S2},
doi = {10.1186/1471-2105-14-S12-S2},
issn = {1471-2105},
year = {2013},
date = {2013-09-24},
journal = {BMC bioinformatics},
volume = {14},
number = {12},
pages = {1},
publisher = {BioMed Central},
abstract = {Background
According to the World Health organization, half the world's population is at risk of contracting malaria. They estimated that in 2010 there were 219 million cases of malaria, resulting in 660,000 deaths and an enormous economic burden on the countries where malaria is endemic. The adoption of various high-throughput genomics-based techniques by malaria researchers has meant that new avenues to the study of this disease are being explored and new targets for controlling the disease are being developed. Here, we apply a novel neighborhood subnetwork alignment approach to identify the interacting elements that help regulate the cell cycle of the malaria parasite Plasmodium falciparum.
Results
Our novel subnetwork alignment approach was used to compare networks in Escherichia coli and P. falciparum. Some 574 P. falciparum proteins were revealed as functional orthologs of known cell cycle proteins in E. coli. Over one third of these predicted functional orthologs were annotated as "conserved Plasmodium proteins" or "putative uncharacterized proteins" of unknown function. The predicted functionalities included cyclins, kinases, surface antigens, transcriptional regulators and various functions related to DNA replication, repair and cell division.
Conclusions
The results of our analysis demonstrate the power of our subnetwork alignment approach to assign functionality to previously unannotated proteins. Here, the focus was on proteins involved in cell cycle regulation. These proteins are involved in the control of diverse aspects of the parasite lifecycle and of important aspects of pathogenesis.},
keywords = {Network Alignment},
pubstate = {published},
tppubtype = {article}
}
Background
According to the World Health organization, half the world's population is at risk of contracting malaria. They estimated that in 2010 there were 219 million cases of malaria, resulting in 660,000 deaths and an enormous economic burden on the countries where malaria is endemic. The adoption of various high-throughput genomics-based techniques by malaria researchers has meant that new avenues to the study of this disease are being explored and new targets for controlling the disease are being developed. Here, we apply a novel neighborhood subnetwork alignment approach to identify the interacting elements that help regulate the cell cycle of the malaria parasite Plasmodium falciparum.
Results
Our novel subnetwork alignment approach was used to compare networks in Escherichia coli and P. falciparum. Some 574 P. falciparum proteins were revealed as functional orthologs of known cell cycle proteins in E. coli. Over one third of these predicted functional orthologs were annotated as "conserved Plasmodium proteins" or "putative uncharacterized proteins" of unknown function. The predicted functionalities included cyclins, kinases, surface antigens, transcriptional regulators and various functions related to DNA replication, repair and cell division.
Conclusions
The results of our analysis demonstrate the power of our subnetwork alignment approach to assign functionality to previously unannotated proteins. Here, the focus was on proteins involved in cell cycle regulation. These proteins are involved in the control of diverse aspects of the parasite lifecycle and of important aspects of pathogenesis.
According to the World Health organization, half the world's population is at risk of contracting malaria. They estimated that in 2010 there were 219 million cases of malaria, resulting in 660,000 deaths and an enormous economic burden on the countries where malaria is endemic. The adoption of various high-throughput genomics-based techniques by malaria researchers has meant that new avenues to the study of this disease are being explored and new targets for controlling the disease are being developed. Here, we apply a novel neighborhood subnetwork alignment approach to identify the interacting elements that help regulate the cell cycle of the malaria parasite Plasmodium falciparum.
Results
Our novel subnetwork alignment approach was used to compare networks in Escherichia coli and P. falciparum. Some 574 P. falciparum proteins were revealed as functional orthologs of known cell cycle proteins in E. coli. Over one third of these predicted functional orthologs were annotated as "conserved Plasmodium proteins" or "putative uncharacterized proteins" of unknown function. The predicted functionalities included cyclins, kinases, surface antigens, transcriptional regulators and various functions related to DNA replication, repair and cell division.
Conclusions
The results of our analysis demonstrate the power of our subnetwork alignment approach to assign functionality to previously unannotated proteins. Here, the focus was on proteins involved in cell cycle regulation. These proteins are involved in the control of diverse aspects of the parasite lifecycle and of important aspects of pathogenesis.