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Analysis of networks of host proteins in the early time points following HIV transduction
- Source :
- BMC Bioinformatics, Vol 20, Iss 1, Pp 1-18 (2019), BMC Bioinformatics
- Publication Year :
- 2019
- Publisher :
- BMC, 2019.
-
Abstract
- Background Utilization of quantitative proteomics data on the network level is still a challenge in proteomics data analysis. Currently existing models use sophisticated, sometimes hard to implement analysis techniques. Our aim was to generate a relatively simple strategy for quantitative proteomics data analysis in order to utilize as much of the data generated in a proteomics experiment as possible. Results In this study, we applied label-free proteomics, and generated a network model utilizing both qualitative, and quantitative data, in order to examine the early host response to Human Immunodeficiency Virus type 1 (HIV-1). A weighted network model was generated based on the amount of proteins measured by mass spectrometry, and analysis of weighted networks and functional sub-networks revealed upregulation of proteins involved in translation, transcription, and DNA condensation in the early phase of the viral life-cycle. Conclusion A relatively simple strategy for network analysis was created and applied to examine the effect of HIV-1 on host cellular proteome. We believe that our model may prove beneficial in creating algorithms, allowing for both quantitative and qualitative studies of proteome change in various biological and pathological processes by quantitative mass spectrometry. Electronic supplementary material The online version of this article (10.1186/s12859-019-2990-3) contains supplementary material, which is available to authorized users.
- Subjects :
- Proteomics
Proteome
Biológiai tudományok
lcsh:Computer applications to medicine. Medical informatics
Mass Spectrometry
Természettudományok
lcsh:Biology (General)
Transduction, Genetic
Protein Interaction Mapping
Quantitative proteomics
Host response
HIV-1
Humans
lcsh:R858-859.7
lcsh:QH301-705.5
Weighted network
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 14712105
- Volume :
- 20
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- BMC Bioinformatics
- Accession number :
- edsair.pmid.dedup....cddf3385f6fb25cb8741f7851b95a4d7