ProteoMill: Efficient network-based functional analysis portal for proteomics data. Rydén, M., Englund, M., & Ali, N. Bioinformatics, May, 2021.
ProteoMill: Efficient network-based functional analysis portal for proteomics data [link]Paper  doi  abstract   bibtex   
Functional analysis has become a common approach to incorporate biological knowledge into the analysis of omics data, and to explore molecular events that govern a disease state. It is though only one step in a wider analytical pipeline that typically requires use of multiple individual analysis software. There is currently a need for a well-integrated omics analysis tool that performs all the steps. The ProteoMill portal is developed as an R Shiny application and integrates all necessary steps from data-upload, converting identifiers, to quality control, differential expression and network-based functional analysis into a single fast, interactive easy to use workflow. Further, it maintains annotation data sources up to date, overcoming a common problem with use of outdated information, and seamlessly integrates multiple R-packages for an improved user-experience. The functionality provided in this software can benefit researchers by facilitating the exploratory analysis of proteomics data.ProteoMill is available at https://proteomill.com.
@article{ryden_proteomill_2021,
	title = {{ProteoMill}: {Efficient} network-based functional analysis portal for proteomics data},
	issn = {1367-4803},
	shorttitle = {{ProteoMill}},
	url = {https://doi.org/10.1093/bioinformatics/btab373},
	doi = {10.1093/bioinformatics/btab373},
	abstract = {Functional analysis has become a common approach to incorporate biological knowledge into the analysis of omics data, and to explore molecular events that govern a disease state. It is though only one step in a wider analytical pipeline that typically requires use of multiple individual analysis software. There is currently a need for a well-integrated omics analysis tool that performs all the steps. The ProteoMill portal is developed as an R Shiny application and integrates all necessary steps from data-upload, converting identifiers, to quality control, differential expression and network-based functional analysis into a single fast, interactive easy to use workflow. Further, it maintains annotation data sources up to date, overcoming a common problem with use of outdated information, and seamlessly integrates multiple R-packages for an improved user-experience. The functionality provided in this software can benefit researchers by facilitating the exploratory analysis of proteomics data.ProteoMill is available at https://proteomill.com.},
	number = {btab373},
	urldate = {2021-05-17},
	journal = {Bioinformatics},
	author = {Rydén, Martin and Englund, Martin and Ali, Neserin},
	month = may,
	year = {2021},
}

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