ArticleNucleic acids research2021
ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics.
Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Microbial Omics.Progress in molecular and subcellular biology · 2026Review
- DEWNA: dynamic entropy weight network analysis and its application to the DNA-binding proteome in A549 cells with cisplatin-induced damage.Briefings in bioinformatics · 2024Article
- Epigenetic silencing of ZIC4 unveils a potential tumor suppressor role in pediatric choroid plexus carcinoma.Scientific reports · 2024Article
- OmicScope unravels systems-level insights from quantitative proteomics data.Nature communications · 2024Article
- Proteomic profiling of cerebrospinal fluid in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease.World journal of pediatrics : WJP · 2024Article
- CURTAIN-A unique web-based tool for exploration and sharing of MS-based proteomics data.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Tidyproteomics: an open-source R package and data object for quantitative proteomics post analysis and visualization.BMC bioinformatics · 2023Article
- The Application of Internet of Things Data Analysis in the Development of International Trade.Computational intelligence and neuroscience · 2022Article
- OmicsOne: associate omics data with phenotypes in one-click.Clinical proteomics · 2021Article
- Proteomes Are of Proteoforms: Embracing the Complexity.Proteomes · 2021Review
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Authors and funding
10 authors.
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Abstract
Bottom-up proteomics analyses have been proved over the last years to be a powerful tool in the characterization of the proteome and are crucial for understanding cellular and organism behaviour. Through differential proteomic analysis researchers can shed light on groups of proteins or individual proteins that play key roles in certain, normal or pathological conditions. However, several tools for the analysis of such complex datasets are powerful, but hard-to-use with steep learning curves. In addition, some other tools are easy to use, but are weak in terms of analytical power. Previously, we have introduced ProteoSign, a powerful, yet user-friendly open-source online platform for protein differential expression/abundance analysis designed with the end-proteomics user in mind. Part of Proteosign's power stems from the utilization of the well-established Linear Models For Microarray Data (LIMMA) methodology. Here, we present a substantial upgrade of this computational resource, called ProteoSign v2, where we introduce major improvements, also based on user feedback. The new version offers more plot options, supports additional experimental designs, analyzes updated input datasets and performs a gene enrichment analysis of the differentially expressed proteins. We also introduce the deployment of the Docker technology and significantly increase the speed of a full analysis. ProteoSign v2 is available at http://bioinformatics.med.uoc.gr/ProteoSign.
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