ArticleDatabase : the journal of biological databases and curation2015
PEIMAN 1.0: Post-translational modification Enrichment, Integration and Matching ANalysis.
Article in Database : the journal of biological databases and curation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A dataset supporting Combinatorial Proteome Integral Solubility/Stability Alteration Analysis (CoPISA).Scientific data · 2026Article
- Monitoring Functional Posttranslational Modifications Using a Data-Driven Proteome Informatic Pipeline.Proteomics · 2025Article
- A Review for Artificial Intelligence Based Protein Subcellular Localization.Biomolecules · 2024Review
- A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction.Genomics, proteomics & bioinformatics · 2023Review
- IrGO: Iranian traditional medicine General Ontology and knowledge base.Journal of biomedical semantics · 2021Article
- Posttranslational modifications in proteins: resources, tools and prediction methods.Database : the journal of biological databases and curation · 2021Article
- Advances on Plant Ubiquitylome-From Mechanism to Application.International journal of molecular sciences · 2020Review
- Proteomics of hot-wet and cold-dry temperaments proposed in Iranian traditional medicine: a Network-based Study.Scientific reports · 2016Article
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Authors and funding
3 authors.
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Abstract
Conventional proteomics has discovered a wide gap between protein sequences and biological functions. The third generation of proteomics was provoked to bridge this gap. Targeted and untargeted post-translational modification (PTM) studies are the most important parts of today's proteomics. Considering the expensive and time-consuming nature of experimental methods, computational methods are developed to study, analyze, predict, count and compute the PTM annotations on proteins. The enrichment analysis softwares are among the common computational biology and bioinformatic software packages. The focus of such softwares is to find the probability of occurrence of the desired biological features in any arbitrary list of genes/proteins. We introduce Post-translational modification Enrichment Integration and Matching Analysis (PEIMAN) software to explore more probable and enriched PTMs on proteins. Here, we also represent the statistics of detected PTM terms used in enrichment analysis in PEIMAN software based on the latest released version of UniProtKB/Swiss-Prot. These results, in addition to giving insight to any given list of proteins, could be useful to design targeted PTM studies for identification and characterization of special chemical groups. Database URL: http://bs.ipm.ir/softwares/PEIMAN/
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