trnamod
trnamod predicts post-transcriptional uridine modifications in transfer RNA (tRNA), specifically pseudouridine (Y) and dihydrouridine (D), using SVM-based hybrid models trained on MODOMICS datasets to provide kingdom-wise modification predictions.
Key Features:
- Prediction of Uridine Modifications: Predicts pseudouridine (Y) and dihydrouridine (D) occurrences in tRNA sequences.
- Kingdom-Wise Prediction Models: Implements a kingdom-wise approach with a three-step strategy that incorporates common and individualized datasets for domain-specific models.
- Hybrid Modeling: Combines binary and structural information in a hybrid feature representation to improve predictive accuracy.
- SVM-Based Classification and Performance: Trains Support Vector Machine (SVM) classifiers reporting Area Under the Curve (AUC) values of 0.936–0.987.
- Dataset and Validation: Constructs a common model using MODOMICS-2008 with five-fold cross-validation and performs subsequent evaluation and individual model development using MODOMICS-2012.
- Input Data Types: Supports predictions from both tRNA sequences and whole genome data.
- Modification Classification: Classifies predicted uridine modifications into specific modification types.
Scientific Applications:
- Genetic Regulation and Expression: Facilitates studies of how tRNA uridine modifications affect genetic regulation and gene expression.
- Genome Architecture and Protein Synthesis: Enables investigation of the implications of uridine modifications on genome architecture, codon usage, and protein synthesis.
- Comparative Genomics and Evolutionary Biology: Supports comparative and evolutionary analyses of tRNA modification patterns across biological kingdoms.
Methodology:
Uses a three-step strategy with a common model built from MODOMICS-2008 validated by five-fold cross-validation, followed by performance evaluation and development of individual kingdom-wise models using MODOMICS-2012; employs hybrid binary and structural features and Support Vector Machine (SVM) classifiers with reported AUCs of 0.936–0.987.
Topics
Details
- Tool Type:
- web application
- Operating Systems:
- Mac, Linux, Windows
- Added:
- 10/11/2022
- Last Updated:
- 10/11/2022
Operations
Data Inputs & Outputs
Analysis
Publications
Panwar B, Raghava GP. Prediction of uridine modifications in tRNA sequences. BMC Bioinformatics. 2014;15(1). doi:10.1186/1471-2105-15-326. PMID:25272949. PMCID:PMC4287530.