1. Devising Isolation Forest-Based Method to Investigate the sRNAome of Using sRNA-seq Data
- Author
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Upasana Maity, Ritika Aggarwal, Rami Balasubramanian, Divya Lakshmi Venkatraman, and Shubhada R Hegde
- Subjects
Biology (General) ,QH301-705.5 - Abstract
Small non-coding RNAs (sRNAs) regulate the synthesis of virulence factors and other pathogenic traits, which enables the bacteria to survive and proliferate after host infection. While high-throughput sequencing data have proved useful in identifying sRNAs from the intergenic regions (IGRs) of the genome, it remains a challenge to present a complete genome-wide map of the expression of the sRNAs. Moreover, existing methodologies necessitate multiple dependencies for executing their algorithm and also lack a targeted approach for the de novo sRNA identification. We developed an Isolation Forest algorithm-based method and the tool Prediction Of sRNAs using Isolation Forest for the de novo identification of sRNAs from available bacterial sRNA-seq data ( http://posif.ibab.ac.in/ ). Using this framework, we predicted 1120 sRNAs and 46 small proteins in Mycobacterium tuberculosis . Besides, we highlight the context-dependent expression of novel sRNAs, their probable synthesis, and their potential relevance in stress response mechanisms manifested by M. tuberculosis.
- Published
- 2024
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