Year: 2024
Type: article
Abstract: Recent studies have confirmed that certain circRNAs encode proteins that are integral to various biological functions. In this study, we present CICADA, an algorithm specifically designed to assess the protein-coding potential and coding products of circRNAs at high throughput, which enables the identification of previously unknown circRNA-encoded proteins. By harnessing the potential of this algorithm, we identified a variety of functional, protein-coding circRNAs in esophageal squamous cell carcinoma and established circRNA translation profiles for diverse types of cancer. This advancement innovatively explores the hidden proteome within the genome, poised to catalyze discoveries in biomarkers and therapies for cancers and complex diseases. CICADA is accessible as a Python module (https://github.com/SunLab-biotool/CICADA).
Source: Nucleic Acids Research
DOI: 10.1093/nar/gkae1179
Language: English
Topic: Circular RNAs in diseases
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $4,192
Awards: 长链非编码RNA中的短肽序列鉴定与特征研究, G6261221074
OpenAlex ID: W4405726213
