Title:AdmiRePred Dataset – Abundant and non‑abundant microRNA (miRNA) sequences in blood exosomes Description: Project: AdmiRePred – A method for predicting abundant miRNAs in exosomes Publication: Arora, A., & Raghava, G.P.S. (2025). AdmiRePred: A method for predicting abundant miRNAs in Exosomes. bioRxiv. https://doi.org/10.1101/2025.03.19.644072 Overview: This dataset accompanies AdmiRePred, a method for predicting miRNAs that are abundantly present in blood exosomes under normal conditions. Exosomes carry miRNAs that reflect the physiological state of parent cells, making them promising non‑invasive biomarkers for liquid biopsy (cancer, cardiovascular, neurodegenerative diseases). Unlike prior binary methods (exosomal vs. non‑exosomal), this study uses expression‑based classification to identify miRNAs highly expressed in exosomes, establishing a baseline for disease‑specific variation. Content: The dataset contains miRNA sequences with expression data from EVmiRNA (blood exosomes, serum/plasma, normal human subjects, n=60) and validated with GEO GSE270497. Class Definition Count Length range Abundant (positive) Average RPKM > 2 348 16–25 nt Non‑abundant (negative) Average RPKM 2; Non‑abundant = RPKM < 1 Redundancy: Duplicates removed Length range: 16–25 nucleotides Train/validation split: 80/20 (5‑fold CV on training) Usage: Predicting highly abundant miRNAs in blood exosomes for liquid biopsy biomarker discovery; designing mutant miRNAs with altered exosomal abundance (Design module); similarity search against known abundant/non‑abundant miRNA database (BLAST module); establishing baseline for disease‑specific miRNA variation studies. Related Resources: Web server: https://webs.iiitd.edu.in/raghava/admirepred/ | GitHub: https://github.com/raghavagps/admirepred Contact: raghava@iiitd.ac.in (Gajendra P. S. Raghava)