MicroRNA(miRNA) is a small, single stranded non-coding RNA which plays an important regulatory role in gene expression. Additionally, miRNAs perform crucial functions in a wide range of biological processes. These functions may be exploited for miRNA-mediated regulation of protein-protein interaction and thus protein function. Many computational methods have been developed to predict the miRNA targets and to explore the regulatory mechanism between miRNA and protein. However, the efforts to investigate important positions within miRNAs are not comprehensive. This paper presents a framework to identify important positions using collision entropy. The information of contained in the sequence and secondary structure of miRNAs is considered. Further, the single base collision entropy and the adjacent base related collision entropy are integrated to measure the importance of miRNA position. Two thresholds are employed to select those positions with more biological meaning. A dataset of Drosophila melanogaster is used in the experiments. The results demonstrate that our approach can find interesting and important positions within miRNAs and may lead to a better understanding of miRNA biogenesis and function.