Comparing Bitmapped microRNA Structure Images using Mutual Symmetry

We present a high-throughput method for analyzing large-scale bitmapped bio-data: processing of elongated molecular structures by 2D images and analyzing their shapes for chemoinformatics databases. Two-dimensional structure databases are transfered to bitmap images — a commonly used visualization widely spread online. Then, an efficient clustering of the molecular structures is achieved by a mutual symmetry-based binary matrix representation of the shapes. We present a method to compute the difference between two of such representations and evaluate its performance with respect to time and quality of matching. In our tests we use two bitmap databases, one containing true human microRNA folded 2D structures and one with claimed human microRNA folded 2D structures. We show the stability of the matching with respect to parameterization and orientation of the shapes. Our method enables a good automatic clustering of structures with high visual similarity.