Standard deep learning architectures typically composed of input, hidden, and output layers. Using DNA strands as inputs, which only contain sequences and structural information, poses challenges for predictive accuracy due to the lack of essential biological information. In this study, we proposed a novel method for preprocessing DNA strands into descriptor matrices, which involves three main steps: the construction of DNA strings, the creation of descriptors and integration of descriptor matrices (Figure ). The resulting descriptor matrices were organized into three rows: "descriptor number", "descriptor energy", and "descriptor entropy".