# From Biological Gene to Functional Gene: Revolutionizing Product Innovation Design
## 4 Research on the Application of Functional Gene
### Functional Gene Coding Forms  
The effective genetic information of biological genes are determined by the arrangement order of the bases. In the DNA molecule, the arrangement order of the four bases, adenine (A), guanine (G), thymine (T), and cytosine (C), constitutes genetic information [67]. The genetic system based on DNA base sequence provides a stable way to store genetic traits [68]. Compared with traditional storage methods, using DNA as an information carrier has advantages such as high storage density [69] and low maintenance cost [70]. By imitating the form of biological DNA bases and storing data in synthetic DNA molecules, it is possible to meet the storage needs of massive amounts of data [71; 72]. The idea of encoding biological genes has also been widely used in computer data storage [73], information encryption [74], quality inspection [75], manufacturing system scheduling [76], intelligent algorithm optimization [77], and other fields. The complex and voluminous content of design knowledge poses significant challenges to traditional data storage methods. Scholars have drawn inspiration from the encoding ideas of biological genes to encode product functional information, enabling the storage of design knowledge for subsequent design use. The core of functional gene encoding is the standardized expression of functional information, which can be classified into three main categories based on different emphases: (1) expression through functional features [78]; (2) expression through functional constraints; (3) expression through input-output transformation [79]. The core of functional gene research is to facilitate the reuse of design knowledge. In order to comprehensively record functional features, components' behavioral information and structural geometric features are recorded. [PERSON] et al. [80] expressed component behavior through geometric features and expressed functions through component behavior. The functional gene is represented as F = f(G\({}_{1}\), G\({}_{2}\),..., G\({}_{\rm m}\)), where G\({}_{\rm m}\) represents the specific component behavior for that function, G\({}_{\rm m}\) = [[b\({}_{\rm i}\), U\({}_{\rm C}\) (b\({}_{\rm i}\))]], and U\({}_{\rm C}\) (b\({}_{\rm i}\)) represents the geometric features affected by the behavior. [PERSON] et al. [81] defined the standardized form of genes as action verbs and key attributes. Based on recording functional information through physical attributes (PA), behavior (B), geometric attributes (GA), etc., they defined address (N), promoter (Start), and terminator (End), forming the gene encoding form [Start, N, PA, B, GA, End]. The reuse of design knowledge is not a simple accumulation. The implementation of functions needs to consider the influencing conditions during the process. [PERSON] et al. [82] proposed that the functional feature model N consists of action process features (T), action object features (P), and action condition features (C). They described the functional feature gene model of a product using the triplet N = (T, P, C). Similarly, [PERSON] [83] encoded functional genes as [V, O, P, EE, RP], using \"verb, object, property\" to represent functional information, and enabling factors (EF) to represent constraint conditions, status features, and technical requirements. Functionality is the understanding of a design system from a technical implementation perspective. It is an abstract description of the system's input-output parameters or state changes. To facilitate computer processing of functional genes and achieve the autonomous generation of solutions through the relationship among functional gene flows, [PERSON] et al. [84] represented product genes using data such as input-output physical quantities and technical implementation constraints, encoding functions as {N, IPU, OPU, NP, RP, EF}.