Patent ID: 11908140
Assignee: ZHEJIANG LAB
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 5:
6. The method for identifying a protein domain based on the protein three-dimensional structure image according to claim 1, wherein the edge-connected convolutional operation of the edge-connected convolutional layers comprises:
denoting an edge-connecting feature between an atomic point ki and an atomic point ki in the local directed graph as eij, and denoting an edge-connected set of the atomic point ki and K-nearest neighbor atomic points as Ei; and an edge-connecting feature eijm between the atomic point ki and the atomic point kj outputted by an mth convolutional kernel is calculated as follows:

eijm=hΘ(θm·(Fkj−Fki),φm·Fki,ωm·HBkikj)

where hΘ represents a non-linear function, Fkj−Fki represents a feature distance between the atomic point ki and the atomic point kj, Fki represents a point cloud feature of the atomic point ki, and HBkikj represents whether a condition for forming a hydrogen bond between the atomic point ki and the atomic point kj exists; hΘ has a group of learnable parameters Θ, Θ=(θ1, . . . , θM, φ1, . . . φM, ω1, . . . , ωM), coding M different convolutional kernels; θm represents a convolutional kernel with a same dimension as Fkj−Fki, φm represents a convolutional kernel with the same dimension as Fki, ωm represents a convolutional kernel with a same dimension as HBkikj, and · represents an Euclidean inner product; and
applying a maximum pooling operation to the edge-connecting feature of the K-nearest neighbor atomic points of each atomic point ki, recording a local feature vector of the atomic point ki after a convolutional operation as Wki=[Wki1, . . . , WkiM], and a local feature generated by an mth convolutional kernel as Wkim=maxj:(i,j)∈Eieijm, wherein j:(i,j)∈Ei represents a connected edge between the atomic point ki and a nearest neighbor atomic point ki belonging to Ei.