Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A number of kernel-based machine algorithms have recently been used to study protein-protein interaction in the field of bioinformatics.   develop a kernel-based machine algorithm called multiple criteria quadratic programming (MCQP) to predict the distance range beten antibody interface residues and the antigen surface in antigen-antibody complex. Antibodies bind their antigen using residues, which are part of the hypervariable loops.   explore the interaction beten antibody interface residues and antigen in the study of antibody functions. The distance beten the antibody's interface residue and the antigen surface is one of the antigen-antibody binding characteristics used to observe the details of the antibody-antigen interaction surface. The results predicted by MCQP are compared with those predicted by the support vector machine (SVM). The MCQP algorithm classifies observations into distinct groups based on a number of criteria via a hyperplane. MCQP shows strong advantages for distances of 8 A and 10 A. Hover, SVM gives better results for a distance of 12 A.
['Yong Shi', 'Jia Wan', 'Xinyang Zhang', 'Gang Kou', 'Yi Peng', 'Yajun Guo']
I am writing a research paper on a idea Comparison study of two kernel-based learning algorithms for predicting the distance range between antibody interface residues and antigen surface
[{"from": "human", "value": "I am writing a research paper on a idea Comparison study of two kernel-based learning algorithms for predicting the distance range between antibody interface residues and antigen surface"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A number of kernel-based machine algorithms have recently been used to study protein-protein interaction in the field of bioinformatics.   develop a kernel-based machine algorithm called multiple criteria quadratic programming (MCQP) to predict the distance range beten antibody interface residues and the antigen surface in antigen-antibody complex. Antibodies bind their antigen using residues, which are part of the hypervariable loops.   explore the interaction beten antibody interface residues and antigen in the study of antibody functions. The distance beten the antibody's interface residue and the antigen surface is one of the antigen-antibody binding characteristics used to observe the details of the antibody-antigen interaction surface. The results predicted by MCQP are compared with those predicted by the support vector machine (SVM). The MCQP algorithm classifies observations into distinct groups based on a number of criteria via a hyperplane. MCQP shows strong advantages for distances of 8\u00a0A and 10\u00a0A. Hover, SVM gives better results for a distance of 12\u00a0A."}]