Predicts the Antifreeze protein. iAFP-Ense is a protector that can become a useful high-throughput software for both basic research and drug development. This random forests algorithm was adopted to conduct prediction using each descriptor features and the final result was gotten by integrating all the random forests results via voting. To obtain the predicted result with the anticipated success rate, the entire sequence of the query protein rather than its fragment should be used as an input.
Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen, China; School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China; School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China
iAFP-Ense funding source(s)
Partially supported by the National Nature Science Foundation of China (No. 31260273, 61261027), the Jiangxi Provincial Foreign Scientific and Technological Cooperation Project (No. 20120BDH80023), Natural Science Foundation of Jiangxi Province, China (No. 20114BAB211013, 20122BAB211033, 20122BAB201044, 20122BAB201020), the Department of Education of JiangXi Province (GJJ12490, GJJ4642, GJJ14651, GJJ14640), the LuoDi plan of the Department of Education of JiangXi Province (KJLD12083), and the JiangXi Provincial Foundation for Leaders of Disciplines in Science (20113BCB22008).