öλÔÓéÀֵǼÈë¿ÚÏÂÔØ

µ¼Ê¦ÐÕÃû£º·®ÓÀÏÔ
ÐÔ±ð£º
ÈËÆøÖ¸Êý£º98

ËùÊôԺУ£º¹ðÁÖµç×ӿƼ¼´óѧ
ËùÊôԺϵ£º¼ÆËã»úÓëÐÅÏ¢°²È«Ñ§Ôº
Ö°³Æ£º¸±Ñо¿Ô±
µ¼Ê¦ÀàÐÍ£ºË¶µ¼
ÕÐÉúöλÔÓéÀֵǼÈë¿ÚÏÂÔØ£º¼ÆËã»ú¿ÆѧÓë¼¼Êõ£¨Ñ§ÊõÐÍ£©¡¢¼ÆËã»ú¼¼Êõ£¨öλÔÓéÀֵǼÈë¿ÚÏÂÔØѧ룩
Ñо¿ÁìÓò£º È˹¤ÖÇÄÜ¡¢Êý¾Ý·ÖÎö¡¢»úÆ÷ѧϰ¡¢Ä£Ê½Ê¶±ð¡¢ÉúÎïÐÅϢѧ
Ñо¿ÁìÓò£º È˹¤ÖÇÄÜ¡¢Êý¾Ý·ÖÎö¡¢»úÆ÷ѧϰ¡¢Ä£Ê½Ê¶±ð¡¢ÉúÎïÐÅϢѧ [ÊÕÆð]




ͨѶ·½Ê½ :
µç×ÓÓʼþ£ºyx_f@163.com


¸öÈ˼òÊö :
·®ÓÀÏÔ£¬ÄУ¬¹¤Ñ§²©Ê¿/¸±Ñо¿Ô±£¬¹ú¼Ò×ÔÈ»¿Æѧ»ù½ðÏîÄ¿ÆÀÒéר¼Ò£¬¹ãÎ÷¿Æ¼¼ÏîÄ¿ÆÀÒéר¼Ò£¬ÖйúÈ˹¤ÖÇÄÜѧ»áÉúÎïÐÅϢѧÓëÈ˹¤ÉúÃüרί»áίԱ£¬Öйú¼ÆËã»úѧ»áÉúÎïÐÅϢѧרί»áίԱ£¬Öйú×Ô¶¯»¯Ñ§»áģʽʶ±ðÓë»úÆ÷ÖÇÄÜרί»áίԱ£¬¹ú¼Êģʽʶ±ðЭ»á£¨IAPR£©»áÔ±¡£±ÏÒµÓÚÉϺ£½»Í¨´óѧͼÏñ´¦ÀíÓëģʽʶ±ðÑо¿Ëù¡£Ö÷³Ö¹ú¼Ò×ÔÈ»¿Æѧ»ù½ðÏîÄ¿2Ï¹ãÎ÷×ÔÈ»¿Æѧ»ù½ðÏîÄ¿1ÏÆäËûÖصãʵÑéÊÒÏîÄ¿Èô¸ÉÏî¡£²ÎÓëÍê³É¶àÏî¹ú¼Ò»ù½ðÏîÄ¿¡£ÔÚ¹ú¼ÊÆÚ¿¯·¢±íÂÛÎĶàƪ£¬¾ù±»SCI¼ìË÷¡£

¿ÆÑй¤×÷ :
[1] Xiaoyong Pan^, Yong-Xian Fan^, Junchi Yan, and Hong-Bin Shen*, IPMiner: Hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction, BMC Genomics, 2016, 17:582. (SCI, IF: 3.867).[2] Yong-Xian Fan and Hong-Bin Shen*, Predicting pupylation sites in prokaryotic proteins using pseudo-amino acid composition and extreme learning machine, Neurocomputing, 2014, 128: 267-272. (SCI, IF: 2.005).[3] Xiaoyong Pan*, Lin Zhu, Yong-Xian Fan, Junchi Yan, Predicting Protein-RNA Interaction Amino Acids using Random Forest Based on Submodularity Subset Selection, Computational Biology and Chemistry, 2014, 53: 324¨C330. (SCI, IF: 1.595).[4] Yong-Xian Fan, Yang Zhang, and Hong-Bin Shen*, LabCaS: Labeling calpain substrate cleavage sites from amino acid sequence using conditional random fields, PROTEINS: Structure, Function, and Bioinformatics, 2013, 81: 622-634. (SCI, IF: 3.337).[5] Yong-Xian Fan, Jiangning Song, Chen Xu, and Hong-Bin Shen*, Predicting protein N-terminal signal peptides using position-specific amino acid propensities and conditional random fields, Current Bioinformatics, 2013, 8: 183-192. (SCI, IF: 2.017).[6] Ya-Nan Zhang^, Dong-Jun Yu^, Shu-Sen Li, Yong-Xian Fan, Yan Huang, and Hong-Bin Shen*, Predicting protein-ATP binding sites from primary sequence through fusing bi-profile sampling of multi-view features, BMC Bioinformatics, 2012, 13: 118. (SCI, IF: 3.024).[7] Zhi Zheng, Youying Chen, Liping Chen, Gongde Guo, Yongxian Fan, and Xiangzeng Kong*, Signal-BNF: A Bayesian Network Fusing Approach to Predict Signal Peptides, Journal of Biomedicine and Biotechnology, 2012, Article ID 492174, 8 pages. (SCI, IF: 2.880).[8] Yong-Xian Fan, Jiangning Song, Xiangzeng Kong, and Hong-Bin Shen*, PredCSF: An integrated feature-based approach for predicting conotoxin superfamily, Protein and Peptide Letters, 2011, 18: 261-267. (SCI, IF: 1.942).[9] Jiang-Bo Yin^, Yong-Xian Fan^, and Hong-Bin Shen*, Conotoxin superfamily prediction using diffusion maps dimensionality reduction and subspace classifier, Current Protein and Peptide Science, 2011, 12: 580-588. (SCI, IF: 2.886).[10] Ñî»Ô»ª*, ÕÅÏþ·ï, ·®ÓÀÏÔ*, лÆ×Ä£, ñÒСÁ¢, »ùÓÚÒ»ÔªÏßÐԻعéµÄ½üºìÍâ¹âÆ×Ä£ÐÍ´«µÝÑо¿£¬·ÖÎö»¯Ñ§, 2014, 42(9): 1229-1234. (SCI, IF: 0.700).[11] Òü½­²¨, À×½£²¨, ·®ÓÀÏÔ, Éòºì±ó*£¬»ùÓÚÀ©É¢Ó³ÉäºÍdHKNNËã·¨µÄÓóÂݶ¾Ëس¬¼Ò×åÔ¤²â, Chinese Conference on Pattern Recognition 2010 (CCPR2010), Chongqing, China, Oct 21-23, 2010. (EI).[12] ²Ì¹úÓÀ, ÂÀÈð, ·®ÓÀÏÔ, »ùÓÚ±êÇ©ºÍÒò×Ó·ÖÎöµÄЭͬÍƼö·½·¨, ±±¾©Óʵç´óѧѧ±¨, 2015, 33(9): 34-38.(EI). Åú×¼±àºÅ£º**ÏîÄ¿Àà±ð£º¹ú¼Ò×ÔÈ»¿Æѧ»ù½ðÆðÖ¹ÄêÔ£º2015Äê01Ô ¨C 2018Äê12ÔÂÏîÄ¿½ÇÉ«£ºÖ÷³Ö?Åú×¼±àºÅ£º**ÏîÄ¿Àà±ð£º¹ú¼Ò×ÔÈ»¿Æѧ»ù½ðÆðÖ¹ÄêÔ£º2018Äê01Ô ¨C 2021Äê12ÔÂÏîÄ¿½ÇÉ«£ºÖ÷³Ö?ºÏͬ±àºÅ£º2017GXNSFAA198278ÏîÄ¿Àà±ð£º¹ãÎ÷×ÔÈ»¿Æѧ»ù½ðÆðÖ¹ÄêÔ£º2017Äê09Ô ¨C 2020Äê09ÔÂÏîÄ¿½ÇÉ«£ºÖ÷³Ö