PositionSpecific Weight Matrix Amino acids Position 6 PositionSpecific

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Position-Specific Weight Matrix Amino acids Position (% ) 6

Position-Specific Weight Matrix Amino acids Position (% ) 6

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 7

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 7

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 8

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 8

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 9

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 9

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 10

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 10

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 11

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 11

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 3. 800

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 3. 800 12

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 3. 800

Position-Specific Weight Matrix Amino acids Position (% ) Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … 3. 800 2. 232 1. 054 Yes cutoff 13 No

LRR预测 Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … Yes 3. 800 2. 232 1. 054 Sensitivity /

LRR预测 Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … Yes 3. 800 2. 232 1. 054 Sensitivity / Specificity cutoff No Cutoff score Cutoff 1. 5 1. 6 1. 7 1. 8 1. 9 2. 0 2. 1 2. 2 2. 3 2. 4 2. 5 Sensitivity 0. 942 0. 933 0. 924 0. 916 0. 907 0. 886 0. 868 0. 858 0. 842 0. 822 0. 805 Specificity 0. 852 0. 882 0. 902 0. 916 0. 935 0. 954 0. 970 0. 981 0. 988 0. 992 0. 994 Spe. (filter) 0. 914 0. 930 0. 953 0. 959 0. 972 0. 981 0. 987 0. 991 0. 994 0. 996 0. 997 14

LRR预测 Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … Yes 3. 800 2. 232 1. 054 Yes No

LRR预测 Example: … LPTNLTVLMLLHNQLRRLPAANFTRYSQLTSLDVGFNT … Yes 3. 800 2. 232 1. 054 Yes No Sensitivity / Specificity cutoff No Cutoff score Cutoff 1. 5 1. 6 1. 7 1. 8 1. 9 2. 0 2. 1 2. 2 2. 3 2. 4 2. 5 Sensitivity 0. 942 0. 933 0. 924 0. 916 0. 907 0. 886 0. 868 0. 858 0. 842 0. 822 0. 805 Specificity 0. 852 0. 882 0. 902 0. 916 0. 935 0. 954 0. 970 0. 981 0. 988 0. 992 0. 994 Spe. (filter) 0. 914 0. 930 0. 953 0. 959 0. 972 0. 981 0. 987 0. 991 0. 994 0. 996 0. 997 15

LRR预测 16

LRR预测 16

LRR预测 17

LRR预测 17

蛋白质三维结构测定 第一个蛋白质的3 D结构是由Kendrew和 Perutz于1958使用X-射线晶体衍射法测得的。 62152 X-射线晶体衍射法 7929 Max Ferdinand Perutz (1914 -2002) nobel prize

蛋白质三维结构测定 第一个蛋白质的3 D结构是由Kendrew和 Perutz于1958使用X-射线晶体衍射法测得的。 62152 X-射线晶体衍射法 7929 Max Ferdinand Perutz (1914 -2002) nobel prize 1962 John Cowdery Kendrew (19171997) nobel prize 1962 核磁共振法 19

蛋白质二级结构预测 已知一个蛋白质的氨基酸序列，预测其二级结构。 常用软件：PSIPRED, APSSP 2, NNPREDICT, PREDICTPROTEIN http: //bioinf. cs. ucl. ac. uk/psipred/ 24

蛋白质二级结构预测 已知一个蛋白质的氨基酸序列，预测其二级结构。 常用软件：PSIPRED, APSSP 2, NNPREDICT, PREDICTPROTEIN http: //bioinf. cs. ucl. ac. uk/psipred/ 24

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