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 27									    
 98  32									    
120   0 905								    
 36  23   0   0								    
 89 246 103 134   0							    
198   1 148 1153  0 716							    
240   9 139 125  11  28  81						    
 23 240 535  86  28 606  43  10						    
 65  64  77  24  44  18  61   0   7					    
 41  15  34   0   0  73  11   7  44 257					    
 26 464 318  71   0 153  83  27  26  46  18				    
 72  90   1   0   0 114  30  17   0 336 527 243				    
 18  14  14   0   0   0   0  15  48 196 157   0  92			    
250 103  42  13  19 153  51  34  94  12  32  33  17  11			    
409 154 495  95 161  56  79 234  35  24  17  96  62  46 245		    
371  26 229  66  16  53  34  30  22 192  33 136 104  13  78 550		    
  0 201  23   0   0   0   0   0  27   0  46   0   0  76   0  75   0	    
 24   8  95   0  96   0  22   0 127  37  28  13   0 698   0  34  42  61	    
208  24  15  18  49  35  37  54  44 889 175  10 258  12  48  30 157   0  28 

0.087127 0.040904 0.040432 0.046872 0.033474 0.038255 0.049530
0.088612 0.033618 0.036886 0.085357 0.080482 0.014753 0.039772
0.050680 0.069577 0.058542 0.010494 0.029916 0.064718

Ala Arg Asn Asp Cys Gln Glu Gly His Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val

S_ij = S_ji and PI_i for the Dayhoff model, with the rate Q_ij=S_ij*PI_j
The rest of the file is not used.
Prepared by Z. Yang, March 1995.


See the following reference for notation used here:

Yang, Z., R. Nielsen and M. Hasegawa. 1998. Models of amino acid substitution and
applications to mitochondrial protein evolution. Mol. Biol. Evol. 15:1600-1611.


-----------------------------------------------------------------------

     
 30									   
109  17									   
154   0 532								   
 33  10   0   0 							   
 93 120  50  76   0							   
266   0  94 831   0 422							   
579  10 156 162  10  30 112						   
 21 103 226  43  10 243  23  10 					   
 66  30  36  13  17   8  35   0   3					   
 95  17  37   0   0  75  15  17  40 253					   
 57 477 322  85   0 147 104  60  23  43  39				   
 29  17   0   0   0  20   7   7   0  57 207  90				   
 20   7   7   0   0   0   0  17  20  90 167   0  17 			   
345  67  27  10  10  93  40  49  50   7  43  43   4   7			   
772 137 432  98 117  47  86 450  26  20  32 168  20  40 269		   
590  20 169  57  10  37  31  50  14 129  52 200  28  10  73 696		   
  0  27   3   0   0   0   0   0   3   0  13   0   0  10   0  17  0	   
 20   3  36   0  30   0  10   0  40  13  23  10   0 260   0  22  23  6	   
365  20  13  17  33  27  37  97  30 661 303  17  77  10  50  43 186  0  17  
 A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y  V
Ala Arg Asn Asp Cys Gln Glu Gly His Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val

Accepted point mutations (x10) Figure 80 (Dayhoff 1978)
-------------------------------------------------------

A 100 /* Ala */		    A 0.087 /* Ala */
R  65 /* Arg */		    R 0.041 /* Arg */
N 134 /* Asn */		    N 0.040 /* Asn */
D 106 /* Asp */		    D 0.047 /* Asp */
C  20 /* Cys */		    C 0.033 /* Cys */
Q  93 /* Gln */		    Q 0.038 /* Gln */
E 102 /* Glu */		    E 0.050 /* Glu */
G  49 /* Gly */             G 0.089 /* Gly */
H  66 /* His */		    H 0.034 /* His */
I  96 /* Ile */		    I 0.037 /* Ile */
L  40 /* Leu */		    L 0.085 /* Leu */
K  56 /* Lys */		    K 0.081 /* Lys */
M  94 /* Met */		    M 0.015 /* Met */
F  41 /* Phe */		    F 0.040 /* Phe */
P  56 /* Pro */		    P 0.051 /* Pro */
S 120 /* Ser */		    S 0.070 /* Ser */
T  97 /* Thr */		    T 0.058 /* Thr */
W  18 /* Trp */		    W 0.010 /* Trp */
Y  41 /* Tyr */		    Y 0.030 /* Tyr */
V  74 /* Val */		    V 0.065 /* Val */

scale factor = SUM_OF_PRODUCT = 75.246


Relative Mutability         The equilibrium freqs.
(Table 21)		    Table 22    
(Dayhoff 1978)		    Dayhoff (1978)        
----------------------------------------------------------------



Some notes from 1995, for those technical people:

I managed to find some notes I wrote in 1995.  The symbols are not
that comprehensible now, but you can get the basic idea, I think.  

(1) Construction of P(0.01), for 1 PAM
    p_ij(0.01) = m_i * A_{ij}/\sum_k{A_{ik}} / 7524.6

(2) Eigensolution of P(0.01) = exp{Q*0.01}
    P(0.01) = U diag{\lambda...} U^{-1}

    Then 
    Q = U diag{100*log{\lambda}...} U^{-1}


I did not use the PAM transition probabilities as rates assuming 0.01
is close to 0, but instead take them as P(0.01) to recover the rate
matrix, and as we expect, the rates are more different from each other
than the p_ij(0.01) are.

I seem to recall that I thought some details in the Dayhoff paper and
the Kishino et al. (1990) paper were not entirely right.  I think I
thought that Q should be a symmetrical matrix, right-multiplied by a
diagonal matrix, while either Dayhoff or Kishino or both used
left-multiplication.

As far as I know, codeml and protml give very similar (but not
identical, I think) results under the Dayhoff model.

My jones.dat file is not based on the Jones et al. (1992) paper, but
is based on an updated data set sent to me by David Jones.  So codeml
and protml gave different results under JTT, but ranking of trees was
not affected for the data set I tested.

Ziheng Yang