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Table 2 Accuracy and Confidence values of global alignment

From: The ranging of amino acids substitution matrices of various types in accordance with the alignment accuracy criterion

  

30 PAM

  

60 PAM

 

Matrix

Gap open

Gap extention

Accuracy

Confi-dence

Gap open

Gap extention

Accuracy

Confi-dence

PAM30

18.0

2.0

0.9910

0.9907

25.0

2.0

0.9604

0.9600

PAM60

17.0

1.0

0.9916

0.9911

21.0

1.0

0.9610

0.9607

PAM120

13.0

1.0

0.9914

0.9908

13.0

1.0

0.9621

0.9599

PAM250

9.0

1.0

0.9901

0.9894

13.0

1.0

0.9610

0.9575

Blosum45

15.0

1.0

0.9901

0.9893

14.0

1.0

0.9559

0.9531

Blosum50

14.0

1.0

0.9902

0.9895

17.0

1.0

0.9563

0.9533

Blosum62

16.0

1.0

0.9906

0.9900

19.0

1.0

0.9575

0.9549

Gonnet250

11.0

1.0

0.9899

0.9890

11.0

1.0

0.9551

0.9514

Gonnet_p

7.0

1.0

0.9879

0.9864

10.0

1.0

0.9460

0.9398

Optima

10.0

1.0

0.9899

0.9891

14.0

1.0

0.9557

0.9520

VTML250

10.0

1.0

0.9894

0.9885

12.0

1.0

0.9555

0.9515

MIQS

11.0

1.0

0.9897

0.9888

15.0

1.0

0.9564

0.9527

Pfasum050

14.0

1.0

0.9899

0.9890

16.0

1.0

0.9574

0.9542

Pfasum100

11.0

1.0

0.9901

0.9892

14.0

1.0

0.9573

0.9542

Crooks

13.0

1.0

0.9900

0.9893

17.0

1.0

0.9555

0.9524

CCF53

11.0

1.0

0.9900

0.9892

13.0

1.0

0.9563

0.9534

Moll60

12.0

1.0

0.9900

0.9893

16.0

1.0

0.9564

0.9531

Johnson

18.0

1.0

0.9904

0.9899

23.0

1.0

0.9564

0.9547

Prlic

18.0

1.0

0.9896

0.9889

24.0

1.0

0.9532

0.9503

Blake

22.0

1.0

0.9880

0.9879

30.0

1.0

0.9468

0.9458

Benner

9.0

1.0

0.9878

0.9867

12.0

1.0

0.9452

0.9407

Miyazawa

21.0

1.0

0.9864

0.9855

22.0

1.0

0.9432

0.9408

Data set

 

120 PAM

  

Bali Base

 

Matrix

Gap open

Gap extention

Accuracy

Confi-dence

Gap open

Gap extention

Accuracy

Confi-dence

PAM30

30.0

4.0

0.8065

0.7991

24.0

4.0

0.6257

0.6215

PAM60

26.0

3.0

0.8174

0.8080

20.0

3.0

0.6301

0.6236

PAM120

19.0

1.0

0.8189

0.8152

16.0

2.0

0.6287

0.6205

PAM250

17.0

1.0

0.8325

0.8241

11.0

2.0

0.6310

0.6240

Blosum45

22.0

1.0

0.7949

0.7855

13.0

1.0

0.6495

0.6473

Blosum50

21.0

1.0

0.7925

0.7866

16.0

2.0

0.6523

0.6433

Blosum62

24.0

2.0

0.7972

0.7877

19.0

2.0

0.6533

0.6455

Gonnet250

16.0

1.0

0.8129

0.8037

11.0

1.0

0.6592

0.6541

Gonnet_p

13.0

1.0

0.7870

0.7729

7.0

1.0

0.6470

0.6353

Optima

17.0

1.0

0.7907

0.7830

13.0

1.0

0.6515

0.6463

VTML250

15.0

1.0

0.8110

0.8017

11.0

1.0

0.6544

0.6486

MIQS

18.0

1.0

0.8046

0.7964

13.0

1.0

0.6518

0.6479

Pfasum050

21.0

1.0

0.8015

0.7939

15.0

2.0

0.6599

0.6507

Pfasum100

18.0

1.0

0.7973

0.7891

12.0

1.0

0.6527

0.6499

Crooks

18.0

2.0

0.7921

0.7823

14.0

2.0

0.6553

0.6470

CCF53

18.0

1.0

0.7923

0.7841

14.0

1.0

0.6488

0.6429

Moll60

19.0

1.0

0.7819

0.7762

12.0

2.0

0.6484

0.6403

Johnson

29.0

2.0

0.8011

0.7935

19.0

3.0

0.6524

0.6456

Prlic

13.0

1.0

0.7870

0.7729

18.0

2.0

0.6476

0.6427

Blake

30.0

4.0

0.7608

0.7547

24.0

3.0

0.6444

0.6419

Benner

16.0

1.0

0.7385

0.7282

10.0

1.0

0.5917

0.5848

Miyazawa

30.0

2.0

0.7539

0.7449

20.0

3.0

0.6024

0.5936

  1. The optimal values of the alignment quality (Accuracy, Confidence) with the corresponding values of the penalty function parameters (GOP, GEP) are given. Data were obtained for all matrices examined, on test sets of the generated sequences: 30 PAM, 60 PAM, 120 PAM, and on Balibase [18] sequences. A full set of alignment quality values for the entire set of tested GOP and GEP parameters is given in Additional files 1, 2: Table S1, Table S2
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BMC Bioinformatics

ISSN: 1471-2105

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