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Output format


DESCRIPTION

Example of output is found below. The output is divided into the folowinng sections:
  • Description of training data
  • Prediction method
  • Parameters for training of Gibbs method
  • Prediction data
  • Evaluation of predictions (if assignments are supplied by user)
  • Predictions This section contain a line "Peptide Start res Motif Prediction (Assign) Sequence"
    Peptide: Peptide number
    Start res: 1st residue in motif
    Motif: Motif found in sequence
    Prediction: Prediction score for motif
    Assign: Assignment of sequence (if supplied by user)
    Sequence: Sequence containing motif



EXAMPLE OUTPUT

Description of training data

Length of motif: 9
Number of training data: 456
Number of positive training examples: 456

Parameters for training of Gibbs method

Clustering using the Henikoff & Henikoff 1/nr method
Weight on prior: 50.000000
Start temperature: 0.150000
End temperature: 0.000100
Number of temperature steps: 10.000000
Using default seed
Number of iterations per train example: 20
Using amino acid background distribution from SWISSPROT
Equal weights on all positions

Figure: Visualization of the binding motif using the logo program.
A short explanation of can be found here.


Alignment generated by Gibbs sampler
Matrix generated by Gibbs sampler

Prediction data

Number of evaluation data: 57
Predicting using a matrix method

Evaluation of predictions

Pearson coefficient for N= 57 data: -0.30553
Aroc value: 0.31622
Threshold for counting example as positive: 50.000000

Predictions

 
Peptide   Start res Motif       Prediction Assign Sequence
1         8         FWSFGSEDG    6.549     5.400  MASPGSGFWSFGSEDGSGDS
2         1         FGSEDGSGD    3.304    62.000  FGSEDGSGDSENPGRARAWC
3         6         ARAWCQVAQ    3.363   100.000  ENPGRARAWCQVAQKFTGGI
4         1         QVAQKFTGG    1.638   100.000  QVAQKFTGGIGNKLCALLYG
5         8         LYGDAEKPA    4.603   100.000  GNKLCALLYGDAEKPAESGG
6         7         ESGGSQPPR    1.463   100.000  DAEKPAESGGSQPPRAAARK
7         8         ARKAACACD    3.170   100.000  SQPPRAAARKAACACDQKPC
8         12        CSKVDVNYA   -1.160     2.400  AACACDQKPCSCSKVDVNYA
9         12        LHATDLLPA    6.138     0.500  SCSKVDVNYAFLHATDLLPA
10        2         LHATDLLPA    6.138     0.200  FLHATDLLPACDGERPTLAF
11        12        QDVMNILLQ    1.590   100.000  CDGERPTLAFLQDVMNILLQ
12        11        YVVKSFDRS    4.430     0.700  LQDVMNILLQYVVKSFDRST
13        1         YVVKSFDRS    4.430    19.000  YVVKSFDRSTKVIDFHYPNE
14        5         FHYPNELLQ    6.535     5.000  KVIDFHYPNELLQEYNWELA
15        7         WELADQPQN    7.249     5.000  LLQEYNWELADQPQNLEEIL
16        11        MHCQTTLKY    5.006   100.000  DQPQNLEEILMHCQTTLKYA
17        9         YAIKTGHPR    9.089   100.000  MHCQTTLKYAIKTGHPRYFN
18        8         YFNQLSTGL    5.320     0.500  IKTGHPRYFNQLSTGLDMVG
19        12        AADWLTSTA    1.734     1.400  QLSTGLDMVGLAADWLTSTA
20        5         WLTSTANTN    4.697    41.000  LAADWLTSTANTNMFTYEIA
21        5         FTYEIAPVF    3.031    85.000  NTNMFTYEIAPVFVLLEYVT
22        4         MREIIGWPG    7.542    48.000  LKKMREIIGWPGGSGDGIFS
23        9         FSPGGAISN    0.479    80.000  PGGSGDGIFSPGGAISNMYA
24        9         YAMMIARFK    3.854   100.000  PGGAISNMYAMMIARFKMFP
25        11        EVKEKGMAA    3.955    25.000  MMIARFKMFPEVKEKGMAAL
26        4         EKGMAALPR    4.336    40.000  EVKEKGMAALPRLIAFTSEH
27        6         FTSEHSHFS    8.330     0.200  PRLIAFTSEHSHFSLKKGAA
28        3         FSLKKGAAA    5.693   100.000  SHFSLKKGAAALGIGTDSVI
29        10        ILIKCDERG    1.002    24.000  ALGIGTDSVILIKCDERGKM
30        10        MIPSDLERR   -0.681   100.000  LIKCDERGKMIPSDLERRIL
31        8         RILEAKQKG    2.013    38.000  IPSDLERRILEAKQKGFVPF
32        10        FLVSATAGT    5.278     4.000  EAKQKGFVPFLVSATAGTTV
33        11        YGAFDPLLA    6.422     7.000  LVSATAGTTVYGAFDPLLAV
34        1         YGAFDPLLA    6.422   100.000  YGAFDPLLAVADICKKYKIW
35        10        WMHVDAAWG    9.248     2.700  ADICKKYKIWMHVDAAWGGG
36        1         MHVDAAWGG    1.533    43.000  MHVDAAWGGGLLMSRKHKWK
37        9         WKLSGVERA    7.137     0.800  LLMSRKHKWKLSGVERANSV
38        9         SVTWNPHKM    4.403    13.000  LSGVERANSVTWNPHKMMGV
39        5         HKMMGVPLQ    3.161    34.000  TWNPHKMMGVPLQCSALLVR
40        8         LVREEGLMQ    5.674    17.000  PLQCSALLVREEGLMQNCNQ
41        3         GLMQNCNQM    2.757    41.000  EEGLMQNCNQMHASYLFQQD
42        5         YLFQQDKHY    5.432    22.000  MHASYLFQQDKHYDLSYDTG
43        5         LSYDTGDKA    4.032    31.000  KHYDLSYDTGDKALQCGRHV
44        12        VFKLWLMWR    0.431   100.000  DKALQCGRHVDVFKLWLMWR
45        5         LWLMWRAKG    8.337    33.000  DVFKLWLMWRAKGTTGFEAH
46        7         FEAHVDKCL    2.003   100.000  AKGTTGFEAHVDKCLELAEY
47        12        YNIIKNREG    3.638    34.000  VDKCLELAEYLYNIIKNREG
48        2         YNIIKNREG    3.638     4.000  LYNIIKNREGYEMVFDGKPQ
49        2         EMVFDGKPQ    2.819    67.000  YEMVFDGKPQHTNVCFWYIP
50        7         WYIPPSLRT    5.691     0.600  HTNVCFWYIPPSLRTLEDNE
51        3         LRTLEDNEE    0.154     5.000  PSLRTLEDNEERMSRLSKVA
52        4         SRLSKVAPV    3.410   100.000  ERMSRLSKVAPVIKARMMEY
53        10        YGTTMVSYQ    2.533    10.000  PVIKARMMEYGTTMVSYQPL
54        3         TMVSYQPLG    1.012    10.000  GTTMVSYQPLGDKVNFFRMV
55        7         FRMVISNPA   11.762     0.700  GDKVNFFRMVISNPAATHQD
56        2         SNPAATHQD    3.258    65.000  ISNPAATHQDIDFLIEEIER
57        8         FLIEEIERL    3.306    20.000  ATHQDIDFLIEEIERLGQDL


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This file was last modified Tuesday 9th 2004f November 2004 13:19:44 GMT