1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
|
:javascript
$(document).ready(function(){
$('[data-toggle="popover"]').popover();
$('.modal').on('hidden.bs.modal', function () {
$(this).removeData('bs.modal');
});
});
%div.well
%a.btn.btn-warning{:href => to('/predict')} New Prediction
/ displays all prediction result in first table
%div.table-responsive
%table.table.table-bordered{:id=>"overview", :style=>"background-color:white;"}
%thead
%tr
%h3 Prediction Results:
%tbody
%tr
%td{:id=>"compound", :style=>"vertical-align:top;"}
%a.btn.btn-link{:href => "#detailsTop", :id=>"linkCompound", data: { toggle: "modal", remote: to("/prediction/#{CGI.escape(@compound.uri)}/details")}}
%img.img-responsive{:src=>"#{@compound.uri}/image", :alt=>"no image", :title=>"#{@compound.smiles}", :width=>"150", :height=>"150"}
- count=0
- @predictions.each do |pa|
/ unpack to single array/prediction
/ if p.data_entries array[0].size == 3 -> database hit
/ change 'result' if database hit
/ change 'confidence' if database hit
- pa.each do |p|
/ prevent conversion of nil
/- $logger.debug "data entries in prediction array:\t#{p.data_entries}\n"
- database_hit = 0
- if p.data_entries[0].size == 3
- database_hit = 1
- c = p.data_entries[0][0] != nil ? p.data_entries[0][0] : ''
- case c
- when /(false|true|inactive|active)/i
- c = c
- else
/- c = Array.new
- c = (p.data_entries[0][0].class == Float) ? p.data_entries[0][0].round(3) : (p.data_entries[0][0] != nil ? p.data_entries[0][0] : "no prediction")
%td{:style=>"vertical-align:top;"}
%b{:class => "title"}
= @prediction_models[count].title.gsub("_", " ")
- @model_uri = @prediction_models[count].uri
%p
/ model type (classification|regression)
%b Type:
= @model_type[count]
%p
- unless database_hit > 0
%b Result:
%b
- if c.class == String
- result = (c != '' ? c : "No prediction result.")
= result
- else
- result = (c != '' ? c.round(3) : "No prediction result.")
= result
- confidence = (p.data_entries[0][1] != nil && p.data_entries[0][1] != 0.0) ? p.data_entries[0][1].round(2) : "--"
%a.btn.glyphicon.glyphicon-info-sign{:href=>"#", :title=>"Result", data: {toggle:"popover", placement:"left", html:"true", content:"LAZAR calculates searches the training dataset for similar compounds (neighbors) and calculates the prediction from their measured activities. LAZAR calculates predictions using <ul><li>a majority vote (weighted by compound similarity) for<br /><b>classification</b> (<a href='http://www.frontiersin.org/Journal/10.3389/fphar.2013.00038/abstract', target='_blank'>original publication</a>) </li><li>a local QSAR model based on neighbors for<br /><b>regression</b> (<a href='http://www.frontiersin.org/Journal/10.3389/fphar.2013.00038/abstract', target='_blank'</h>original publication</a>) </li></ul>Please keep in mind that predictions are based on the measured activities of neighbors."}}
- @cv = OpenTox::Validation.find @prediction_models[count].metadata[RDF::OT.crossValidation][0]+"/statistics" #unless @prediction_models[count].title.include?("Mutagenicity")
- unless @model_type[count] == "regression"
%br
%b
= "Probability: "
- unless result == "No prediction result." or confidence == "--"
- prob = @cv.probabilities( confidence, result )[:probs][result]*100
= "#{prob.round(1)} %"
%p
%b Confidence:
= confidence
%a.btn.glyphicon.glyphicon-info-sign{:href=>"#", :title=>"Confidence", data: {toggle:"popover", placement:"left", html:"true", content:"Indicates the applicability domain of a model. Predictions with a high confidence can be expected to be more reliable than predictions with low confidence. Confidence values may take any value between 0 and 1. For most models confidence > 0.025 is a sensible (hard) cutoff to distinguish between reliable and unreliable predictions."}}
%p
/TODO add tooltip for significant ftagments and descriptors
- if @model_type[count] =~ /classification/i && (p.data_entries[0][1] != nil && p.data_entries[0][1] != 0.0)
/ Significant fragments:
%a.btn.btn-default.btn-sm{:id=>"linkSigFragments", :href => "#detailsTop", data: { toggle: "modal", remote: to("/prediction/#{CGI.escape(@model_uri)}/#{@model_type[count]}/#{CGI.escape(@compound.uri)}/fingerprints")}} Significant fragments
- if @model_type[count] =~ /regression/i && (p.data_entries[0][1] != nil && p.data_entries[0][1] != 0.0)
/ Descriptors
%a.btn.btn-default.btn-sm{:id=>"linkDescriptors", :href => "#detailsTop", data: { toggle: "modal", remote: to("/prediction/#{CGI.escape(@model_uri)}/#{@model_type[count]}/#{CGI.escape(@compound.uri)}/fingerprints")}} Descriptors
%p
- if c != ''
%a.btn.btn-default.btn-sm{:href=> "#tabs", :id=>"link#{count}"}
Neighbors
:javascript
$("a#link#{count}").click(function () {
$(".results").show();
//document.getElementById('tabs').focus();
$('#neighborTabs a[href="#results_#{count+1}"]').tab('show');
//$("#tabs").tabs({ active: "#{count}" });
});
%p
- count+=1
- else # database hit
%b Database hit:
%br Compound found in training dataset
%p
%b Measured activity:
= p.data_entries[0][2]
%p
- count+=1
/ always show the neighbors table, message is given there
= haml :neighbors, :layout => false, :model_type => @model_type
%div.modal.fade{:id=>"detailsTop", :role=>"dialog"}
%div.modal-dialog.modal-lg
%div.modal-content
|
