From 7870cd69eaa1f0c62d980fb40c45abaacd8c71d2 Mon Sep 17 00:00:00 2001
From: gebele <gebele@in-silico.ch>
Date: Thu, 13 Jul 2017 07:41:33 +0000
Subject: updated qmrf report; consistent use of uri list for features

---
 lib/feature.rb |   7 +-
 lib/report.rb  | 335 ++++++++++++++++++++++++++++-----------------------------
 2 files changed, 170 insertions(+), 172 deletions(-)

diff --git a/lib/feature.rb b/lib/feature.rb
index 140cc25..06a5b37 100644
--- a/lib/feature.rb
+++ b/lib/feature.rb
@@ -7,10 +7,9 @@ get "/feature/?" do
     return uri_list.join("\n") + "\n"
   when "application/json"
     features = JSON.parse features.to_json
-    features.each_index do |idx|
-      features[idx][:URI] = uri("/feature/#{features[idx]["_id"]["$oid"]}")
-    end
-    return features.to_json
+    list = []
+    features.each{|f| list << uri("/feature/#{f["_id"]["$oid"]}")}
+    return list.to_json
   else
     bad_request_error "Mime type #{@accept} is not supported."
   end
diff --git a/lib/report.rb b/lib/report.rb
index ae2526c..f576106 100644
--- a/lib/report.rb
+++ b/lib/report.rb
@@ -8,202 +8,201 @@ get "/report/?" do
     uri_list = models.collect{|model| uri("/report/#{model.model_id}")}
     return uri_list.join("\n") + "\n"
   when "application/json"
-    reports = [{}]
-    #models = JSON.parse models.to_json
-    models.each_index do |idx|
-      reports[idx] = {}
-      reports[idx][:URI] = uri("/report/#{models[idx]["model_id"]}")
-      reports[idx][:repeated_crossvalidation_uri] = uri("/validation/repeatedcrossvalidation/#{models[idx]["repeated_crossvalidation_id"]}") if models[idx]["repeated_crossvalidation_id"]
-      reports[idx][:leave_one_out_validation_uri] = uri("/validation/leaveoneoutvalidation/#{models[idx]["leave_one_out_validation_id"]}") if models[idx]["leave_one_out_validation_id"]
-      reports[idx][:training_dataset_URI] = uri("/dataset/#{models[idx].training_dataset.id}") if models[idx].training_dataset.id 
-    end
-    return reports.to_json
+    models = JSON.parse models.to_json
+    list = []
+    models.each{|m| list << uri("/report/#{m["model_id"]["$oid"]}")}
+    return list.to_json
   else
     bad_request_error "Mime type #{@accept} is not supported."
   end
 end
 
 get "/report/:id/?" do
-  model = Model::Lazar.find params[:id]
-  not_found_error "Model with id: #{params[:id]} not found." unless model
-  prediction_model = Model::Validation.find_by :model_id => params[:id]
-  validation_template = File.join(File.dirname(__FILE__),"../views/model_details.haml")
-
-  if File.directory?("#{File.dirname(__FILE__)}/../../lazar")
-    lazar_commit = `cd #{File.dirname(__FILE__)}/../../lazar; git rev-parse HEAD`.strip
-    lazar_commit = "https://github.com/opentox/lazar/tree/#{lazar_commit}"
-  else
-    lazar_commit = "https://github.com/opentox/lazar/releases/tag/v#{Gem.loaded_specs["lazar"].version}"
-  end
+  case @accept
+  when "application/xml"
+    model = Model::Lazar.find params[:id]
+    not_found_error "Model with id: #{params[:id]} not found." unless model
+    prediction_model = Model::Validation.find_by :model_id => params[:id]
+    validation_template = File.join(File.dirname(__FILE__),"../views/model_details.haml")
+
+    if File.directory?("#{File.dirname(__FILE__)}/../../lazar")
+      lazar_commit = `cd #{File.dirname(__FILE__)}/../../lazar; git rev-parse HEAD`.strip
+      lazar_commit = "https://github.com/opentox/lazar/tree/#{lazar_commit}"
+    else
+      lazar_commit = "https://github.com/opentox/lazar/releases/tag/v#{Gem.loaded_specs["lazar"].version}"
+    end
 
-  report = OpenTox::QMRFReport.new
+    report = OpenTox::QMRFReport.new
 
-  # QSAR Identifier Title 1.1
-  report.value "QSAR_title", "Lazar model for #{prediction_model.species} #{prediction_model.endpoint}"
+    # QSAR Identifier Title 1.1
+    report.value "QSAR_title", "Lazar model for #{prediction_model.species} #{prediction_model.endpoint}"
 
-  # Software coding the model 1.3
-  report.change_catalog :software_catalog, :firstsoftware, {:name => "lazar", :description => "lazar Lazy Structure- Activity Relationships", :number => "1", :url => "https://lazar.in-silico.ch", :contact => "info@in-silico.ch"}
-  report.ref_catalog :QSAR_software, :software_catalog, :firstsoftware
+    # Software coding the model 1.3
+    report.change_catalog :software_catalog, :firstsoftware, {:name => "lazar", :description => "lazar Lazy Structure- Activity Relationships", :number => "1", :url => "https://lazar.in-silico.ch", :contact => "info@in-silico.ch"}
+    report.ref_catalog :QSAR_software, :software_catalog, :firstsoftware
 
-  # Date of QMRF 2.1
-  report.value "qmrf_date", "#{Time.now.strftime('%d %B %Y')}"
+    # Date of QMRF 2.1
+    report.value "qmrf_date", "#{Time.now.strftime('%d %B %Y')}"
 
-  # QMRF author(s) and contact details 2.1
-  report.change_catalog :authors_catalog, :firstauthor, {:name => "Christoph Helma", :affiliation => "in silico toxicology gmbh", :contact => "Rastatterstr. 41, CH-4057 Basel", :email => "info@in-silico.ch", :number => "1", :url => "www.in-silico.ch"}
-  report.ref_catalog :qmrf_authors, :authors_catalog, :firstauthor
+    # QMRF author(s) and contact details 2.1
+    report.change_catalog :authors_catalog, :firstauthor, {:name => "Christoph Helma", :affiliation => "in silico toxicology gmbh", :contact => "Rastatterstr. 41, CH-4057 Basel", :email => "info@in-silico.ch", :number => "1", :url => "www.in-silico.ch"}
+    report.ref_catalog :qmrf_authors, :authors_catalog, :firstauthor
 
-  # Model developer(s) and contact details 2.5
-  report.change_catalog :authors_catalog, :modelauthor, {:name => "Christoph Helma", :affiliation => "in silico toxicology gmbh", :contact => "Rastatterstr. 41, CH-4057 Basel", :email => "info@in-silico.ch", :number => "1", :url => "www.in-silico.ch"}
-  report.ref_catalog :model_authors, :authors_catalog, :modelauthor
+    # Model developer(s) and contact details 2.5
+    report.change_catalog :authors_catalog, :modelauthor, {:name => "Christoph Helma", :affiliation => "in silico toxicology gmbh", :contact => "Rastatterstr. 41, CH-4057 Basel", :email => "info@in-silico.ch", :number => "1", :url => "www.in-silico.ch"}
+    report.ref_catalog :model_authors, :authors_catalog, :modelauthor
 
-  # Date of model development and/or publication 2.6
-  report.value "model_date", "#{Time.parse(model.created_at.to_s).strftime('%Y')}"
+    # Date of model development and/or publication 2.6
+    report.value "model_date", "#{Time.parse(model.created_at.to_s).strftime('%Y')}"
 
-  # Reference(s) to main scientific papers and/or software package 2.7
-  report.change_catalog :publications_catalog, :publications_catalog_1, {:title => "Maunz, Guetlein, Rautenberg, Vorgrimmler, Gebele and Helma (2013), lazar: a modular predictive toxicology framework  ", :url => "http://dx.doi.org/10.3389/fphar.2013.00038"}
-  report.ref_catalog :references, :publications_catalog, :publications_catalog_1
+    # Reference(s) to main scientific papers and/or software package 2.7
+    report.change_catalog :publications_catalog, :publications_catalog_1, {:title => "Maunz, Guetlein, Rautenberg, Vorgrimmler, Gebele and Helma (2013), lazar: a modular predictive toxicology framework  ", :url => "http://dx.doi.org/10.3389/fphar.2013.00038"}
+    report.ref_catalog :references, :publications_catalog, :publications_catalog_1
 
-  # Reference(s) to main scientific papers and/or software package 2.7
-  report.change_catalog :publications_catalog, :publications_catalog_2, {:title => "Maunz A and Helma C (2008) Prediction of chemical toxicity with local support vector regression and activity-specific kernels. SAR & QSAR in Environmental Research 19 (5-6), 413-431", :url => "http://dx.doi.org/10.1080/10629360802358430"}
-  report.ref_catalog :references, :publications_catalog, :publications_catalog_2
+    # Reference(s) to main scientific papers and/or software package 2.7
+    report.change_catalog :publications_catalog, :publications_catalog_2, {:title => "Maunz A and Helma C (2008) Prediction of chemical toxicity with local support vector regression and activity-specific kernels. SAR & QSAR in Environmental Research 19 (5-6), 413-431", :url => "http://dx.doi.org/10.1080/10629360802358430"}
+    report.ref_catalog :references, :publications_catalog, :publications_catalog_2
 
-  # Species 3.1
-  report.value "model_species", prediction_model.species 
+    # Species 3.1
+    report.value "model_species", prediction_model.species 
 
-  # Endpoint 3.2 
-  report.change_catalog :endpoints_catalog, :endpoints_catalog_1, {:name => prediction_model.endpoint, :group => ""}
-  report.ref_catalog :model_endpoint, :endpoints_catalog, :endpoints_catalog_1
+    # Endpoint 3.2 
+    report.change_catalog :endpoints_catalog, :endpoints_catalog_1, {:name => prediction_model.endpoint, :group => ""}
+    report.ref_catalog :model_endpoint, :endpoints_catalog, :endpoints_catalog_1
 
-  # Endpoint Units 3.4
-  report.value "endpoint_units", "#{prediction_model.unit}"
+    # Endpoint Units 3.4
+    report.value "endpoint_units", "#{prediction_model.unit}"
 
-  model_type = model.class.to_s.gsub('OpenTox::Model::Lazar','')
+    model_type = model.class.to_s.gsub('OpenTox::Model::Lazar','')
 
-  # Type of model 4.1
-  report.value "algorithm_type", "#{model_type}"
+    # Type of model 4.1
+    report.value "algorithm_type", "#{model_type}"
 
-  # Explicit algorithm 4.2
-  report.change_catalog :algorithms_catalog, :algorithms_catalog_1, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "Neighbor algorithm: #{model.neighbor_algorithm.gsub('_',' ').titleize}#{(model.neighbor_algorithm_parameters[:min_sim] ? ' with similarity > ' + model.neighbor_algorithm_parameters[:min_sim].to_s : '')}"}
-  report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_1
-  report.change_catalog :algorithms_catalog, :algorithms_catalog_3, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "modified k-nearest neighbor #{model_type}"}
-  report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_3
-  if model.prediction_algorithm_parameters
-    pred_algorithm_params = (model.prediction_algorithm_parameters[:method] == "rf" ? "random forest" : model.prediction_algorithm_parameters[:method])
-  end
-  report.change_catalog :algorithms_catalog, :algorithms_catalog_2, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "Prediction algorithm: #{model.prediction_algorithm.gsub('OpenTox::Algorithm::','').gsub('_',' ').gsub('.', ' with ')} #{(pred_algorithm_params ? pred_algorithm_params : '')}"}
-  report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_2
+    # Explicit algorithm 4.2
+    report.change_catalog :algorithms_catalog, :algorithms_catalog_1, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "Neighbor algorithm: #{model.algorithms["similarity"]["method"].gsub('_',' ').titleize}#{(model.algorithms["similarity"][:min] ? ' with similarity > ' + model.algorithms["similarity"][:min].to_s : '')}"}
+    report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_1
+    report.change_catalog :algorithms_catalog, :algorithms_catalog_3, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "modified k-nearest neighbor #{model_type}"}
+    report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_3
+    if model.algorithms["prediction"]
+      pred_algorithm_params = (model.algorithms["prediction"][:method] == "rf" ? "random forest" : model.algorithms["prediction"][:method])
+    end
+    report.change_catalog :algorithms_catalog, :algorithms_catalog_2, {:definition => "see Helma 2016 and lazar.in-silico.ch, submitted version: #{lazar_commit}", :description => "Prediction algorithm: #{model.algorithms["prediction"].to_s.gsub('OpenTox::Algorithm::','').gsub('_',' ').gsub('.', ' with ')} #{(pred_algorithm_params ? pred_algorithm_params : '')}"}
+    report.ref_catalog :algorithm_explicit, :algorithms_catalog, :algorithms_catalog_2
 
-  # Descriptors in the model 4.3
-  if model.neighbor_algorithm_parameters[:type]
-    report.change_catalog :descriptors_catalog, :descriptors_catalog_1, {:description => "", :name => "#{model.neighbor_algorithm_parameters[:type]}", :publication_ref => "", :units => ""}
-    report.ref_catalog :algorithms_descriptors, :descriptors_catalog, :descriptors_catalog_1
-  end
+    # Descriptors in the model 4.3
+    if model.algorithms["descriptors"][:type]
+      report.change_catalog :descriptors_catalog, :descriptors_catalog_1, {:description => "", :name => "#{model.algorithms["descriptors"][:type]}", :publication_ref => "", :units => ""}
+      report.ref_catalog :algorithms_descriptors, :descriptors_catalog, :descriptors_catalog_1
+    end
 
-  # Descriptor selection 4.4
-  report.value "descriptors_selection", "#{model.feature_selection_algorithm.gsub('_',' ')} #{model.feature_selection_algorithm_parameters.collect{|k,v| k.to_s + ': ' + v.to_s}.join(', ')}" if model.feature_selection_algorithm
-  
-  # Algorithm and descriptor generation 4.5
-  report.value "descriptors_generation", "exhaustive breadth first search for paths in chemical graphs (simplified MolFea algorithm)"
-  
-  # Software name and version for descriptor generation 4.6
-  report.change_catalog :software_catalog, :software_catalog_2, {:name => "lazar, submitted version: #{lazar_commit}", :description => "simplified MolFea algorithm", :number => "2", :url => "https://lazar.in-silico.ch", :contact => "info@in-silico.ch"}
-  report.ref_catalog :descriptors_generation_software, :software_catalog, :software_catalog_2
-
-  # Chemicals/Descriptors ratio 4.7
-  report.value "descriptors_chemicals_ratio", "not applicable (classification based on activities of neighbors, descriptors are used for similarity calculation)"
-
-  # Description of the applicability domain of the model 5.1
-  report.value "app_domain_description", "<html><head></head><body>
-      <p>
-        The applicability domain (AD) of the training set is characterized by 
-        the confidence index of a prediction (high confidence index: close to 
-        the applicability domain of the training set/reliable prediction, low 
-        confidence: far from the applicability domain of the 
-        trainingset/unreliable prediction). The confidence index considers (i) 
-        the similarity and number of neighbors and (ii) contradictory examples 
-        within the neighbors. A formal definition can be found in Helma 2006.
-      </p>
+    # Descriptor selection 4.4
+    report.value "descriptors_selection", "#{model.algorithms["feature_selection"].gsub('_',' ')} #{model.algorithms["feature_selection"].collect{|k,v| k.to_s + ': ' + v.to_s}.join(', ')}" if model.algorithms["feature_selection"]
+    
+    # Algorithm and descriptor generation 4.5
+    report.value "descriptors_generation", "exhaustive breadth first search for paths in chemical graphs (simplified MolFea algorithm)"
+    
+    # Software name and version for descriptor generation 4.6
+    report.change_catalog :software_catalog, :software_catalog_2, {:name => "lazar, submitted version: #{lazar_commit}", :description => "simplified MolFea algorithm", :number => "2", :url => "https://lazar.in-silico.ch", :contact => "info@in-silico.ch"}
+    report.ref_catalog :descriptors_generation_software, :software_catalog, :software_catalog_2
+
+    # Chemicals/Descriptors ratio 4.7
+    report.value "descriptors_chemicals_ratio", "not applicable (classification based on activities of neighbors, descriptors are used for similarity calculation)"
+
+    # Description of the applicability domain of the model 5.1
+    report.value "app_domain_description", "<html><head></head><body>
+        <p>
+          The applicability domain (AD) of the training set is characterized by 
+          the confidence index of a prediction (high confidence index: close to 
+          the applicability domain of the training set/reliable prediction, low 
+          confidence: far from the applicability domain of the 
+          trainingset/unreliable prediction). The confidence index considers (i) 
+          the similarity and number of neighbors and (ii) contradictory examples 
+          within the neighbors. A formal definition can be found in Helma 2006.
+        </p>
+        <p>
+          The reliability of predictions decreases gradually with increasing 
+          distance from the applicability domain (i.e. decreasing confidence index)
+        </p>
+      </body>
+    </html>"
+
+    # Method used to assess the applicability domain 5.2
+    report.value "app_domain_method", "see Helma 2006 and Maunz 2008"
+    
+    # Software name and version for applicability domain assessment 5.3  
+    report.change_catalog :software_catalog, :software_catalog_3, {:name => "lazar, submitted version: #{lazar_commit}", :description => "integrated into main lazar algorithm", :number => "3", :url => "https://lazar.in-silico.ch", :contact => "info@in-silico.ch"}
+    report.ref_catalog :app_domain_software, :software_catalog, :software_catalog_3
+
+    # Limits of applicability 5.4
+    report.value "applicability_limits", "Predictions with low confidence index, unknown substructures and neighbors that might act by different mechanisms"
+
+    # Availability of the training set 6.1
+    report.change_attributes "training_set_availability", {:answer => "Yes"}
+
+    # Available information for the training set 6.2
+    report.change_attributes "training_set_data", {:cas => "Yes", :chemname => "Yes", :formula => "Yes", :inchi => "Yes", :mol => "Yes", :smiles => "Yes"}
+
+    # Data for each descriptor variable for the training set 6.3
+    report.change_attributes "training_set_descriptors", {:answer => "No"}
+
+    # Data for the dependent variable for the training set 6.4
+    report.change_attributes "dependent_var_availability", {:answer => "All"}
+
+    # Other information about the training set 6.5
+    report.value "other_info", "#{prediction_model.source}"
+
+    # Pre-processing of data before modelling 6.6
+    report.value "preprocessing", (model.class == OpenTox::Model::LazarRegression ? "-log10 transformation" : "none")
+
+    # Robustness - Statistics obtained by leave-many-out cross-validation 6.9
+    if prediction_model.repeated_crossvalidation
+      crossvalidations = prediction_model.crossvalidations
+      out = haml File.read(validation_template), :layout=> false, :locals => {:model => prediction_model}
+      report.value "lmo",  out
+    end
+
+    # Mechanistic basis of the model 8.1
+    report.value "mechanistic_basis","<html><head></head><body>
       <p>
-        The reliability of predictions decreases gradually with increasing 
-        distance from the applicability domain (i.e. decreasing confidence index)
+        Compounds with similar structures (neighbors) are assumed to have 
+        similar activities as the query compound. For the determination of 
+        activity specific similarities only statistically relevant subtructures 
+        (paths) are used. For this reason there is a priori no bias towards 
+        specific mechanistic hypothesis.
       </p>
     </body>
   </html>"
 
-  # Method used to assess the applicability domain 5.2
-  report.value "app_domain_method", "see Helma 2006 and Maunz 2008"
-  
-  # Software name and version for applicability domain assessment 5.3  
-  report.change_catalog :software_catalog, :software_catalog_3, {:name => "lazar, submitted version: #{lazar_commit}", :description => "integrated into main lazar algorithm", :number => "3", :url => "https://lazar.in-silico.ch", :contact => "info@in-silico.ch"}
-  report.ref_catalog :app_domain_software, :software_catalog, :software_catalog_3
-
-  # Limits of applicability 5.4
-  report.value "applicability_limits", "Predictions with low confidence index, unknown substructures and neighbors that might act by different mechanisms"
-
-  # Availability of the training set 6.1
-  report.change_attributes "training_set_availability", {:answer => "Yes"}
-
-  # Available information for the training set 6.2
-  report.change_attributes "training_set_data", {:cas => "Yes", :chemname => "Yes", :formula => "Yes", :inchi => "Yes", :mol => "Yes", :smiles => "Yes"}
-
-  # Data for each descriptor variable for the training set 6.3
-  report.change_attributes "training_set_descriptors", {:answer => "No"}
-
-  # Data for the dependent variable for the training set 6.4
-  report.change_attributes "dependent_var_availability", {:answer => "All"}
-
-  # Other information about the training set 6.5
-  report.value "other_info", "#{prediction_model.source}"
-
-  # Pre-processing of data before modelling 6.6
-  report.value "preprocessing", (model.class == OpenTox::Model::LazarRegression ? "-log10 transformation" : "none")
-
-  # Robustness - Statistics obtained by leave-many-out cross-validation 6.9
-  if prediction_model.repeated_crossvalidation
-    crossvalidations = prediction_model.crossvalidations
-    out = haml File.read(validation_template), :layout=> false, :locals => {:model => prediction_model}
-    report.value "lmo",  out
+    # A priori or a posteriori mechanistic interpretation 8.2
+    report.value "mechanistic_basis_comments","a posteriori for individual predictions"
+
+    # Other information about the mechanistic interpretation 8.3
+    report.value "mechanistic_basis_info","<html><head></head><body><p>Hypothesis about biochemical mechanisms can be derived from individual 
+        predictions by inspecting neighbors and relevant fragments.</p>
+        <p>Neighbors are compounds that are similar in respect to a certain 
+        endpoint and it is likely that compounds with high similarity act by 
+        similar mechanisms as the query compound. Links at the webinterface 
+        prove an easy access to additional experimental data and literature 
+        citations for the neighbors and the query structure.</p>
+        <p>Activating and deactivating parts of the query compound are highlighted 
+        in red and green on the webinterface. Fragments that are unknown (or too 
+        infrequent for statistical evaluation are marked in yellow and 
+        additional statistical information about the individual fragments can be 
+        retrieved. Please note that lazar predictions are based on neighbors and 
+        not on fragments. Fragments and their statistical significance are used 
+        for the calculation of activity specific similarities.</p>"
+
+    # Bibliography 9.2
+    report.ref_catalog :bibliography, :publications_catalog, :publications_catalog_1
+    report.ref_catalog :bibliography, :publications_catalog, :publications_catalog_2
+    report.change_catalog :publications_catalog, :publications_catalog_3, {:title => "Helma (2006), Lazy structure-activity relationships (lazar) for the prediction of rodent carcinogenicity and Salmonella mutagenicity.", :url => "http://dx.doi.org/10.1007/s11030-005-9001-5"}
+    report.ref_catalog :bibliography, :publications_catalog, :publications_catalog_3
+
+    # output
+    response['Content-Type'] = "application/xml"
+    return report.to_xml
+  else
+    bad_request_error "Mime type #{@accept} is not supported."
   end
 
-  # Mechanistic basis of the model 8.1
-  report.value "mechanistic_basis","<html><head></head><body>
-    <p>
-      Compounds with similar structures (neighbors) are assumed to have 
-      similar activities as the query compound. For the determination of 
-      activity specific similarities only statistically relevant subtructures 
-      (paths) are used. For this reason there is a priori no bias towards 
-      specific mechanistic hypothesis.
-    </p>
-  </body>
-</html>"
-
-  # A priori or a posteriori mechanistic interpretation 8.2
-  report.value "mechanistic_basis_comments","a posteriori for individual predictions"
-
-  # Other information about the mechanistic interpretation 8.3
-  report.value "mechanistic_basis_info","<html><head></head><body><p>Hypothesis about biochemical mechanisms can be derived from individual 
-      predictions by inspecting neighbors and relevant fragments.</p>
-      <p>Neighbors are compounds that are similar in respect to a certain 
-      endpoint and it is likely that compounds with high similarity act by 
-      similar mechanisms as the query compound. Links at the webinterface 
-      prove an easy access to additional experimental data and literature 
-      citations for the neighbors and the query structure.</p>
-      <p>Activating and deactivating parts of the query compound are highlighted 
-      in red and green on the webinterface. Fragments that are unknown (or too 
-      infrequent for statistical evaluation are marked in yellow and 
-      additional statistical information about the individual fragments can be 
-      retrieved. Please note that lazar predictions are based on neighbors and 
-      not on fragments. Fragments and their statistical significance are used 
-      for the calculation of activity specific similarities.</p>"
-
-  # Bibliography 9.2
-  report.ref_catalog :bibliography, :publications_catalog, :publications_catalog_1
-  report.ref_catalog :bibliography, :publications_catalog, :publications_catalog_2
-  report.change_catalog :publications_catalog, :publications_catalog_3, {:title => "Helma (2006), Lazy structure-activity relationships (lazar) for the prediction of rodent carcinogenicity and Salmonella mutagenicity.", :url => "http://dx.doi.org/10.1007/s11030-005-9001-5"}
-  report.ref_catalog :bibliography, :publications_catalog, :publications_catalog_3
-
-  # output
-  response['Content-Type'] = "application/xml"
-  return report.to_xml
-
 end
-- 
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