Index

1. Home/Query page

2. Results page

Analysis Parameter Summary

Re-Analysis Box

Tag Clouds

Drugs



Contents

1. Home/Query page [Go to top]

The home page of DrugQuest is the page where the user can input his query:



Query: The keywords with which the search will be performed over the DrugBank database. The query is a simple string matching using the boolean operastions: OR for any term, AND for every term .

Advanced Options: Control of clustering algorithms and their parameters. Upon Clicking on the Advanced Options, the user can change the default options:

Clustering Algorithm: (Default: MCL). Clustering can be performed by various algorithms. Currently the following clustering algorithms are supported: Markov Clustering (MCL), Hierarchical - Average Linkage, K-means, Spectral Clustering, Affinity Propagation and RNSC.
Each Clustering algorithm has parameters whose optimum values (according to the of the author of the implementation) are chosen as default. The user can change them according to his needs using the slider.

  • Markov Clustering (MCL), parameter: inflation (default: 1.8)
    The rule of thumb is that the larger the inflation parameter the more clusters will be created and the more fine-grained they will be.
  • Hierarchical - Average Linkage, parameter: number of clusters (default: 3)
    The user specifies the desired number of resulting clusters.
  • K-Means, parameter: number of clusters (default: 3)
    The user specifies the desired number of resulting clusters.
  • Spectral Clustering (MCL), parameter: epsilon (default: 1.03)
    The rule of thumb is that the larger the epsilon parameter the more clusters will be created and the more fine-grained they will be.

Clustering can be performed according to various similarity methods such as: Cosine similarity, Tanimoto similarity, Pearson, Kendall and Spearman correlations as well as Okabi BM25 document ranking algorithm.

2. Results page [Go to top]



Analysis Summary
The Analysis Summary displays the parameters, limits and keywords used to make the query whose results are being displayed

Tag Clouds

The clusters created by DrugQuest. Each cluster is represented by keywords. If a cluster is expanded, its keywords are displayed as a tag cloud. The size of each term is proportional to its frequency. The user may choose to highlight the terms that fall in any of the following 4 categories in a cluster:

  • unique
    significant terms that do not appear in any other cluster.

  • non-standard English
    significant terms that are not standard grammatical terms (they do not belong in the dictionary used by DrugQuest).

  • chemicals
    significant terms that describe drugs (PubChem database dictionary).

  • proteins
    significant terms that describe proteins (Reflect web service).

  • diseases
    significant terms that describe diseases (subset of UMLS)

  • pathways
    significant terms that describe pathways and processes (BeCAS tagging service)

Drugs



  • The drugs that belong to each cluster.
    • Clicking on the icon will open a new window in DrugBank with the respective record.