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A Biomedical Text Mining Suite for Concept Discovery
BioTextQuest accepts a
PubMed or an OMIM query
. In the case of OMIM, either the
OMIM
text
will be processed or the
PubMed articles referenced in the OMIM text (OMIM references)
.
The collected articles or text are then
clustered in meaningfull clusters
. The most important
terms of each cluster are
presented in a tag cloud format and enriched by exterior services
.
Query:
(examples:
#1,
#2,
#3
)
Target database:
PubMed
OMIM refereneces
OMIM text
PubMed aspects to use :
abstracts
MeSH terms
both
 
Max number of articles:
Advanced Options
Remove common word suffixes
Similarity Matrix :
Cosine
Tanimoto
Pearson
Spearman
Kendall
BM25
Threshold:
Clustering Algorithm:
K-means
Markov Clustering (MCL)
Hierarchical: Average linkage
Spectral Clustering
Affinity Propagation
Spectral Clustering (NEW)
Fewer
clusters
More
clusters
1
5
10
15
20
Number of clusters
Fewer
clusters
More
clusters
1.02
1.03
1.04
1.05
Epsilon
Fewer
clusters
More
clusters
1
2
3
4
5
Inflation