SiBIC: A tool for generating a network of biclusters captured by maximal frequent itemset mining

Kei Ichiro Takahashi*, David A. duVerle, Sohiya Yotsukura, Ichigaku Takigawa, Hiroshi Mamitsuka

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review


Biclustering extracts coexpressed genes under certain experimental conditions, providing more precise insight into the genetic behaviors than one-dimensional clustering. For understanding the biological features of genes in a single bicluster, visualizations such as heatmaps or parallel coordinate plots and tools for enrichment analysis are widely used. However, simultaneously handling many biclusters still remains a challenge. Thus, we developed a web service named SiBIC, which, using maximal frequent itemset mining, exhaustively discovers significant biclusters, which turn into networks of overlapping biclusters, where nodes are gene sets and edges show their overlaps in the detected biclusters. SiBIC provides a graphical user interface for manipulating a gene set network, where users can find target gene sets based on the enriched network. This chapter provides a user guide/instruction of SiBIC with background of having developed this software. SiBIC is available at

Original languageEnglish
Title of host publicationMethods in Molecular Biology
Number of pages17
ISBN (Electronic)978-1-4939-8561-6
Publication statusPublished - 1 Jan 2018
MoE publication typeA3 Part of a book or another research book

Publication series

NameMethods in Molecular Biology
PublisherHumana Press
ISSN (Print)1064-3745


  • Biclustering
  • Frequent itemset mining
  • Gene enrichment analysis
  • Gene expression
  • Gene set network

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