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Gene Analytics: Discovery and Contextualization of Enriched Gene Sets

author: Nada Lavrač, Department of Knowledge Technologies, Jožef Stefan Institute

Description

The paper present a preliminary study of creative knowledge discovery through bisociative data analysis. Bisociative reasoning is at the heart of creative, accidental discovery (serendipity), and is focused on finding unexpected links by crossing different contexts. Contextualization and linking between highly diverse and distributed data and knowledge sources is therefore crucial for implementation of bisociative reasoning. In the paper we explore these ideas on the problem of analysis of microarray data. We show how enriched gene sets are found by using ontology information as background knowledge in semantic subgroup discovery. These genes are then contextualized by the computation of probabilistic links to diverse bioinformatics resources. Results of two case studies are used to illustrate the approach.

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Slides
0:00 Gene Analytics: Discovery and Contextualization of Enriched Gene Groups
0:10 Talk outline
0:58 Data Mining
1:18 Subgroup discovery task definition
1:58 Sample microarray analysis tasks
2:34 Relational Data Mining (Inductive Logic Programming)
2:50 Relational Data Mining (ILP)
3:50 Gene Ontology (GO)
4:34 Ontology encoded as relational background knowledge
5:14 Multi-Relational representation
5:30 Propositionalization in RDM
7:14 Gene set enrichment analysis with SEGS
7:34 Ontologies
7:46 Identifying differentially expressed genes in data preprocessing 1
8:22 Ranking of differentially expressed genes
8:46 Gene expression data: Positive and negative examples for data mining
9:14 Ontology encoded as relational background knowledge + gene expression data 1
9:26 Ontology encoded as relational features + gene expression data
9:34 Propositionalization
10:10 Propositional subgroup discovery
10:34 Summary: SEGS Method and Results
10:46 SEGS implementation
10:58 BISON project
11:18 SEGS implementation
11:54 BISON project
12:58 Heterogeneous data sources (BISON, M. Berthold, 2008)
13:10 Bridging concepts (BISON, M. Berthold, 2008)
13:18 Use Case: Glioma Cancer (investigated at NIB)
13:50 Glioma treatment
14:30 Gene Analytics
14:54 SEGS+Biomine Methodology
15:42 Biomine
16:22 Biomine Information fusion
16:30 SEGS+Biomine Methodology
17:18 Biomine: Bisociative link discovery
17:38 SEGS+Biomine Information fusion
17:46 SEGS+Biomine Creative knowledge discovery
17:50 SEGS+Biomine Creative link discovery
17:58 SEGS+Biomine Exploration and explanation
18:02 Summary

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