Improving text clustering for functional analysis of genes
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Summary
The goal of this project was to build a text clustering-based software system, called GeneNarrator, for functional analysis of genes (microarray experiments), and to demonstrate how biologists can be presented with dozens of topics as a summarization of the citations, and gene (groups) mapped to the topics.
- Type
- dissertation
- Published
- 2006-01-01
- Cited by
- 0
- References
- 97
- Access
- Open access
- OpenAlex
- https://openalex.org/W7520102
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9620278
Keywords
Cluster analysis, Computer science, Automatic summarization, Information retrieval, Document clustering
References
- Text mining with the WEBSOM
- Design of a Standoff Object-Oriented Markup Language (sooml) for Annotating Biomedical Literature
- PathBinderH: a tool for sentence-focused, plant taxonomy-sensitive access to the biological literature.
- MedMeSH Summarizer: Text Mining for Gene Clusters
- Finding Groups in Data: An Introduction to Cluster Analysis
- Text Retrieval Using Self-Organized Document Maps
- A dynamic adaptive self-organising hybrid model for text clustering
- The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data
- Book Reviews: Foundations of Statistical Natural Language Processing
- What Is the Nearest Neighbor in High Dimensional Spaces?
- A Probabilistic Approach to Full-Text Document Clustering
- Saccharomyces Genome Database.
- A Comparison of Document Clustering Techniques
- PubMatrix: a tool for multiplex literature mining
- Ontology-based text clustering
- Hierarchical Text Categorization Using Neural Networks
- Introduction to Modern Information Retrieval
- Describing inequality in plant size or fecundity
- Data clustering: a review
- Scatter/Gather: a cluster-based approach to browsing large document collections
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