Data Mining and Bioinformatics

1. Front Matter

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2. Bioinformatics at Microsoft Research

   • Simon Mercer

   Pages 1-1

3. A Novel Approach for Effective Learning of Cluster Structures with Biological Data Applications

   • Miyoung Shin

   Pages 2-13

4. Subspace Clustering of Microarray Data Based on Domain Transformation

   • Jongeun Jun, Seokkyung Chung, Dennis McLeod

   Pages 14-28

5. Bayesian Hierarchical Models for Serial Analysis of Gene Expression

   • Seungyoon Nam, Seungmook Lee, Sanghyuk Lee, Seokmin Shin, Taesung Park

   Pages 29-39

6. Applying Gaussian Distribution-Dependent Criteria to Decision Trees for High-Dimensional Microarray Data

   • Raymond Wan, Ichigaku Takigawa, Hiroshi Mamitsuka

   Pages 40-49

7. A Biological Text Retrieval System Based on Background Knowledge and User Feedback

   • Meng Hu, Jiong Yang

   Pages 50-64

8. Automatic Annotation of Protein Functional Class from Sparse and Imbalanced Data Sets

   • Jaehee Jung, Michael R. Thon

   Pages 65-77

9. Bioinformatics Data Source Integration Based on Semantic Relationships Across Species

   • Badr Al-Daihani, Alex Gray, Peter Kille

   Pages 78-93

10. An Efficient Storage Model for the SBML Documents Using Object Databases

    • Seung-Hyun Jung, Tae-Sung Jung, Tae-Kyung Kim, Kyoung-Ran Kim, Jae-Soo Yoo, Wan-Sup Cho

    Pages 94-105

11. Identification of Phenotype-Defining Gene Signatures Using the Gene-Pair Matrix Based Clustering

    • Chung-Wein Lee, Shuyu Dan Li, Eric W. Su, Birong Liao

    Pages 106-119

12. TP+Close: Mining Frequent Closed Patterns in Gene Expression Datasets

    • YuQing Miao, GuoLiang Chen, Bin Song, ZhiHao Wang

    Pages 120-130

13. Exploring Essential Attributes for Detecting MicroRNA Precursors from Background Sequences

    • Yun Zheng, Wynne Hsu, Mong Li Lee, Limsoon Wong

    Pages 131-145

14. A Gene Structure Prediction Program Using Duration HMM

    • Hongseok Tae, Eun-Bae Kong, Kiejung Park

    Pages 146-157

15. An Approximate de Bruijn Graph Approach to Multiple Local Alignment and Motif Discovery in Protein Sequences

    • Rupali Patwardhan, Haixu Tang, Sun Kim, Mehmet Dalkilic

    Pages 158-169

16. Discovering Consensus Patterns in Biological Databases

    • Mohamed Y. ElTabakh, Walid G. Aref, Mourad Ouzzani, Mohamed H. Ali

    Pages 170-184

17. Comparison of Modularization Methods in Application to Different Biological Networks

    • Zhuo Wang, Xin-Guang Zhu, Yazhu Chen, Yixue Li, Lei Liu

    Pages 185-195

18. Back Matter

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This volume contains the papers presented at the inaugural workshop on Data Mining and Bioinformatics at the 32nd International Conference on Very Large Data Bases (VLDB). The purpose of this workshop was to begin bringing - gether researchersfrom database, data mining, and bioinformatics areas to help leverage respective successes in each to the others. We also hope to expose the richness, complexity, and challenges in this area that involves mining very large complex biological data that will only grow in size and complexity as geno- scale high-throughput techniques become more routine. The problems are s- ?ciently di?erent enough from traditional data mining problems (outside of life sciences) that novel approaches must be taken to data mine in this area. The workshop was held in Seoul, Korea, on September 11, 2006. We received 30 submissions in response to the call for papers. Each subm- sion was assigned to at least three members of the Program Committee. The Program Committee discussed the submission electronically, judging them on their importance, originality, clarity, relevance, and appropriateness to the - pected audience. The Program Committee selected 15 papers for presentation. These papers arein the areasof microarraydata analysis, bioinformaticssystem and text retrieval, application of gene expression data, and sequence analysis. Because of the format of the workshop and the high number of submissions, many good papers could not be included.

• Alignment
• Annotation
• Microarray
• Radiologieinformationssystem
• algorithms
• association rule mining
• bioinformatics
• biomedical data analysis
• biomedical informatics
• classification
• data mining
• databases
• discretization
• hierarchical clustering
• sequence analysis

• School of Informatics, Indiana University, Bloomington,  

  Mehmet M. Dalkilic, Sun Kim

• EECS Department, Case Western Reserve Univ., Cleveland, USA

  Jiong Yang

Policies and ethics