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V-cluster algorithm: A new algorithm for clustering molecules based upon numeric data

Molecular Diversity volume 10, pages 463–478 (2006)Cite this article

Summary

Clustering molecules based on numeric data such as, gene-expression data, physiochemical properties, or theoretical data is very important in drug discovery and other life sciences. Most approaches use hierarchical clustering algorithms, non-hierarchical algorithms (for examples, K-mean and K-nearest neighbor), and other similar methods (for examples, the Self-Organization Mapping (SOM) and the Support Vector Machine (SVM)). These approaches are non-robust (results are not consistent) and, computationally expensive. This paper will report a new, non-hierarchical algorithm called the V-Cluster (V stands for vector) Algorithm. This algorithm produces rational, robust results while reducing computing complexity. Similarity measurement and data normalization rules are also discussed along with case studies. When molecules are represented in a set of numeric vectors, the V-Cluster Algorithm clusters the molecules in three steps: (1) ranking the vectors based upon their overall intensity levels, (2) computing cluster centers based upon neighboring density, and (3) assigning molecules to their nearest cluster center. The program is written in C/C++ language, and runs on Window95/NT and UNIX platforms. With the V-Cluster program, the user can quickly complete the clustering process and, easily examine the results by use of thumbnail graphs, superimposed intensity curves of vectors, and spreadsheets. Multi-functional query tools have also been implemented.

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Affiliations

  1. Boehringer Ingelheim Pharmaceuticals, Inc., 900 Ridgebury Road, Ridgefield, Connecticut, 06877-0368, USA

    Jun Xu, Qiang Zhang & Chen-Kon Shih

  2. Research Center of Modernization of Chinese Traditional Medicine, Department of Chemistry, Central South University, Lu Shan Road, Chang Sha, 410083, P.R. China

    Jun Xu

  3. Discovery Partners International, Inc., 9640 Towne Centre Drive, San Diego, CA, 92121, U.S.A.

    Jun Xu

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  1. Jun Xu
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  2. Qiang Zhang
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Correspondence to Jun Xu.

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Xu, J., Zhang, Q. & Shih, CK. V-cluster algorithm: A new algorithm for clustering molecules based upon numeric data. Mol Divers 10, 463–478 (2006). https://doi.org/10.1007/s11030-006-9023-7

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  • DOI: https://doi.org/10.1007/s11030-006-9023-7

Keywords

  • cluster algorithm
  • similarity
  • data normalization