Abstract
An effective unsupervised method (TDAC) is proposed for identification of biologically relevant co-expressed patterns. Effectiveness of TDAC is established in comparison to its other competing algorithms over four publicly available benchmark gene expression datasets in terms of both internal and external validity measures.
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© 2014 Springer India
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Rahman, T., Bhattacharyya, D. (2014). TDAC: Co-Expressed Gene Pattern Finding Using Attribute Clustering. In: Babu, B., et al. Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012. Advances in Intelligent Systems and Computing, vol 236. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_64
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DOI: https://doi.org/10.1007/978-81-322-1602-5_64
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