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Integrated statistical and rule-mining techniques for dna methylation and gene expression data analysis

Mallik S., Mukhopadhyay A., Maulik U.

Journal of Artificial Intelligence and Soft Computing Research

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2013

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Vol. 3, No. 2

101--115

EN

For determination of the relationships among significant gene markers, statistical analysis and association rule mining are considered as very useful protocols. The first protocol identifies the significant differentially expressed/methylated gene markers, whereas the second one produces the interesting relationships among them across different types of samples or conditions. In this article, statistical tests and association rule mining based approaches have been used on gene expression and DNA methylation datasets for the prediction of different classes of samples (viz., Uterine Leiomyoma/class-formersmoker and uterine myometrium/class-neversmoker). A novel rule-based classifier is proposed for this purpose. Depending on sixteen different rule-interestingness measures, we have utilized a Genetic Algorithm based rank aggregation technique on the association rules which are generated from the training set of data by Apriori association rule mining algorithm. After determining the ranks of the rules, we have conducted a majority voting technique on each test point to estimate its class-label through weighted-sum method. We have run this classifier on the combined dataset using 4-fold cross-validations, and thereafter a comparative performance analysis has been made with other popular rulebased classifiers. Finally, the status of some important gene markers has been identified through the frequency analysis in the evolved rules for the two class-labels individually to formulate the interesting associations among them.

2

Unsupervised Pixel Classification in Satellite Imagery: A Two-stage Fuzzy Clustering Approach

Mukhopadhyay A., Maulik U.

Fundamenta Informaticae

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2008

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Vol. 86, nr 4

411-428

EN

A popular approach for landcover classification in remotely sensed satellite images is clustering the pixels in the spectral domain into several fuzzy partitions. It has been observed that performance of the clustering algorithms deteriorate with more and more overlaps in the data sets. Motivated by this observation, in this article a two-stage fuzzy clustering algorithm is described that utilizes the concept of points having significant membership to multiple classes. The points situated in the overlapped regions of different clusters are first identified and excluded from consideration while clustering. Thereafter, these points are given class labels based on Support vector Machine classifier which is trained by the remaining points. The well known Fuzzy C-Means algorithm and some recently proposed genetic clustering schemes are utilized in the process. The effectiveness of the two-stage clustering technique has been demonstrated on IRS remote sensing satellite images of the cities of Bombay and Calcutta and compared with other well known clustering techniques. Also statistical significance test has been carried out to establish the statistical significance of the clustering results.

3

Finite amplitude long wave instability of a film of conducting fluid flowing down an inclined plane in presence of electromagnetic field

Dandapat B. S., Mukhopadhyay A.

International Journal of Applied Mechanics and Engineering

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2003

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Vol. 8, no 3

379-383

EN

Stability characteristics of a thin conducting liquid film flowing down, on a non-conducting plane in the presence of the electromagnetic field is investigated under the assumption of a small magnetic Reynolds number. A surface evolution equation is derived by using the long-wave approximation method. A linear and non-linear stability analysis of the evolution equation shows that the magnetic field stabilizes the flow whereas the electric field stabilizes or destabilizes the flow depending on its orientation with the flow. It is found that both the subcritical instability and supercritical stability are possible in a finite amplitude regime. Two critical Hartmann numbers Mc and Mc>(Mc) are observed for subcritical and supercritical zones respectively. The existence of a subcritical unstable zone may be ruled out when Mc>Mc which is independent of other parameters whereas supercritical and explosive zones are possible till Mc