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List Of International Journal Publications
47. A. Ghosh and R. K. De, Development of a fuzzy entropy based method for detecting altered gene-gene interactions in carcinogenic state, Journal of Intelligent & Fuzzy Systems, (in press).
46. A. Ghosh, B. C. Dhara, and R. K. De, Selection of genes mediating certain cancers, using Neuro-Fuzzy Approach, Neurocomputing, (in press).
45. A. Bhattacharya, N. Chowdhury, and R. K. De, Concepts of Relative Sample Outlier (RSO) and Weighted Sample Similarity (WSS) for improving performance of clustering genes: Co-function and co-regulation, International Journal of Data Mining and Bioinformatics, (in press).
44. M. Das, S. Mukhopadhyay, and R. K. De, Development of an engineering method to optimize polyamine metabolic pathways, Current Bioinformatics, (in press).
43. S. Tagore, N. Chowdhury, and R. K. De, Analyzing methods for path mining with applications in metabolomics, Gene, vol. 534, no. 2, pp. 125-138, 2014.
42. S. Tagore and R. K. De, Simulating an infection growth model in certain healthy metabolic pathways of Homo sapiens for highlighting their role in type I diabetes mellitus using fire-spread strategy, feedbacks and sensitivities, PLoS ONE, vol. 8, no. 9, pp. e69724, 2013.
41. M. Das, C. A. Murthy, and R. K. De, An optimization rule for in silico identification of targeted overproduction in metabolic pathways, IEEE/ACM Transactions on Computational Biology and Bioinformatics, (accepted).
40. N. Tomar and R. K. De, A comprehensive view on metabolic pathway analysis methodologies, Current Bioinformatics, vol. 9, no. 3, pp. 295-305, 2014.
39. N. Tomar and R. K. De, A model of an integrated immune system pathway in Homo sapiens and its interaction with superantigen producing expression regulatory pathway in Staphylococcus aureus: Comparing behavior of pathogen perturbed and unperturbed pathway, PLoS ONE, vol. 8, no. 12, pp. e80918, 2013.
38. L. Nayak, H. Tunga, and R. K. De, Disease co-morbidity and the human Wnt signaling pathway: A Network-Wise Study, OMICS: A Journal of Integrative Biology, vol. 17, no. 6, pp. 318-337, 2013.
37. N. Tomar and R. K. De, Comparing methods for metabolic network analysis and an application to Metabolic Engineering, GENE, vol. 521, no. 1, pp. 1-14, 2013.
36. N. Tomar, O. Choudhury, A. Chakrabarty and R. K. De, An integrated pathway systems modeling of Saccharomyces cerevisiae HOG pathway: A Petri net based approach, Molecular Biology Reports, Springer, DOI 10.1007/s11033-012-2153-3, pp. 1-23, 2012.
35. R. K. De and N. Tomar, Modeling the optimal CCM pathways under feedback inhibition using flux balance analysis, Journal of Bioinformatics and Computational Biology, vol. 10, no. 6, pp. 1-34, 2012.
34. N. Tomar and R. K. De, Modeling host-pathogen interactions: H. sapiens as a host and C. difficile as a pathogen, Journal of Molecular Recognition, vol. 25, no. 9, pp. 474-85. 2012.
33. S. Tagore and R. K. De, SAGPAR: StructurAl Grammar-based automated PAthway Reconstruction, Interdisciplinary Sciences: Computational Life Sciences, vol. 4, no. 2, pp. 116-127, 2012.
32. R. K. De and S. Tagore, Automated reconstruction of metabolic pathways of Homo sapiens involved in the functioning of GAD1 and GAD2 genes based on structural grammars, Metabolomics: Open Access, S1:005. doi:10.4172/2153-0769.S1-005
31. A. Bhattacharya, N. Chowdhury, and R. K. De, Comparative analysis of clustering and biclustering algorithms for grouping of genes: co-function and co-regulation, Current Bioinformatics, vol. 7, pp. 63-76, 2012.
30. S. Tagore R. K. De, Detecting breakdown points in metabolic networks, Computational Biology and Chemistry, vol. 35, pp. 371-380, 2011.
29. A. Bhattacharya and R. K. De, A novel noise handling method to improve clustering of gene expression patterns, BMC Bioinformatics, vol. 12 (Suppl 7):A3, doi:10.1186/1471-2105-12-S7-A3.
28. M. Das, S. Mukhopadhyay, and R. K. De, Gradient descent optimization in gene regulatory pathways, PLoS ONE, vol. 5, no. 9, e12475, 2010. doi:10.1371/journal.pone.0012475.
27. N. Tomar and R. K. De, Immunoinformatics: An integrated scenario, Immunology, vol. 131, pp. 153-168, 2010.
26. N. Tomar, L. Nayak, and R. K. De, Comparative analysis of various algorithms in modularizing VEGF signaling pathway: Exploring gradual development over various species, Journal of Biomedical Science and Engineering, vol. 3, no. 10, pp. 931-942, 2010.
25. A. Bhattacharya and R. K. De, Average correlation clustering algorithm (ACCA) for grouping of co-regulated genes with similar pattern of variation in their expression value, Journal of Biomedical Informatics, vol. 43, no. 4, pp. 560-568, 2010.
24. S. Sinha, T. S. Vasulu, and R. K. De, Performance and evaluation of microRNA gene identification tools, Journal of Proteomics and Bioinformatics, vol.2, no. 8, pp. 336-343, 2009.
23. R. K. De and A. Ghosh, Interval based fuzzy systems for identification of important genes from microarray gene expression data: Application to carcinogenic development, Journal of Biomedical Informatics, vol. 42, pp. 1022-1028, 2009.
22. A. Bhattacharya and R. K. De, Bi-correlation clustering algorithm for determining a set of co-regulated genes, Bioinformatics, vol. 25, no. 21, pp. 2795-2801, 2009.
21. R. K. De and A. Ghosh, Linguistic recognition system for identification of some possible genes mediating the development of lung adenocarcinoma, Information Fusion (Special Issue on Natural Computing in Bioinformatics), vol. 10, no. 3, pp. 260-269, 2009.
20. S. Tagore, V. S. Gomase, and R. K. De, Pathway modeling: New face of graphical probabilistic analysis, Journal of Proteomics and Bioinformatics, vol. 1, no. 5, pp. 281-286, 2008.
19. R. K. De, M. Das, and S. Mukhopadhyay, Incorporation of enzyme concentrations into FBA and identification of optimal metabolic pathways, BMC Systems Biology, 2:65, 2008.
18. A. Bhattacharya and R. K. De, Divisive correlation clustering algorithm (DCCA) for grouping of genes: Detecting varying patterns in expression profiles, Bioinformatics, vol. 24, 1359-1366, 2008.
17. R. K. De, M. Das, and S. Mukhopadhyay, Learning weights representing enzyme concentration: Identification of metabolic pathways, Far East Journal of Experimental and Theoretical Artificial Intelligence, vol. 1, pp. 23-43, 2008.
16. R. K. De and A. Bhattacharya, Clustering on gene expression and fold values: Identification of some possible genes mediating allergic asthma, International Journal of Computational Cognition, vol. 5, no. 1, pp. 35-43, 2007.
15. L. Nayak and R. K. De, Modularized study of human calcium signaling pathway, Journal of Biosciences, vol. 32, no. 5, pp. 1009-1017, 2007.
14. L. Nayak and R. K. De, An algorithm for modularization of MAPK and Calcium signaling pathways: Comparative analysis among different species, Journal of Biomedical Informatics, vol. 40, pp. 726-749, 2007.
13. R. K. De and A. Ghosh, Generation of linguistic rules on the genes mediating the development of lung adenocarcinoma, Research in Computing Science (Special Issue on Advances in Computer Science and Engineering), vol. 23, pp. 87-98, 2006.
12. M. Acharyya, R. K. De, and M. K. Kundu, Segmentation of remotely sensed images using wavelet features and their evaluation in soft computing framework, IEEE Transactions on Geoscience and Remote Sensing, vol. 41, pp. 2900-2905, 2003.
11. M. Acharyya, R. K. De, and M. K. Kundu, Extraction of features using M-band wavelet packet frame and their neuro-fuzzy evaluation for multi-texture segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, pp. 1639-1644, 2003.
10. R. K. De, J. Basak, and S. K. Pal, Unsupervised feature extraction using neuro-fuzzy approach, Fuzzy Sets and Systems, vol. 126, pp. 277-291, 2002.
9. R. K. De and S. K. Pal, A connectionist model for selection of cases,Information Sciences, vol. 132, pp. 179-194, 2001.
8. R. K. De and S. K. Pal, Pattern classification using fuzzy sets and neural nets: A case based approach, International Journal of Engineering Intelligent Systems, vol. 8, pp. 103-108, 2000.
7. S. K. Pal, R. K. De, and J. Basak, Unsupervised feature evaluation: A neuro-fuzzy approach, IEEE Transactions on Neural Networks, vol. 11, pp. 366-376, 2000.
6. R. K. De, J. Basak, and S. K. Pal, Neuro-fuzzy feature evaluation with theoretical analysis, Neural Networks, vol. 12, pp. 1429-1455, 1999.
5. J. Basak, R. K. De, and S. K. Pal, Unsupervised feature selection using neuro-fuzzy approach, Pattern Recognition Letters, vol. 19, pp. 997-1006, 1998.
4. J. Basak, R. K. De, and S. K. Pal, Fuzzy feature evaluation index and connectionist realization-II: Theoretical analysis, Information Sciences, vol. 111, pp. 1-17, 1998.
3. S. K. Pal, J. Basak, and R. K. De, Fuzzy feature evaluation index and connectionist realization, Information Sciences, vol. 105, pp. 173-188, 1998.
2. S. Mitra, R. K. De, and S. K. Pal, Knowledge-based fuzzy MLP for classification and rule generation, IEEE Transactions. on Neural Networks, vol. 8, pp. 1338-1350, 1997.
1. R. K. De, N. R. Pal, and S. K. Pal, Feature analysis: Neural network and fuzzy set theoretic approaches, Pattern Recognition, vol. 30, pp. 1579-1590, 1997.