Publications‎ > ‎

Journals

1. U. Biswas, M. K. Naskar, A. Mukhopadhyay and U. Maulik, “A Heuristic Algorithm for Static Wavelength Assignment in WDM Optical Networks”, IETE Technical Review, Vol. 22, No. 3, pp. 199-204, May-June 2004. [Impact Factor: 1.339] 

2. U. Maulik, A. Mukhopadhyay and S. Bandyopadhyay, “Efficient Clustering with Multi-class Point Identification”, Journal of Three Dimensional Images, Vol. 20, No. 1, pp. 35-40, Japan, 2006. 

3. S. Bandyopadhyay, U. Maulik and A. Mukhopadhyay, “Multiobjective Genetic Clustering for Pixel Classification in Remote Sensing Imagery”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 5, pp. 1506-1511, 2007. [Impact Factor: 4.662] 

4. S. Bandyopadhyay, A. Mukhopadhyay and U. Maulik, “An Improved Algorithm for Clustering Gene Expression Data”, Bioinformatics, Vol. 23, No. 21, pp. 2859-2865, 2007. [Impact Factor: 5.481] 

5. A. Mukhopadhyay and U. Maulik, “Unsupervised Pixel Classification in Satellite Imagery: A Two-stage Fuzzy  Clustering Approach”, Fundamenta Informaticae, Vol. 86, No. 4, pp. 411-428, 2008. [Impact Factor: 0.725] 

6. I. Saha and A. Mukhopadhyay, “Improved Crisp and Fuzzy  Clustering  Techniques  for  Categorical  Data”, IAENG International Journal of Computer Science, Vol. 35 Issue 4, pp. 438-450, 2008. 

7. U. Biswas, U. Maulik, A. Mukhopadhyay and M. K. Naskar, “Multiobjective Evolutionary Approach to Cost-effective Traffic  Grooming  in Unidirectional SONET/ WDM Rings”, Photonic Network Communications, Vol.  18,  No. 1, pp. 105-115, 2009. [Impact Factor: 1.203] 

8. A. Mukhopadhyay and U Maulik, “Unsupervised Pixel Classification in Satellite Imagery using Multiobjective Fuzzy Clustering combined with SVM Classifier”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, No. 4, pp. 1132-1138, 2009. [Impact Factor: 4.662] 

9. A. Mukhopadhyay, U Maulik and S. Bandyopadhyay, “Multi-objective Genetic Algorithm based Fuzzy  Clustering of Categorical Attributes”, IEEE Transactions on Evolutionary Computation, Vol. 13, No. 5, pp. 991-1005,  2009. [Impact Factor: 8.124] 

10. U Maulik, A. Mukhopadhyay and S. Bandyopadhyay, “Combining Pareto-Optimal Clusters using Supervised Learning for Identifying Co-expressed Genes”, BMC Bioinformatics, Vol. 10, No. 27, 2009. [Impact Factor:  2.213] 

11. U. Maulik and A. Mukhopadhyay, “Simulated  Annealing  based  Automatic  Fuzzy  Clustering  combined  with  ANN Classification for Analyzing Microarray Data”, Computers and Operations Research, Vol. 37, No. 8, pp. 1369-1380, 2009. [Impact Factor: 2.962] 

12. U. Maulik, A.  Mukhopadhyay and S. Bandyopadhyay,  “Finding Multiple Coherent Biclusters in Microarray Data using Variable String Length Multiobjective Genetic Algorithm”, IEEE Transactions on Information Technology in Biomedicine, Vol. 13, No. 6, pp. 969-975, 2009. [Impact Factor: 2.493] 

13. A. Mukhopadhyay and U. Maulik, “Towards Improving Fuzzy Clustering using Support Vector Machine: Application to Gene Expression Data”, Pattern Recognition, Vol. 42, No. 11, pp. 2744-2763, 2009. [Impact Factor: 3.962] 

14. A. Mukhopadhyay, U. Maulik and S. Bandyopadhyay, “A Novel Coherence Measure for Discovering Scaling Biclusters from Gene Expression Data”, Journal of Bioinformatics and Computational Biology, Vol. 7, No. 5, pp. 853-868, 2009. [Impact Factor: 0.991] 

15. A. Mukhopadhyay, U. Maulik and S. Bandyopadhyay, “On Biclustering of Gene Expression Data”, Current Bioinformatics, Vol. 5, No. 3, pp. 204-216, 2010. [Impact Factor: 0.54] 

16. U. Biswas, A. Mukhopadhyay, U. Maulik and M. K. Naskar, “Lightpath Protection using Genetic Algorithm through Topology Mapping in WDM Optical Networks”, Journal of Optics, Vol. 39, No. 1, pp. 32-38, 2010. 

17. U. Biswas, A. Mukhopadhyay, U. Maulik and M. K. Naskar, “Multiobjective Genetic Algorithm based  Approach to Traffic Grooming in Unidirectional  SONET/WDM  Rings”,  Journal  of  Optics,  Vol.  39,  No.  3,  pp.  136-142, 2010. 

18. A. Mukhopadhyay, S. Bandyopadhyay and U. Maulik, “Multi-class Clustering  of  Cancer  Subtypes  through SVM based Ensemble of Pareto-optimal Solutions for  Gene  Marker  Identification”,  PLOS  ONE,  Vol.  5,  No.  11, 2010. [Impact Factor: 2.766] 

19. D. Chakraborti, P. Biswas, A. Mukhopadhyay, “A Genetic Algorithm based Fuzzy Goal Programming to Multiobjective Optimal Planning of Electric Power Generation Dispatch”, International journal of Computational Intelligence Research, Vol. 6, No. 4, pp. 929-937, 2010. 

20. A. Mukhopadhyay and U. Maulik, “A Multiobjective Approach  to  MR  Brain  Image  Segmentation”,  Applied Soft Computing, Vol. 11, No. 1, pp. 872-880, 2011. [Impact Factor: 3.907] 

21. B. B. Pal, D. Chakraborti, P. Biswas, A. Mukhopadhyay, “A Genetic Algorithm Based Mixed 0-1 Goal Programming Approach to Interval-valued multiobjective Bilevel Programming Problem”, International Journal of Fuzzy systems and Rough systems, Vol. 4, No. 1, pp. 71-78, 2011. 

22. U. Maulik, M. Bhattacharyya, A. Mukhopadhyay and S. Bandyopadhyay, “Identifying the Immunodeficiency Gateway Proteins in Human and their Involvement  in  MicroRNA  Regulation”,  Molecular  BioSystems,  Royal  Society of Chemistry, Vol. 7, No. 6, pp. 1842-1851, 2011. [Impact Factor: 2.759] 

23. L. Dey and A. Mukhopadhyay, “Microarray Gene Expression Data Clustering using PSO based K-means Algorithm”, International Journal of Computer Science and its Applications, Vol. 1, No. 1, pp. 232-236, 2011. 

24. B. B. Pal, D. Chakraborti, P. Biswas and A. Mukhopadhyay, “An application of genetic algorithm method for solving patrol manpower deployment problems through fuzzy goal programming in traffic management system: A case study”, International Journal of Bio-Inspired Computation, Vol. 4, No. 1, pp. 47-60, 2012. [Impact Factor: 2.266] 

25. A. Mukhopadhyay, U. Maulik and S. Bandyopadhyay, “A Novel Biclustering Approach to Association  Rule Mining for Predicting HIV-1–Human Protein Interactions”, PLOS ONE, Vol. 7, No. 4, 2012. [Impact  Factor:  2.766] 

26. A. Mukhopadhyay, U. Maulik and S. Bandyopadhyay, “Gene Expression Data Analysis using Multiobjective Clustering Improved with SVM based Ensemble”, In Silico Biology, Vol. 11, No. 1-2, pp. 19-27, 2012. 

27. A. Mukhopadhyay, S. Ray and M. De, “Detecting Protein Complexes in PPI Network: A Gene Ontology-based Multiobjective Evolutionary Approach”, Molecular BioSystems, Royal Society of Chemistry, Vol. 8, No. 11, pp. 3036-3048, 2012. [Impact Factor: 2.759] 

28. A. Mukhopadhyay, U. Maulik and S. Bandyopadhyay, “An Interactive Approach to Multiobjective Clustering of Gene Expression Patterns”, IEEE Transactions on Biomedical Engineering, Vol. 60, No. 1, pp. 35-41, 2012. [Impact Factor: 4.288] 

29. U. Maulik, A. Mukhopadhyay, and D. Chakraborty, “Gene-expression Based Cancer Subtypes Prediction through Feature Selection and Transductive SVM”,  IEEE Transactions on Biomedical Engineering,  Vol.  60,  No.  4, pp. 1111-1117, 2013. [Impact Factor: 4.288] 

30. U. Maulik, A. Mukhopadhyay, M. Bhattacharyya, L. Kaderali, B. Brors, S. Bandyopadhyay, and R. Eils, “Mining Quasi-Bicliques from HIV-1–Human Protein Interaction Network: A Multiobjective Biclustering Approach”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 10, No. 2, pp. 423-435, 2013. [Impact Factor: 2.428] 

31. A. Bhar, M. Haubrock, A. Mukhopadhyay, U. Maulik,  S. Bandyopadhyay,  and E. Wingender,  “Coexpression and Coregulation Analysis of Time-Series Gene Expression Data in Estrogen-Induced Breast Cancer Cell”, Algorithms for Molecular Biology, Vol. 8, No. 9, 2013. [Impact Factor: 1.536] 

32. A. Mukhopadhyay and U. Maulik, “An SVM-wrapped Multiobjective Evolutionary Feature Selection Approach for Identifying Cancer-MicroRNA Markers”, IEEE Transactions on NanoBioScience, Vol. 12, No. 4, pp. 275-281, 2013. [Impact Factor: 2.158] 

33. P. Biswas, B. B. Pal, A. Mukhopadhyay and D. Chakraborti, “Genetic Algorithm based Goal Programming Procedure for Solving Interval-Valued Multilevel Programming Problems”, International Journal of Advanced Computer Research, Vol. 3, No. 1(8), pp. 125-135, 2013. 

34. S. Mallik, A. Mukhopadhyay and U. Maulik, “Integrated Statistical and Rule-Mining Techniques for DNA Methylation and Gene Expression Data Analysis”, Journal of Artificial Intelligence and Soft Computing Research, Vol. 3, No. 2, 2013. 

35. B. Barman and A. Mukhopadhyay, “Neural Network-based Approaches for Modeling Metabolic Pathways through Construction of Gene Regulatory Network from Time Series Gene Expression Data”, CSI Journal of Computing, Vol. 2, No. 1, pp. 90-97, 2013. 

36. B. B. Pal, A. Mukhopadhyay, P. Biswas and S. Mukerjee, “A Priority based Fuzzy Goal Programming Method for Solving Thermal Power Generation-Dispatch Problems using Genetic Algorithm”, CSI Journal of Computing, Vol. 2, No. 1, pp. 47-56, 2013. 

37. A. Mukhopadhyay, U. Maulik, S. Bandyopadhyay and C. A. Coello Coello, “A Survey of Multi-Objective Evolutionary Algorithms for Data Mining: Part-I”,  IEEE  Transactions  on  Evolutionary  Computation,  Vol.  18, No. 1, pp. 4-19, 2014. [Impact Factor: 8.124] 

38. A. Mukhopadhyay, U. Maulik, S. Bandyopadhyay and C. A. Coello Coello, “Survey of Multi-Objective Evolutionary Algorithms for Data Mining:  Part-II”, IEEE Transactions on Evolutionary Computation, Vol.  18, No.  1,  pp. 20-35, 2014. [Impact Factor: 8.124] 

39. S. Bandyopadhyay, S. Mallik and A. Mukhopadhyay, “A Survey and Comparative Study of Statistical Tests for Identifying Differential Expression from Microarray Data”, IEEE/ACM  Transactions  on  Computational  Biology and Bioinformatics, Vol. 11, No. 1, pp. 95-115, 2014. [Impact Factor: 2.428] 

40. A. Mukhopadhyay, S. Ray and U. Maulik, “Incorporating the type and direction information in predicting novel regulatory interactions between HIV-1 and human proteins  using  a  biclustering  approach”,  BMC  Bioinformatics,  Vol. 15, No. 26, 2014. [Impact Factor: 2.213] 

41. M. Mandal and A. Mukhopadhyay, “A Graph-Theoretic Approach for Identifying Non-redundant and Relevant Gene Markers from Microarray Data Using Multiobjective Binary PSO”, PLOS ONE, Vol. 9, No. 3, e90949, 2014. [Impact Factor: 2.766] 

42. A. Mukhopadhyay and U. Maulik, “Network-based Study Reveals Potential Infection Pathways of Hepatitis-C Leading to Various Diseases”, PLOS ONE, Vol. 9, No. 4, e94029, 2014. [Impact Factor: 2.766] 

43. A. Mukhopadhyay and M. Mandal, “Identifying Non-redundant Gene Markers from Microarray Data: A Multiobjective Variable Length PSO-based Approach”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 11, No. 6, pp. 1170-1183, 2014. [Impact Factor: 2.428] 

44. A. Mukhopadhyay, “Algorithms for Mining Protein-Protein Interaction Networks”, Annals of Indian National Academy of Engineering (INAE), Vol. XII, pp. 249-256, April 2014. 

45. S. Bandyopadhyay, S. Ray, A. Mukhopadhyay and U. Maulik, “A Review of In Silico Approaches for Analysis  and Prediction of HIV-1-Human Protein-Protein Interactions”, Briefings in Bioinformatics, Vol. 16, No. 5, pp. 830-851, doi: 10.1093/bib/bbu041, 2015. [Impact Factor: 6.302] 

46. M. Mandal and A. Mukhopadhyay, “A Novel PSO-based Graph-Theoretic Approach for  Identifying  Most  Relevant and Non-redundant Gene Markers from Gene Expression  Data”, International Journal of Parallel, Emergent and Distributed Systems, Vol. 30, No. 3, pp. 175-192, 2015. 

47. S. Mallik, A. Mukhopadhyay and U. Maulik, “RANWAR: Rank-Based Weighted Association Rule Mining from Gene Expression and Methylation Data”, IEEE Transactions on NanoBioscience, Vol. 14, No. 1, pp. 58-65, 2015. [Impact Factor: 2.158] 

48. M. Mandal, A. Mukhopadhyay and U. Maulik, “Prediction of protein subcellular localization by incorporating multiobjective PSO-based feature subset selection into the general form of Chou’s PseAAC”, Medical & Biological Engineering & Computing, Vol. 53, No. 4, pp. 331-344, 2015. [Impact Factor: 1.971] 

49. U. Maulik, S. Mallik, A. Mukhopadhyay and S. Bandyopadhyay, “Analyzing Large Gene Expression and Methylation Data Profiles using  StatBicRM: Statistical Biclustering-based Rule Mining”,  PLOS  ONE,  Vol.  10,  No. 4, pid: e0119448, 2015. [Impact Factor: 2.766] 

50. A. Mukhopadhyay, U. Maulik and S. Bandyopadhyay, “A Survey of Multiobjective Evolutionary Clustering”, ACM Computing Surveys, Vol. 47, No. 4, pp. 61:1-61:46, 2015. [Impact Factor: 5.55] 

51. M. Mandal and A. Mukhopadhyay, “A Comparative Study Among Various Statistical Tests Using Microarray Gene Expression Data”, Current Bioinformatics, Vol. 10, No. 4, pp. 377-392, 2015. [Impact Factor: 0.54] 

52. M. Mandal, J. Mondal and A. Mukhopadhyay, “A  PSO-based Approach for Pathway Marker Identification from Gene Expression Data”, IEEE Transactions of NanoBioscience, Vol. 14, No. 6, pp. 591-597, 2015. [Impact Factor: 2.158] 

53. A. Bhar, M. Haubrock, A. Mukhopadhyay and E. Wingender, “Multiobjective Triclustering of Time-Series Transcriptome Data Reveals Key Genes of Biological Processes”, BMC Bioinformatics, Vol. 16, 2015. [Impact Factor: 2.213] 

54. S. Bandyopadhyay, S. Ray, A. Mukhopadhyay and U. Maulik, “A Multiobjective Approach for Identifying Protein Complexes and Studying their Association in Multiple Disorders”, Algorithms for Molecular Biology,  Vol. 10, No. 24, 2015. [Impact Factor: 1.536] 

55. B. Barman, P. Biswas and A. Mukhopadhyay, “Comparison of gene regulatory networks using adaptive neural network and self-organising map approach  over Huh7 hepatoma cell microarray data matrix”, International Journal of Bio-Inspired Computation, Vol. 8, No. 4, 240-247, 2016. [Impact Factor: 2.266] 

56. B. Barman, R. Kanjilal and A. Mukhopadhyay, “Neuro-Fuzzy Controller  Design  to  Navigate  Unmanned  Vehicle with Construction of Traffic Rules to Avoid Obstacles”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 24, No. 3, pp. 433-449, 2016. [Impact Factor: 1.159] 

57. B. Barman and A. Mukhopadhyay, “Polynomial equation models for yeast cell-cycle time series microarray data by analysing fidelity matrices of gene expression values ”, International Journal of Bioinformatics Research and Applications, Vol. 12, No. 3, pp. 194-210, 2016. 

58. M. Mandal and A. Mukhopadhyay, “Multiobjective PSO-based rank aggregation:  Application in gene ranking  from microarray data”, Information Sciences, Vol. 385-386, pp. 55-75, 2017. [Impact Factor: 4.305] 

59. S. Chatterjee, A. Mukhopadhyay and M. Bhattacharyya, “Dependent Judgment Analysis: A  Markov Chain based Approach for Aggregating Crowdsourced Opinions”, Information Sciences, Vol. 396, pp. 83-96, 2017. [Impact Factor: 4.305] 

60. Sk Md M. Hossain, S. Ray and A.  Mukhopadhyay, “Preservation affinity in consensus modules among stages of HIV-1 progression”, BMC Bioinformatics, Vol. 18, No. 181, 2017. [Impact Factor: 2.213] 

61. R. K. Barman, A. Mukhopadhyay and S. Das, “An  improved  method  for  identification  of  small  non-coding RNAs in bacteria using support vector machine”, Scientific Reports, Vol. 7, No. 46070 Nature Partner Journals (NPJ], doi: 10.1038/srep46070, 2017. [Impact Factor: 4.122] 

62. L. Dey and A. Mukhopadhyay, “DenvInt: A Database of Protein-protein Interactions between Dengue Virus and its Hosts”, PLoS Neglected Tropical Diseases, Vol. 11, No. 10, e0005879, 2017. [Impact Factor: 4.367]

63. S. Chatterjee, A. Mukhopadhyay and M. Bhattacharyya, “Constrained Crowd Judgment Analysis”, ACM SIGWEB Newsletter, Autumn, pp. 4:1-4:3, 2017. 

64. S. Ray, Sk Md M. Hossain, L. Khatun and A. Mukhopadhyay, “A comprehensive analysis on preservation patterns of gene co-expression networks  during  Alzheimer’s  disease  progression”,  BMC  Bioinformatics,  Vol.  18, No. 1, pp. 579:1-579:21, 2017. [Impact Factor: 2.213] 

65. S. Atta, P. R. S. Mahapatra and A. Mukhopadhyay, “Solving Maximal  Covering  Location  Problem  using  Genetic Algorithm with Local Refinement”, Soft Computing, Springer, Vol. 22, No. 12, pp. 3891-3906, 2018. [Impact Factor: 2.367]

66. S. Ray, U. Maulik and A. Mukhopadhyay, “A review of computational approaches for analysis of hepatitis C virus-mediated liver diseases”, Briefings in Functional Genomics, Vol. 17, No. 6, pp. 428-440, elx040, Oxford University Press, 2018. [Impact Factor: 3.783]

67. S. Chatterjee, A. Mukhopadhyay and M. Bhattacharyya, “A Weighted Rank Aggregation Approach  towards Crowd Opinion Analysis”, Knowledge-Based Systems, Vol. 149, No. 1, pp. 47-60, 2018 [Impact Factor: 4.396]

68. S. Atta, P. R. S. Mahapatra and A. Mukhopadhyay, “Solving Tool Indexing Problem using Harmony Search Algorithm with Harmony Refinement”, Soft Computing, Springer, Vol. 23, No. 16, pp. 7407-7423, 2019 [Impact Factor: 2.367]

69. S. Atta, P. R. S. Mahapatra and A. Mukhopadhyay, “Multi-objective Uncapacitated Facility Location  Problem  with Customers’ Preferences: Pareto-based and Weighted Sum GA-based  Approaches”,  Soft Computing,  Springer, Vol. 23, No. 23, pp. 12347-12362, 2019 [Impact Factor: 2.367]

70. S. Chatterjee, A. Mukhopadhyay and M. Bhattacharyya, “A Review of Judgment Analysis Algorithms for Crowdsourced Opinions”, IEEE Transactions on Knowledge and Data Engineering, 10.1109/TKDE.2019.2904064, 2019. [Impact Factor: 2.775]

71. L. Dey and A. Mukhopadhyay, “Biclustering-based Association Rule Mining Approach for Predicting Cancer-Associated Protein Interactions”, IET Systems Biology, Vol. 13, No. 5, pp. 234-242, 2019 [Impact  Factor: 1.392] 

72. L. Dey and A. Mukhopadhyay, “A Graph-Based Approach for Finding the  Dengue  Infection  Pathways  in  Humans Using Protein-Protein Interactions”, Journal of Computational Biology, Vol. 26, DOI: 10.1089/cmb.2019.0171, 2019 [Impact factor: 1.191]
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Anirban Mukhopadhyay,
Jan 31, 2017, 9:06 AM
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