Publications

97. Kumar, A., Arora, G., Kumari, D., Changotra, H., and Chatterjee, S. Synergistic and divergent effects of dietary sugars on hepatocyte viability and steatosis. Toxicology in Vitro, (vol. 110), 106148 (2026).

96. Kumar, S., Pandey, D., and Chatterjee, S. A 3D feature fusion model integrating multi-scale MRI feature for interpretable Glioblastoma prediction. Medical & Biological Eng & Computing, (Accepted), (2025).*corresponding author

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95. Kumar, S., Agarwal, A., and Chatterjee, S. Feature learning augmented with sampling and heuristics (FLASH) improves model performance and biomarker identification. npj Systems Biology and Applications, (Accepted),(2025). *corresponding author

94. Kumar, S., Pandey, D., and Chatterjee, S. Introducing feature identification and refinement engine (FIRE) for identifying consistent and informative gene signature. Computational Biology and Chemistry, (Accepted), (2025). *corresponding author

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​​93. Ansari, S., Sarmah, D. T., Rohit Verma, R., Chandrasekar, K., Shalimar, Nayak, B., Chatterjee, S., Surjit, M., Network controllability analysis reveals the antiviral potential of Etravirine against Hepatitis E Virus infection. Msystems. 0:e00438-
25. doi.org/10.1128/msystems.00438-25 (2025).

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92. Kumar, S., Agarwal, A., Sarmah, D. T., and Chatterjee, S. konnect2prot 2.0: Integrating advanced analytical tools for deeper understanding of protein properties in a functional protein-protein interaction network. Computational and
Structural Biotechnology Journal, (vol. 27), pp. 3036–3044, (2025). *corresponding author

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91. Pandey, D., Kumar, S., Sarmah, D. T., and Chatterjee, S. TCGAimmunosurv: an R package to identify genes associated with patient survival and immune cell state transitions using TCGA and single-cell RNA-seq data. Computational Biology and Chemistry, (vol. 119), pp. 108568, (2025). *corresponding author

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90. Sharma, T., Tyagi, S., Pal, R., Kundu, J., Gupta, S K., Barik, V., Nain, V K.,Pandey, M., Dwivedi, P., Panda, B N., Kumar, Y., Nanda, R N., Chatterjee, S.,Pandey, A K., Phosphoglucomutase A mediated regulation of carbon flux is
essential for antibiotic and disease persistence in Mycobacterium tuberculosis.Msystems. 0:e00420-25. https://doi.org/10.1128/msystems.00420-25 (2025).

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89. Ghosh, S., Kumar, Verma, R., Ansari, S., Chatterjee, S., Surjit, M., Emerging RNA-centric technologies to probe RNA-protein interactions: Importance in decoding the life cycle of positive sense single strand RNA viruses and antiviral
discovery. Frontiers in Cellular and Infection Microbiology, 15:1580337.doi:10.3389/fcimb.2025.1580337 (2025).

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88. Soni, R., Soni, N., Paul, A., Tripathi, A., Chatterjee, S., & Banerjee, A. Integrated proteomics and connectivity map‐based analysis reveal compounds with a potential antiviral effect against Japanese encephalitis virus infection in a mouse model. The FEBS Journal, 292(4), 864-880 (2025).

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​87. Gupta, A., Arora, G., Bairagi, N., and Chatterjee, S. Evaluating the significance of latent tuberculosis infection treatment in high-incidence countries. Mathematical Methods in the Applied Sciences, (vol. 48), pp. 4035-4049 (2025). *corresponding author

86. Kumar, S., and Chatterjee, S. HistoSPACE: Histology-inspired spatial transcriptome prediction and characterization engine. Methods (vol. 232), pp. 107–114 (2024). *corresponding author
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85. Arora, G.,Chatterjee, P., and Chatterjee, S. Exploration of subtype-specific perturbations in breast cancer. Journal of Proteins and Proteomics,(vol. 15), pp. 329-345 (2024).*corresponding author
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84. Arora, G., Bairagi, N., and Chatterjee, S. A mathematical model to study low-dose metronomic scheduling for chemotherapy. Mathematical Biosciences, (vol. 372), pp. 109186, (2024).*corresponding author

83. Kumar, S., Sarmah, D. T., Paul, A., and Chatterjee, S. Exploration of functional relations among differentially co-expressed genes identifies regulators in glioblastoma. Computational Biology and Chemistry, (vol. 109), pp. 108024, (2024). *corresponding author

82. Tyagi, S., Sadhu, S., Sharma, T., Paul, A., Pandey, M., Nain, V., Rathore, D., Chatterjee, S., Awasthi, A., Pandey, A. VapC12 ribonuclease toxin modulates host immune response during Mycobacterium tuberculosis infection. Frontiers in immunology, 15:1302163. doi: 10.3389/fimmu.2024.1302163 (2024).

81. Halder S., Ghosh S., Das, P., Bairagi, N., and Chatterjee, S. Studying the role of random translocation of GLUT4 in cardiomyocytes on calcium oscillations. Applied Mathematical Modelling, (vol. 125) pp. 599-616, (2024).*corresponding author

80. Arora, G., Banerjee, M., Langthasa, J., Bhat, R., and Chatterjee, S. Targeting metabolic fluxes reverts metastatic transitions in ovarian cancer. iScience. (2023).*corresponding author

79. Sarmah, D. T., Paul, A., Kumar, S., Bairagi, N., and Chatterjee, S.A data-driven multilayer approach for the identification of potential therapeutic targets in non-alcoholic steatohepatitis. Physica A: Statistical Mechanics and its Applications, (Accepted). (2023).*corresponding author

78. Paul, A., Kundu, J., Chatterjee, S., A minimal mathematical model to study insulin synthesis and secretion process. Applied Mathematical Modelling, (vol. 122) pp. 456-476, (2023). *corresponding author

77. Sarmah, D. T., Paul, A., Berry, U., Surjit, M., Bairagi, N., and Chatterjee, S. BAG6 is a novel player in controlling nonalcoholic steatohepatitis: result from a comprehensive in-silico study. BioRxiv, 2023-05. (2023).*corresponding author

76. Arora, G., Langthasa, J., Banerjee, M., Bhat, R., and Chatterjee, S. Targeting metabolic fluxes reverts metastatic transitions in ovarian cancer. BioRxiv,2023-05. (2023).*corresponding author

75. Sarmah, D T., Gujjar, S., Mathapati, S., Bairagi, N., Chatterjee, S., Identification of critical autophagy-related proteins in diabetic retinopathy: A multi-dimensional computational study. Gene, (accepted). (2023).*corresponding author

74. Gupta, S., Kumawat, S., Fatima, Z., Priya., Chatterjee, S., Quantitative analysis of the bioenergetics of Mycobacterium tuberculosis along with Glyoxylate cycle as a drug target under inhibition of enzymes using Petri net. Computational Biology and Chemistry, (online), 107828, (2023).

73. Sarmah, D T., Parveen, R., Kundu, J., Chatterjee, S., Latent tuberculosis and computational biology: A less-talked affair. Progress in Biophysics and molecular biology, (Vol. 178), pp. 17-31, (2023) *corresponding author

72. Halder S., Chatterjee, S., Bistability regulates TNFR2-mediated survival and death of T-regulatory cells. Journal of Biological Physics, (Vol. 49), 95–119, (2023). *corresponding author

71. Kumar, S., Sarmah, D T., Asthana, S., Chatterjee, S., konnect2prot: A web application to explore the protein properties in a functional protein-protein interaction network. Bioinformatics, 39(1), btac815, (2023).  *corresponding author

70. Halder, S., Ghosh S., Chattopadhyay, J., Chatterjee, S., Understanding noise in cell signalling in the prospect of drug-targets. Journal of Theoretical Biology, 555, 111298, (2022). *corresponding author

69. Kumar, P., Soory, A., Mustfa, S, A., Sarmah, D, T.,Chatterjee, S., Bossis, G., Ratnaparkhi, G, S., and Srikanth, C, V., Bidirectional regulation between AP-1 and SUMO genes modulates inflammatory signalling during Salmonella Typhimurium infection. Journal of Cell Science 135 (16): jcs260096, (2022).

68. Paul, A., Das, P, N., Chatterjee, S., A minimal model of glucose-stimulated insulin secretion process explores factors responsible for the development of type 2 diabetes. Applied Mathematical Modelling, (Vol. 108), pp. 408-426, (2022).  *corresponding author

67. Paul, A., Azhar, S., Das, P, N., Bairagi, N., Chatterjee, S., Elucidating the metabolic characteristics of pancreatic β-cells from patients with type 2 diabetes (T2D) using a genome-scale metabolic modeling. Computers in Biology and Medicine. (vol. 144) 105365, (2022).  *corresponding author

66. Paul, A., Kadnur, H B., Ray, A, Chatterjee, S., Wig, N., Seroprevalence and attainment of herd immunity against SARS CoV‐2: A modelling study. J Family Medicine and Primary Care (vol. 10 (11)), 4030-4035, (2021).

65. Halder S., Ghosh S., Chattopadhyay, J., Chatterjee, S., Bistability in cell signalling and its significance in identifying potential drug targets. Bioinformatics, (vol. 37(22)), pp. 4146-416,  (2021).  *corresponding author

64. Sarmah, D T., Bairagi, N., Chatterjee, S., The interplay between DNA damage and autophagy in lung cancer: A mathematical study. Biosystems (Vol. 206), 10443, (2021).  *corresponding author

63. Arora G., Ghosh S., Chatterjee S. Understanding doxorubicin as1.    Halder S., Ghosh S., Chattopadhyay, J., Chatterjee, S., Understanding noise in cell signalling in the prospect of drug-targets. Journal of Theoretical Biology (Accepted). *corresponding authorsociated calcium remodeling during triplenegative breast cancer treatment: an in silico study. Explor Target Antitumor Ther; 2: 208- 26. https://doi.org/10.37349/etat.2021.00042 (2021). *corresponding author

62. Paul A., Kadnur, H B., Ray, A., Chatterjee, S., Wig, N., Seroprevalence and attainment of herd immunity against SARS CoV-2: A modelling study. medRxiv. (2021).

61. Gupta A., Kumar, A., Anand, R., Bairagi, N., Chatterjee, S., Genome scale metabolic model driven strategy to delineate host response to Mycobacterium tuberculosis infection. Molecular Omics (Vol.  17), pp. 296-306, (2021).  *corresponding author

60. Sarmah, D T., Bairagi, N., and Chatterjee, S., Tracing the footsteps of autophagy in computational biology. Briefings in Bioinformatics, 22(4), bbaa286, (2021). *corresponding author

59. Paul A., Anand, R., Karmakar, S., Rawat, S., Bairagi, N., Chatterjee S., Exploring gene knockout strategies to identify potential drug targets using genome-scale metabolic models. Scientific Reports. 11:213 (2021).  *corresponding author

58. Paul A., Chatterjee S., Bairagi N., COVID-19 Transmission Dynamics During the Unlock Phase and Significance of Testing. J Vaccines Vaccin. S6: 001. (2020).

57. Das, K., Srinivas, M. N., Chatterjee, S., Spatiotemporal analysis of a prey predator model with trophic interaction with harvesting. American J Math and Sci., Vol. 9, (2020).

56. Das, P. N., Kumar, A.,Bairagi, N., and Chatterjee, S., Effect of delay in transportation of extracellular glucose into cardiomyocytes under diabetic condition: A study through mathematical model. Journal of Biological Physics (Vol. 46), pp. 253-281 (2020).  *corresponding author

55. Paul, A., Chatterjee, S., & Bairagi, N. Prediction on Covid-19 epidemic for different countries: Focusing on South Asia under various precautionary measures. medRxiv. (2020). *co-corresponding author

54. Das, P. N., Halder, S., Bairagi, N., and Chatterjee, S., Delay in ATP-dependent calcium inflow may affect insulin secretion from pancreatic beta-cell. Applied Mathematical Modelling (Vol. 84), pp.202-221,  (2020).  *corresponding author

53. Gupta A., Das, P. N., Bouzeyen, R., Karmakar, S, P., Singh, R., Chatterjee, S., Restoration of cytosolic calcium inhibits Mycobacterium tuberculosis intracellular growth: Theoretical evidence and experimental observation. Journal of Theoretical Biology (Vol. 472), pp.110-123, (2019).  *corresponding author
 

52. Halder, S., Chatterjee, S., & Bairagi, N. Unravelling the Sensitivity of Two Motif Structures Under Random Perturbation. In Trends in Biomathematics: Modeling, Optimization and Computational Problems. Springer, Cham. pp. 245-263, (2018) *corresponding author

51. Anand, R., Sarmah, D T., Chatterjee, S., Extracting proteins involved in disease progression using temporally connected networks. BMC systems Biology (12:78) (2018) DOI 10.1186/s12918-018-0600-z. *corresponding author

50. Das, P., Kumar, A., Bairagi, N., and Chatterjee, S., Restoring calcium homeostasis in diabetic cardiomyocytes: An investigation through mathematical modeling. Molecular Biosystems (vol. 13), pp. 2056-2068, (2017).*corresponding author

49. Gupta, N., Duggal, S., Jailkhani, N., Chatterjee, S., Rao, K. V., & Kumar, A. Dataset to delineate changes in association between Akt1 and its interacting partners as a function of active state of Akt1 protein. Data in Brief (vol. 13), pp.187. (2017).

48. Das, P. N., Mehrotra, P., Mishra, A., Bairagi, N., Chatterjee, S., Calcium dynamics in cardiac excitatory and non-excitatory cells and the role of gap junction. Mathematical Biosciences, (vol. 289), pp. 51-68, (2017).*corresponding author  

47. Anand, R., Chatterjee, S., Tracking disease progression by searching paths in a temporal network of biological processes. Plos One (12(4)): e0176172, doi.org/10.1371/journal.pone.0176172(2017). *corresponding author

46. Anand, R., Chatterjee, S., Extracting genes involved in disease from a connected network of perturbed biological processes. Journal of Computational Biology (Vol. 24(5)), pp. 460-469,, (2017). *corresponding author

45. Mehrotra, P., Rao, K., Chatterjee, S., A mathematical model predicting host mitochondrial pyruvate transporter activity to be critical regulator ofMycobacterium tuberculosis pathogenicity. Biosystems (vol. 155), pp. 1-9, (2017).*corresponding author

44. Anand, R., Ravichandran, S., Chatterjee, S., A new method of finding groups of coexpressed genes and condition of coexpression. BMC Bioinformatics (17:486) (2016). DOI 10.1186/s12859-016-1356-3. *corresponding author

43. Das, P. N.,Pedruzzi, G., Bairagi, N., Chatterjee, S., Coupling calcium dynamics and mitochondrial bioenergetic: an in silico study to simulate cardiomyocyte dysfunction. Molecular Biosystems (vol. 12), pp. 806-817, (2016).*corresponding author

42. Pedruzzi, G., Das, P. N., Rao, K., Chatterjee, S., Understanding PGE2, LXA4 and LTB4 balance during Mycobacterium tuberculosis infection through mathematical model. Journal of Theoretical Biology (Vol. 389), pp.159-170, (2016). *corresponding author

41. Chatterjee, S., Pessani, D., Venturino, E., Harvesting strategies for ``bianchetti" and ``blue fish" in the Ligurian Sea (North Mediterranean). Appl. Math. Inf. Sci., 10, No. 3,pp.1-14, (2016).

40. Singh, V., Kaur, C., Chaudhary, VK., Rao, K., Chatterjee, S., M. tuberculosisSecretory Protein ESAT-6 Induces Metabolic Flux Perturbations to Drive Foamy Macrophage Differentiation. Scientific Reports. 5, 12906; doi: 10.1038/ srep12906 (2015). *corresponding author

39. Pedruzzi, G., Rao, K., Chatterjee, S., Mathematical model of mycobacterium-host interaction describes physiology of persistence. Journal of Theoretical Biology (Vol. 376), pp.105-117, (2015). *corresponding author

38. Biswas, S., Chatterjee, S., Chattopadhyay, J., Cannibalism may control disease in predator population: Result drawn from a model based study. Mathematical methods in the Applied Sciences(Vol 38), pp. 2272-2290 (2015).

37. Sinha, N., Negi, S., Tikoo, K., Sharma, S., Tripathi, P., Kumar, D., Rao, K V S., Chatterjee, S., Molecular signatures for obesity and associated disorders identified through partial least square regression models.BMC System Biology (2014). 8:104. *corresponding author

36. Mehrotra, P., Jamwal, S., Saquib, N, Md., Sinha, N., Siddiqui, Z., Manivel, V., Chatterjee, S., and Rao, K, V S., Pathogenicity of Mycobacterium tuberculosis is expressed by regulating metabolic thresholds of the host macrophage. PLOS Pathogens.(2014). 10 (7): e1004265. doi:10.1371/journal.ppat.1004265

35. Bhattacharya, S., Chatterjee, S., Biswas, B., Roy, P., Guerekata, G., Chattopadhyay, J., A handling tool to estimate upper bounds of environmental fluctuations.Applicable analysis. (2013) DOI: 10.1080/00036811.2013.851786.

34. Kapil, C., Hussain, T., Jairajpuri, M, A., Yogavel, M., Chatterjee, S., Sharma, A., Systematic analysis of proteomes with emphasis oninsertions in malaria parasite Plasmodium falciparum. Protein & Peptide Letters(Vol. 20), pp.1088-1097, (2013).

33. Chattopadhyay, J., Chatterjee, S., Venturino, E. Aggregation of toxin producing phytoplankton acts as a defense mechanism- a model based study.Mathematical and Computer Modelling of Dynamical System(Vol. 19), pp.159-174, (2013). *corresponding author

32. Midha, Mukul., Tikoo, K., Sinha, N., Negi, S., Verma, H N., Rao, K V S., Chatterjee, S., Manivel, V., Extracting time dependent obese-diabetic specific networks in hepatic proteome analysis.Journal of Proteome Research (Vol. 11), pp. 6030-6043, (2012). *co-corresponding author

31. Chatterjee, S.,Coupling effect of grazing pressure and nutrient enrichment on system stability. Mathematical Biosciences (Vol. 238), pp.1-11, (2012). *single author

30. Chatterjee, S., Kesh, D., Bairagi, N., How population dynamics change in presence of migratory prey and predator's preference?Ecological Complexity, (Vol. 11),pp- 53-66(2012).

29. Chatterjee, S., Kumar, D.,Unraveling the Design Principle for Motif Organization in Signaling Networks. PLos One 6(12): e28606. Doi: 10.1371/ journal. pone. 0028606 (2011).

28. Bhattacharya, S., Chatterjee, S., Chattopadhyay, J., Basu, A., On stochastic differential equations and equilibrium distribution: A conditional moment approach. Environmental and Ecological Statistics (vol. 18 (4)), pp. 687-708, (2011).

27. Chatterjee, A., Pal, S., Chatterjee, S., Bottom-up and top-down effect on toxin producing phytoplankton and its consequence on the formation of the plankton bloom. Appl. Math. Comp. (Vol. 218), pp.3387-3398, (2011).

26. Chatterjee, S., Venturino, E., On predation of symbiotic systems. AIP Conf. Proc., (Vol. 1389), pp. 1240-1243, (2011).

25. Md. Sarwar Jamal, M, S., Ravichandran, S., Chatterjee, S., Dua, R., Rao, K. V. S., Defining the antigen receptor-dependent regulatory network that induces arrest of cycling immature B-lymphocytes. BMC System Biology, 4:169, (2010).

24. Chatterjee, S., Alternative food source coupled with prey recovery enhance stability between migratory prey and their predator in the presence of disease. Nonlinear Analysis B: Real world application,(Vol. 11(5)), pp. 4415-4430, (2010). *single author

23. Das, K.,Chatterjee, S., Chattopadhyay, J., Occurrence of chaos and its possible control in a predator-prey model with density dependent disease-induced mortality on predator population. Journal of Biological Systems, (Vol. 18(2)), pp.399-435,(2010).

22. Chatterjee, S., Venturino, E. Shark-Fish interplay at different life stages. Aplimat- Journal of Applied Mathematics (Vol. 2(2)), pp. 177-188, (2009). (Accepted in the APLIMAT proceeding also-- Chatterjee, S., Venturino, E. Shark-Fish interplay at different life stages. Aplimat- 8th- International conference on Applied Mathematics, APLIMAT- 2009, Slovak University of Technology in Bratislava, pp. 567-576).

21. Chatterjee, S., Isaia, M., Venturino, E. Effects of spiders' predational delays in intensive agroecosystems. Nonlinear Analysis: Real world application (Vol. 10), pp. 3045-3058, (2009).

20. Chatterjee, S., Isaia, M., Venturino, E. Spiders as a biological controllers in the Langa Astigiana vineyards. Journal of Theoretical Biology,(Vol. 258), pp. 352-362, (2009). *corresponding author

19. Chatterjee, S., Venturino, E., Chakraborty, S., Chattopadhyay, J., A simple mathematical model for seasonal planktonic blooms. Mathematical Methods in the Applied Sciences, (Vol. 32), pp.1738-1750,(2009).

18. Pal, S.,Chatterjee, S., Das, K., Chattopadhyay, J., Role of competition in phytoplankton population for the occurrence and control of plankton bloom in the presence of environmental fluctuations. Ecological Modelling (Vol. 220), pp. 96-110, (2009).

17. Das, K.,Chatterjee, S., Chattopadhyay, J., Disease in prey population and body size of intermediate predator reduce the prevalence of chaos- conclusion drawn from Hastings-Powell model. Ecological Complexity,(Vol. 6), pp. 363-374, (2009).

16. Chatterjee, S., Kundu, K., Pal, S., Chattopadhyay, J., Venturino, E. Comparing two new ecoepidemic models of the Salton Sea. MATHMOD 2009, the 6th Vienna International Conference on Mathematical Modelling, Vienna, Austria, February 11th – 13th, 2009.

15. Venturino, E.,Isaia, M., Bona, F., Chatterjee, S., Badino, G. Biological controls of intensive agro-ecosystems: wanderer spiders in the Langa Astigiana. Ecological Complexity, (Vol. 5(2)),pp157-164, (2008).

14. Chatterjee, S., Pal, S.,Chattopadhyay, J. Role of migratory birds under environmental fluctuation- A mathematical study. Journal of Biological Systems, (Vol. 16 (1)), pp. 81-106, (2008). *corresponding author

13. Chattopadhyay, J., Chatterjee, S., Venturino, E. Patchy agglomeration as a transition from monospecies to recurrent plankton blooms. Journal of Theoretical Biology,(Vol. 253), pp. 289-295, (2008).

12. Bandyopadhyay, M., Chatterjee, S., Chakraborty, S., Chattopadhyay, J., Density dependent predator death prevalence chaos in a tri-trophic food chain model. Nonlinear Analysis: Modelling and Control, (Vol. 13), pp. 305-324, (2008).

11. Chatterjee, S., Isaia, M., Bona, F., Badino, G., Venturino, E. Modelling environmental influences on wanderer spiders in the Langhe region (Piemonte-NW Italy). Journal of Numerical Analysis, Industrial and Applied Mathematics (Vol. 3), pp. 193-209, (2008).

10. Bairagi, N., Chatterjee, S., Chattopadhyay, J. Variability in the secretion of CRH, ACTH & Cortisol and understandability of the HPA axis dynamics- a mathematical study based on clinical evidences. Mathematical Medicine and Biology: A journal of IMA, (Vol. 25), pp. 37-63, (2008).

9. Das, K.,Chatterjee, S., Chattopadhyay, J., Dynamics of nutrient-phytoplankton interaction in the presence of viral infection and periodic nutrient input. Math. Model. Nat. Phenom.(Vol. 3 (3)), pp. 149-169,(2008).

8. Chatterjee, S., Venturino, E. The paradox of enrichment in ratio--dependent ecoepidemic models. NUMERICAL ANALYSIS AND APPLIED MATHEMATICS: International Conference on Numerical Analysis and Applied Mathematics 2008, Kos, Greece; AIP Conf. Proc., Vol. 1048(1), pp. 974-977 (2008).

7. Chakraborty, S., Chatterjee, S., Venturino, E., Chattopadhyay, J. Recurring plankton bloom dynamics modeled via toxin producing phytoplankton. Journal of Biological Physics, (Vol. 33(4)), pp. 271-290, (2007).

6. Chatterjee, S. and Chattopadhyay, J. Role of migratory bird population in a simple eco-epidemiological model. Mathematical and Computer Modelling of Dynamical System. (Vol. 13 (1)), pp. 99-114, (2007).

5. Chatterjee, S., Das, K., Chattopadhyay, J. Time delay factor can be used as a key factor for preventing the outbreak of a disease- results drawn from a mathematical study of a one season eco-epidemiological model. Nonlinear Analysis: Real World application (Vol. 8 (5)), pp. 1472-1493, (2007).

4. Pal, S.,Chatterjee, S., Chattopadhyay, J. Role of toxin and nutrient for the occurrence and termination of plankton bloom - Results drawn from field observations and a mathematical model. Biosystems. (Vol. 90(1)), pp. 87-100, (2007).

3. Chatterjee, S., Kundu, K.,Chattopadhyay, J. Role of horizontal incidence in the occurrence and control of chaos in an eco-epidemiological system. Mathematical Medicine and Biology: A Journal of IMA. (Vol. 24(3)), pp. 301-326, (2007).

2. Chatterjee, S., Ghosh, A, K., Chattopadhyay, J. Controlling disease in migratory bird population- A probable solution through mathematical study. Dynamical system: An International Journal. (Vol. 21 (3)), pp. 265-288, (2006).

1. Chatterjee, S., Bandyopadhyay,M. Chattopadhyay, J. Proper predation makes the system disease free - Conclusion drawn from an eco-epidemiological model. Journal of Biological Systems. (Vol. 14(4)), pp. 599-616, (2006).