Research Statement
Through mathematical modelling and data analysis, my research work is dedicated to understand biological problems. I use small conceptual models as well as large scale models to understand relation between processes (variables) and the factors (parameters) driving those processes. I build different mathematical models using different kinds of differential equations like ordinary differential equations (ODEs), delay differential equations (DDEs) and stochastic differential equations (SDEs). To analyze those models I use different mathematical tools from linear algebra, classical algebra and differential equations with computer simulation (numerical analysis) using softwares like Matlab, Maple, SPlus and XPPAUTO. I also have experience of handling large volumes of highthroughput data (from microarray and massspectrometer experiments). To analyze those large volume data, I use systems biology techniques (like network analysis) using softwares like cytoscape, Simca and other online packages like KEGG pathway, PANTHER and STRING data set. I am also developing tools (using Matlab with my own algorithm) that can be used to handle large volume of highthroughput data and to estimate parameters for the proposed model.
In terms of large scal data analysis, one of our major research thrust is to build dynamical network to capture disease progression trajectories and to identify disease state specific regulatory nodes. In another direction, we used genome scale metabolic models to identify choke points responsible for causing disease state and use this information for restoration to normal state. The tools for such studies includes differential equation, graph theory, dynamical theorem like chaos theory, numerical analysis and tools from physics like percolation and statistical modeling that includes machine learning. In terms of small scale model, we are focusing in two areas. First area focused in biulding ODE based models to understand the hostpathogen interaction in presence of M.tb. We are looking at how pathogen is manipulating host machinary for its survival and then using models we are hypothesing on possible rstoration mechanisms. In the second area we are exploring the role of calcium signalling in maintaining normal function of cardiomyocytes. We are looking at possible restoration meachism for normal cardiac functioning in disease conditions like diabetes causing calcium overloading etc.
Simultaneously, we are also involved in the identification of potential drug targets for drug discovery pipeline set in DDRC. We use available systems biology tools like network analysis, clustering etc., as well as develop our own computational tools for target identification from big data. In another DDRC project, we are also working on the development of diagnostic and prognostic models using machinelearning (ML) algorithms.
Journal editorial board member:
 The Scientific World Journal.
Journal referee
 “Journal of theoretical biology” by Elsevier.
 “Nonlinear Analysis series B: Real world application” by Elsevier.
 “Ecological Complexity” by Elsevier.
 "Mathematical Methods in the Applied Science" by John Wiley and sons.
 “Frontiers of Environmental Science & Engineering in China” by Springer.
 “Ecological Modelling”by Elsevier.
 “International Journal of Biomathematics” by worldscientific.
 “Journal of Biological systems” by worldscientific.
 “Nonlinear studies: The international journal”.
 “Journal of medical plants research” by Academic journals.
 “Bulletin of Calcutta Mathematical Society” by CMS.
 “EURASIP Journal on Bioinformatics and Systems Biology” by springer open journal.
 “Mathematics and computers in simulation” by Elsevier.
 “International Journal of Bifurcation and Chaos” by worldscientific.
 “Nonlinear Analysis: Modelling and Control” by Lithuanian Association of Nonlinear Analysts (LANA).
 "Advances in Difference equations" by Springer.

"Ain Shams Engineering Journal" by Elsevier.
Academic Society member:
 American Mathematical Society (Affiliated member).
 Biomathematical society of India (member).
Review assignments as faculty
 Associate faculty member in F1000
 Reviewer in ‘Mathematical Reviews’ published by the American Mathematical society, (Reviewer Code: 59077)
2018:
51. Anand, R., Sarmah, D T., Chatterjee, S., Extracting proteins involved in disease progression using temporally connected networks. BMC systems Biology (accepted) (2018). *corresponding author
2017:
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. 20562068, (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 nonexcitatory cells and the role of gap junction. Mathematical Biosciences, (vol. 289), pp. 5168, (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. 460469,, (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. 19, (2017).*corresponding author
2016 (Total 4):
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/s1285901613563. *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. 806817, (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.159170, (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.114, (2016).
2015(Total 3):
40. Singh, V., Kaur, C., Chaudhary, VK., Rao, K., Chatterjee, S., M. tuberculosisSecretory Protein ESAT6 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 mycobacteriumhost interaction describes physiology of persistence. Journal of Theoretical Biology (Vol. 376), pp.105117, (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. 22722290 (2015).
2014 (Total 2):
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
2013: (Total 3)
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.10881097, (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.159174, (2013). *corresponding author
2012: (Total 3)
32. Midha, Mukul., Tikoo, K., Sinha, N., Negi, S., Verma, H N., Rao, K V S., Chatterjee, S., Manivel, V., Extracting time dependent obesediabetic specific networks in hepatic proteome analysis.Journal of Proteome Research (Vol. 11), pp. 60306043, (2012). *cocorresponding author
31. Chatterjee, S.,Coupling effect of grazing pressure and nutrient enrichment on system stability. Mathematical Biosciences (Vol. 238), pp.111, (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 5366(2012).
2011: (Total 4)
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. 687708, (2011).
27. Chatterjee, A., Pal, S., Chatterjee, S., Bottomup and topdown effect on toxin producing phytoplankton and its consequence on the formation of the plankton bloom. Appl. Math. Comp. (Vol. 218), pp.33873398, (2011).
26. Chatterjee, S., Venturino, E., On predation of symbiotic systems. AIP Conf. Proc., (Vol. 1389), pp. 12401243, (2011).
2010: (Total 3)
25. Md. Sarwar Jamal, M, S., Ravichandran, S., Chatterjee, S., Dua, R., Rao, K. V. S., Defining the antigen receptordependent regulatory network that induces arrest of cycling immature Blymphocytes. 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. 44154430, (2010). *single author
23. Das, K.,Chatterjee, S., Chattopadhyay, J., Occurrence of chaos and its possible control in a predatorprey model with density dependent diseaseinduced mortality on predator population. Journal of Biological Systems, (Vol. 18(2)), pp.399435,(2010).
2009: (Total 7)
22. Chatterjee, S., Venturino, E. SharkFish interplay at different life stages. Aplimat Journal of Applied Mathematics (Vol. 2(2)), pp. 177188, (2009). (Accepted in the APLIMAT proceeding also Chatterjee, S., Venturino, E. SharkFish interplay at different life stages. Aplimat 8^{th} International conference on Applied Mathematics, APLIMAT 2009, Slovak University of Technology in Bratislava, pp. 567576).
21. Chatterjee, S., Isaia, M., Venturino, E. Effects of spiders' predational delays in intensive agroecosystems. Nonlinear Analysis: Real world application (Vol. 10), pp. 30453058, (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. 352362, (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.17381750,(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. 96110, (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 HastingsPowell model. Ecological Complexity,(Vol. 6), pp. 363374, (2009).
16. Chatterjee, S., Kundu, K., Pal, S., Chattopadhyay, J., Venturino, E. Comparing two new ecoepidemic models of the Salton Sea. MATHMOD 2009, the 6^{th} Vienna International Conference on Mathematical Modelling, Vienna, Austria, February 11^{th} – 13^{th}, 2009.
2008: (Total 8)
15. Venturino, E.,Isaia, M., Bona, F., Chatterjee, S., Badino, G. Biological controls of intensive agroecosystems: wanderer spiders in the Langa Astigiana. Ecological Complexity, (Vol. 5(2)),pp157164, (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. 81106, (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. 289295, (2008).
12. Bandyopadhyay, M., Chatterjee, S., Chakraborty, S., Chattopadhyay, J., Density dependent predator death prevalence chaos in a tritrophic food chain model. Nonlinear Analysis: Modelling and Control, (Vol. 13), pp. 305324, (2008).
11. Chatterjee, S., Isaia, M., Bona, F., Badino, G., Venturino, E. Modelling environmental influences on wanderer spiders in the Langhe region (PiemonteNW Italy). Journal of Numerical Analysis, Industrial and Applied Mathematics (Vol. 3), pp. 193209, (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. 3763, (2008).
9. Das, K.,Chatterjee, S., Chattopadhyay, J., Dynamics of nutrientphytoplankton interaction in the presence of viral infection and periodic nutrient input. Math. Model. Nat. Phenom.(Vol. 3 (3)), pp. 149169,(2008).
8. Chatterjee, S., Venturino, E. The paradox of enrichment in ratiodependent 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. 974977 (2008).
2007: (Total 5)
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. 271290, (2007).
6. Chatterjee, S. and Chattopadhyay, J. Role of migratory bird population in a simple ecoepidemiological model. Mathematical and Computer Modelling of Dynamical System. (Vol. 13 (1)), pp. 99114, (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 ecoepidemiological model. Nonlinear Analysis: Real World application (Vol. 8 (5)), pp. 14721493, (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. 87100, (2007).
3. Chatterjee, S., Kundu, K.,Chattopadhyay, J. Role of horizontal incidence in the occurrence and control of chaos in an ecoepidemiological system. Mathematical Medicine and Biology: A Journal of IMA. (Vol. 24(3)), pp. 301326, (2007).
2006: (Total 2)
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. 265288, (2006).
1. Chatterjee, S., Bandyopadhyay,M. Chattopadhyay, J. Proper predation makes the system disease free  Conclusion drawn from an ecoepidemiological model. Journal of Biological Systems. (Vol. 14(4)), pp. 599616, (2006).
1. Kumar, D., Chatterjee, S., Mathematics and Biology: The Growing Synergy. Math Unlimited: Essays in Mathematics, Ed: H.N. Ramaswamy, R. Sujatha, C.S. Yogananda, published by Science publishers, Taylor and Francis group(2012). *corresponding author
2. Jailkhani, N., Chatterjee, S., Rao, K., Systems Biology: Evolution of a new discipline. Science and culture. (Vol. 78), pp. 100105, (2012).
3. Caccherano,E., Chatterjee S., Giani, L C., Grande, L., Romano, T., Visconti, G., Venturino, E., Models of symbiotic associations in food chains. published by NOVA Science publishers, (In press).
4. Roy, P.K., Mondol, J., Chatterjee, S., Vertical incidence increases virulence in pathogens: A model based study. Electrical Engineering and Applied Computing. Lecture Notes in Electrical Engineering. (Vol. 90), pp. 661673, (2011).
5. Chatterjee, S., Migratory birds and spread of disease A mathematical model based study, VDMVerlag (Germany). (ISBN13:9783639268256). [full book].
6. Bairagi, N., Pal, S., Chatterjee, S., Chattopadhyay, J. A qualitative study on nutrient, nontoxic phytoplankton, toxic phytoplankton and zooplankton interaction in open marine system. Aspects of Mathematical Biology, Birkhauser, eds, Hosking, R, J., and Venturino, E., Mathematics and Biosciences in Interaction, pp. 4168, (2008).
1. Diary No.: 52951/2014CO/SW
Title: Computer Software for Drug Targeting
Authors: Dr. Samrat Chatterjee  Dr. Rajat Anand
IPR Protection Status: Copyright protection opted [Software Category]
Advantageous Feature(s):Algorithm uses less number of parameters than existing software
Application(s):Software can be used to extract drug targets from biological/Clinical data based on proteinprotein interaction
Subscription: THSTI
2. Diary No.: 5662/2017CO/SW
Title: An Artificial Intelligence Algorithm for Predicting Susceptibility to Type 2 Diabetes
Authors: Dr. Samrat Chatterjee, Rajat Anand, Dr. Kanury V.S. Rao, Dr. Ravi Chandra Beeram
IPR Protection Status: Copyright protection opted[Software Category]
Advantageous Feature(s):Predict their future diabetic state with high accuracy
Application(s):Predict susceptibility to Type 2 Diabetes
Subscription: THSTI
3. Indian Patent number: 201711041969
Title of the technology: Method of predict diabetes outcome susceptibility
Inventors: Dr. Samrat Chatterjee , Dr. Kanury Venkata Subba Rao, Dr. Rajat Anand, Mr. Shivam Kumar, Dr. Yashwant Kumar and Dr. Ravi Chandra Beeram
Field of invention: The present invention relates to the field of biotechnology particularly relates to prediction of type2 diabetes in the general population.
Owner(s): THSTI, RPBL
 "Mathematical approaches to understand host pathogen crosstalk in Mycobacterial pathogenesis". (Granted by SERB, DST) for three years from 2015. (Principal Investigator) Completed
 "Unravelling the architecture of biological networks to identify points of sensitivity under perturbation". (Granted by DBT) for three years from 2016. (Principal investigator) in collaboration with Indian Statistical Institute.
 "Use of model trajectories to understand the regulatory mechanisms underlying metabolic diseases". (Granted by CSIR) for three years from 2016. (Principal investigator)
 "Improving the resolution of proteinprotein interaction (PPI) network". (Granted by DBT) for three years from Jan, 2018. (Principal investigator)
 Gold Medal in M. Sc– 2003
 NBHM Research award (for PhD research)– 2003
 Selected as young Indian researcher under MIUR project of Italian Government– 2006, 2007.
 Autobiography is published in 2010 Edition of Who's Who in the World.
External student:
Dr. Phonindra Nath Das: PhD degree awarded from Jadavpur University2018 (Joint Supervision with Prof. Nandadulal Bairagi, Jadavpur University).
MS. SONALI POREY KARMAKAR
TECHNICAL OFFICERI
DR. RAJAT ANAND
RESEARCH ASSOCIATE
MR. DIPANKA TANU SARMAH
JUNIOR RESEARCH FELLOW
MR. PRADEEP KUMAR
TECHNICAL OFFICERI
MR. SURENDER RAWAT
JUNIOR RESEARCH FELLOW
MS. POOJA
JUNIOR RESEARCH FELLOW
MR. KRISHAN
PROJECT ASSISTANT
MR. ABHIJIT PAUL
PH.D STUDENT
MR. SUVANKAR HALDER
PH.D STUDENT
MR. SHIVAM KUMAR
JUNIOR RESEARCH FELLOW
DR. SUMANA GHOSH
RESEARCH ASSOCIATE