@article {PACHFULE,
	title = {Realistic host-vector transmission model for describing malaria prevalence pattern},
	journal = {Bulletin of Mathematical Biology},
	volume = {75},
	number = {12},
	year = {2013},
	month = {DEC},
	pages = {2499-2528},
	publisher = {SPRINGER},
	address = {233 SPRING ST, NEW YORK, NY 10013 USA},
	abstract = {<p>Malaria continues to be a major public health concern all over the world even after effective control policies have been employed, and considerable understanding of the disease biology have been attained, from both the experimental and modelling perspective. Interactions between different general and local processes, such as dependence on age and immunity of the human host, variations of temperature and rainfall in tropical and sub-tropical areas, and continued presence of asymptomatic infections, regulate the host-vector interactions, and are responsible for the continuing disease prevalence pattern. In this paper, a general mathematical model of malaria transmission is developed considering short and long-term age-dependent immunity of human host and its interaction with pathogen-infected mosquito vector. The model is studied analytically and numerically to understand the role of different parameters related to mosquitoes and humans. To validate the model with a disease prevalence pattern in a particular region, real epidemiological data from the north-eastern part of India was used, and the effect of seasonal variation in mosquito density was modelled based on local climactic data. The model developed based on general features of host-vector interactions, and modified simply incorporating local environmental factors with minimal changes, can successfully explain the disease transmission process in the region. This provides a general approach toward modelling malaria that can be adapted to control future outbreaks of malaria.</p>},
	keywords = {Basic reproduction number, Environmental effects, Malaria model, Prevalence data, Stability analysis},
	issn = {0092-8240},
	doi = {10.1007/s11538-013-9905-7},
	author = {Mandal, Sandip and Sinha, Somdatta and Sarkar, Ram Rup}
}
@article {43789,
	title = {Revealing the mystery of metabolic adaptations using a genome scale model of Leishmania infantum},
	journal = {Scientific Reports},
	volume = {7},
	year = {2017},
	month = {AUG},
	type = {Article},
	abstract = {Human macrophage phagolysosome and sandfly midgut provide antagonistic ecological niches for Leishmania parasites to survive and proliferate. Parasites optimize their metabolism to utilize the available inadequate resources by adapting to those environments. Lately, a number of metabolomics studies have revived the interest to understand metabolic strategies utilized by the Leishmania parasite for optimal survival within its hosts. For the first time, we propose a reconstructed genome-scale metabolic model for Leishmania infantum JPCM5, the analyses of which not only captures observations reported by metabolomics studies in other Leishmania species but also divulges novel features of the L. infantum metabolome. Our results indicate that Leishmania metabolism is organized in such a way that the parasite can select appropriate alternatives to compensate for limited external substrates. A dynamic non-essential amino acid motif exists within the network that promotes a restricted redistribution of resources to yield required essential metabolites. Further, subcellular compartments regulate this metabolic re-routing by reinforcing the physiological coupling of specific reactions. This unique metabolic organization is robust against accidental errors and provides a wide array of choices for the parasite to achieve optimal survival.},
	doi = {10.1038/s41598-017-10743-x},
	author = {Subramanian, Abhishek and Sarkar, Ram Rup}
}
