@article { ISI:000363023500010,
	title = {Temporal protein expression pattern in intracellular signalling cascade during T-cell activation: a computational study},
	journal = {Journal of Biosciences},
	volume = {40},
	number = {4},
	year = {2015},
	month = {OCT},
	pages = {769-789},
	publisher = {INDIAN ACAD SCIENCES},
	address = {C V RAMAN AVENUE, SADASHIVANAGAR, P B \#8005, BANGALORE 560 080, INDIA},
	abstract = {<p>Various T-cell co-receptor molecules and calcium channel CRAC play a pivotal role in the maintenance of cell{\textquoteright}s functional responses by regulating the production of effector molecules (mostly cytokines) that aids in immune clearance and also maintaining the cell in a functionally active state. Any defect in these co-receptor signalling pathways may lead to an altered expression pattern of the effector molecules. To study the propagation of such defects with time and their effect on the intracellular protein expression patterns, a comprehensive and largest pathway map of T-cell activation network is reconstructed manually. The entire pathway reactions are then translated using logical equations and simulated using the published time series microarray expression data as inputs. After validating the model, the effect of in silico knock down of co-receptor molecules on the expression patterns of their downstream proteins is studied and simultaneously the changes in the phenotypic behaviours of the T-cell population are predicted, which shows significant variations among the proteins expression and the signalling routes through which the response is propagated in the cytoplasm. This integrative computational approach serves as a valuable technique to study the changes in protein expression patterns and helps to predict variations in the cellular behaviour.</p>},
	keywords = {Boolean model, co-receptors and CRAC channel, synchronous and asynchronous simulation, T-cell signalling pathway, temporal gene expression patterns},
	issn = {0250-5991},
	doi = {10.1007/s12038-015-9561-1},
	author = {Ganguli, Piyali and Chowdhury, Saikat and Bhowmick, Rupa and Sarkar, Ram Rup}
}
@article {47048,
	title = {Boolean model for melanogenesis},
	journal = {Physical Biology},
	volume = {18},
	year = {2021},
	month = {MAR},
	pages = {026004},
	type = {Article},
	abstract = {<p>Melanogenesis is a highly regulated process through which the pigment melanin is produced in skin cells. Irregularities in the molecular events that govern the process of skin pigmentation can cause disorders like vitiligo. In order to understand the biology of disease progression, it is important to have an in depth understanding of intracellular events. Mathematical models provide an integrated view of intracellular signalling. There are very few models to date that incorporate intracellular processes relevant to melanogenesis and only one to our knowledge that simulates the dynamics of response to varying levels of input. Here, we report the formulation of the largest Boolean model (265 nodes) for melanogenesis to date. The model was built on the basis of a detailed interaction network graph published by Raghunath et al. Through additional manual curation of the reported interactions, we converted the graph into a set of Boolean rules, following the procedure of the first Boolean model (62 nodes) for melanogenesis published by Lee et al. Simulations show that the predicted response to varying UV levels for most of the nodes is similar to the predictions of the existing model. The greater complexity allows investigation of the sensitivity of melanin to additional nodes. We carried out perturbation analysis of the network through node deletion and constitutive activation to identify sensitivity of outcomes, and compared the nodes identified as sensitive to previous reports.</p>
},
	keywords = {Boolean model, melanogenesis, Signal transduction},
	issn = {1478-3967},
	doi = {10.1088/1478-3975/abd3dd},
	author = {Dnyane, Pooja and Gadgil, Chetan}
}
