biblio

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2017
V. ; Maralingannavar, Parmar, D., Pant, T., Gadgil, C., Panchagnula, V., and Gadgil, M., “CHO Cells Adapted to Inorganic Phosphate Limitation Show Higher Growth and Higher Pyruvate Carboxylase Flux in Phosphate Replete Conditions”, Biotechnology progress, vol. 33, no. 3, pp. 749-758, 2017.
2018
V. Maralingannavar, Parmar, D., Pant, T., Gadgil, C., Panchagnula, V., and Gadgil, M., “Differential responses of CHO cells adapted to limitation of inorganic phosphate, glucose or glutamine”, in 255th National Meeting and Exposition of the American-Chemical-Society (ACS) - Nexus of Food, Energy, and Water, New Orleans, LA, 2018.
2019
, Gadgil, C., Mote, R. D., Rajan, R., and Subramanyam, D., “Clathrin-mediated endocytosis regulates a balance between opposing signals to maintain the pluripotent state of embryonic stem cells”, Stem Cell Reports, vol. 12, no. 1, pp. 152-164, 2019.
B. K. Kuntal, Gadgil, C., and Mande, S. S., “Web-gLV: a web based platform for lotka-volterra based modeling and simulation of microbial populations”, Frontiers in Microbiology, vol. 10, p. 288, 2019.
2021
P. Dnyane and Gadgil, C., “Boolean model for melanogenesis”, Physical Biology, vol. 18, no. 2, p. 026004, 2021.
B. K. Kuntal, Gadgil, C., and Mande, S. S., “Web-gLV: a web based platform for lotka-volterra based modeling and simulation of microbial populations (vol 10, 288, 2019)”, Frontiers in Microbiology, vol. 11, p. 605308, 2021.
2022
K. Culhane, Gupte, T., Madhugiri, I., Gadgil, C., and Sivaramakrishnan, S., “Kinetic model of GPCR-G protein interactions reveals allokairic modulation of signaling”, Biophysical Journal, vol. 121, no. 3, p. 122, 2022.
F. Sultan, Basu, R., Murthy, D., Kochar, M., Attri, K. S., Aggarwal, A., Kumari, P., Dnyane, P., Tanwar, J., Motiani, R. K., Singh, A., Gadgil, C., Bhavesh, N. Sarovar, Singh, P. K., Natarajan, V. T., and Gokhale, R. S., “Temporal analysis of melanogenesis identifies fatty acid metabolism as key skin pigment regulator”, Plos Biology, vol. 20, no. 5, p. e3001634, 2022.
2024
U. Pandey, Madhugiri, I., Gadgil, C., and Gadgil, M., “Leveraging machine learning to dissect role of combinations of amino acids in modulating the effect of zinc on mammalian cell growth”, BIOTECHNOLOGY PROGRESS, vol. 40, 2024.