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Your search keyword '"Maulik P."' showing total 10 results
Start Over Author "Maulik P." Publication Type Books
10 results on '"Maulik P."'

1. Contributors

Author

Abrams, Gary M., primary, Albers, Gregory W., additional, Amans, Matthew R., additional, Aminoff, Michael J., additional, Batla, Amit, additional, Betjemann, John P., additional, Camilleri, Michael, additional, Chen, Robert, additional, Christine, Chadwick W., additional, Coleman, Kyle J., additional, Davies-Jones, G.A.B., additional, DeAngelis, Lisa M., additional, Dhand, Amar, additional, Dillon, William P., additional, Douglas, Vanja C., additional, Fox, Christine, additional, Furman, Joseph M., additional, Gelb, Douglas J., additional, Gladstone, David J., additional, Glynn, Simon M., additional, Goodin, Douglas S., additional, Goodman, Brent P., additional, Greenlee, John E., additional, Guterman, Elan, additional, Halabi, Cathra, additional, Hallett, Mark, additional, Halperin, John J., additional, Harris, Shelby, additional, Hemphill, J. Claude, additional, Hurko, Orest, additional, Irani, Sarosh R., additional, Jo, Jasmin, additional, Josephson, S. Andrew, additional, Kaley, Thomas J., additional, Kim, Anthony S., additional, Ko, Nerissa U., additional, Koshy, Anita A., additional, Kraler, Lironn, additional, Krumholz, Allan, additional, Leonard, John M., additional, Levin, Morris, additional, Manno, Edward M., additional, Mastaglia, Frank L., additional, Maurer, Carine W., additional, McCall, Andrew A., additional, Messing, Robert O., additional, Miravalle, Augusto, additional, Monderer, Renee, additional, Morren, John A., additional, Muccilli, Alexandra D., additional, Muir, Ryan T., additional, Murphy, Olwen C., additional, Nash, Kendall, additional, Ooi, Winnie W., additional, Pal, Pramod K., additional, Panicker, Jalesh N., additional, Parent, Jack M., additional, Peluso, Michael J., additional, Perfect, John R., additional, Peyvandi, Shabnam, additional, Pfeiffer, Ronald F., additional, Phillips, Steven M., additional, Poncelet, Ann Noelle, additional, Prasad, Sashank, additional, Prasad, Shweta, additional, Probasco, John C., additional, Purdy, Kaylynn, additional, Rabinstein, Alejandro A., additional, Ralph, Jeffrey W., additional, Ramachandran, Prashanth S., additional, Roos, Karen L., additional, Rose-Innes, Andrew P., additional, Safarpour, Delaram, additional, Schiff, David, additional, Schipper, Hyman M., additional, Shah, Maulik P., additional, Sharzehi, Kaveh, additional, Shaw, Pamela J., additional, Spudich, Serena, additional, Srinivasan, Jayashri, additional, Stern, Barney J., additional, Sun, Chung-Huan Johnny, additional, Sussman, Jon D., additional, Thorpy, Michael, additional, Verber, Nick S., additional, VoduŠek, David B., additional, Weissenborn, Karin, additional, Williams, Linda S., additional, Wilson, Michael R., additional, and Zochodne, Douglas W., additional

Published
2021
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3. Assembly, Annotation, and Comparative Genomics in PATRIC, the All Bacterial Bioinformatics Resource Center

Author

Wattam, Alice R., primary, Brettin, Thomas, additional, Davis, James J., additional, Gerdes, Svetlana, additional, Kenyon, Ronald, additional, Machi, Dustin, additional, Mao, Chunhong, additional, Olson, Robert, additional, Overbeek, Ross, additional, Pusch, Gordon D., additional, Shukla, Maulik P., additional, Stevens, Rick, additional, Vonstein, Veronika, additional, Warren, Andrew, additional, Xia, Fangfang, additional, and Yoo, Hyunseung, additional

Published
2017
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8. Pseudorandom Pattern Generation by a 4-Neighborhood Cellular Automata Based on a Probabilistic Analysis.

Author

Seth, Abhishek, Bandyopadhyay, S., and Maulik, U.

Subjects
RANDOM number generators, CELLULAR automata, MATHEMATICAL programming, SHIFT registers, COMPUTERS
Abstract

In this article, we construct a random number generator using a one dimensional, nonuniform 4-Neighborhood Cellular Automata (4NCA). A probabilistic analysis of CA rules has been done to select the appropriate rules for 4NCA random number generator (RNG). A comparison is made between the pseudo random patterns generated by using the proposed CA RNGs with those obtained using a recent Cellular Programming (CP) evolved CA RNGs. The results show that our approach outperforms CP both in terms of average time taken to evolve CA rules and in terms of quality of pseudo random patterns generated. The proposed approach is also shown to be better than the common generators such as Shift Register, Congruential Generator and Lagged Fibonacci Generator. [ABSTRACT FROM AUTHOR]

Published
2008

9. Role of Receptor Tyrosine Kinases in Lung Cancer.

Author

Walker, John M., Driscoll, Barbara, Maulik, Gautam, Kijima, Takashi, and Salgia, Ravi

Abstract

Lung cancer cells express receptor tyrosine kinases (RTKs) that may be important targets for therapies. RTKs are proto-oncogenes, which are key regulators for cell growth, differentiation, survival, or motility. More than 50 RTKs, in both lung and other tissues, have been identified (1). The receptors contain an N-terminal extracellular ligand-binding domain, a single transmembrane α helix, and a cytosolic C-terminal domain with tyrosine kinase activity. The binding of growth factors to the RTKs extracellular domain activates the cytosolic kinase domain. Growth factor activation of the RTK results in dimerization of the receptor, with phosphorylation of the receptor and downstream targets. Upon activation of RTKs, various biological functions are altered in lung cancer cells, including cell growth, migration/motility, alterations of reactive oxygen species (ROS), and activation of downstream signal-transduction events. [ABSTRACT FROM AUTHOR]

Published
2003
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10. Molecular Alterations in Lung Cancer.

Author

Walker, John M., Driscoll, Barbara, Kijima, Takashi, Maulik, Gautam, and Salgia, Ravi

Abstract

Lung cancer is a devastating illness, and very few of the advances in chemotherapeutics have enhanced survival over the past decade. In order to make an impact on this disease, we must understand the molecular abnormalities to target better therapeutics. In this chapter, we will describe the better understanding at the molecular level that has been gained for lung cancer and its prognosis. Over the last decade, advances in molecular biology have provided important information about potentially significant determinants of prognosis in lung cancer (1,2). These molecular biomarkers are typically expressed in neoplastic lung tissue. Molecular abnormalities include chromosomal aberrations, telomerase expression, expression of oncogenes, and loss of tumor suppressor genes. Based on the understanding of the abnormalities at the cellular and molecular levels, newer therapies can be pursued. [ABSTRACT FROM AUTHOR]

Published
2003
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