mona singh princeton

McGrew A, Singh M, Stahl J, Yoos J, Sanghvi K. TCT-230 Rotational Atherectomy vs Orbital Atherectomy in Calcified Coronary Artery Disease: A Contemporary Retrospective Comparative Analysis (ROCC study). She works broadly in computational molecular biology, as well as its interface with machine learning and algorithms. Forward-Thinking Idea: A sociologist who has pioneered uses of data and digital technologies in social research, Salganik is the author of the 2017 book, “Bit by Bit: Social Research in the Digital Age.” His research examines how social media, smartphones and other digital devices can transform our understanding of human activity, while keenly pointing out the complex ethical challenges of collecting massive troves of personal information. She received her Ph.D. in computer science from MIT in 1996 after earning her master’s and bachelor’s degrees from Harvard. Conserved and Associated with Distinct Genomic Features in. structures highlights DNA-, RNA- and other ligand-binding positions. Our structural approach has been to focus on particular structural motifs that mediate protein-protein interactions, and to develop fast, computational methods both for recognizing these motifs within protein sequences as well as for predicting which of these sequences interact with each other. SPICi: a fast clustering algorithm for The difficulty of the general protein structure prediction problem precludes prediction at a detailed structural level (e.g., at the atomic level). Elena Nabieva, Kam Jim, Amit Agarwal, Bernard Chazelle and Mona Singh. Proc. Mona Singh is a professor of computer science and the Lewis Sigler Institute for Integrative Genomics. Princeton University. She has pioneered interdisciplinary courses in the field of bioinformatics, the method by which computers are used to synthesize vast quantities of raw biological data. A systematic survey of the Cys2His2 zinc finger DNA-binding landscape. Beyond the E-Value: Stratified Statistics for Protein Domain Prediction. Mona Singh. A. Persikov, J. Wetzel, E. Rowland, B. Oakes, D. Xu, M. Singh and M. Noyes. Download source code. B. Hristov, B. Chazelle and M. Singh. motif finding. Download source code for use within the MUMmer 3 system. "Domain prediction with probabilistic directional context." genetic code, The trimer-of-hairpins motif in viral We are particularly interested in developing algorithms for genome-level analysis of protein structure and protein-protein interactions. Professor of Sociology and Director of the Center for Information Technology Policy. Her recent work has identified genes and mutations that play a role in cancer development, an important first step to guiding new treatments. motif finding applications, A compact mathematical programming formulation for Nucleic Acids Res. She received her A.B. interactions, Structural characterization of the human She received a Presidential Early Career Award for Scientists and Engineers and the Rheinstein Junior Faculty Award from the School of Engineering and Applied Science. Systematic domain-based aggregation of protein /~mona / Mona Singh is a Professor of Computer Science in the Lewis-Sigler Institute for Integrative Genomics at Princeton University. Assistant Professor of Politics and Public Affairs and Arthur H. Scribner Bicentennial Preceptor. Two critical positions in zinc finger domains (Authors alphabetized.) Stratification of coronary artery disease patients for revascularization procedure based on estimating adverse effects. Persikov AV, Wetzel JL, Rowland EF, Oakes BL, Xu DJ, Singh M, et al. microarrays, A practical algorithm for finding maximal exact J. Comput. Genome-wide detection and analysis of Presidental Early Career Award (PECASE), 2001. Princeton is full of Forward Thinkers. Interaction-based discovery of functionally Singh, a professor of computer science and the Lewis-Sigler Institute for Integrative Genomics, was recognized “for contributions to computational biology, spearheading algorithmic and machine learning approaches for characterizing proteins and their interactions,” the association said. De novo prediction of DNA-binding specificities bind common targets. Professor of Sociology and Public Affairs. Site Map, Ph.D., Massachusetts Institute of Technology, 1995. Additionally, the constraint of genomic-level analysis favors a focus on fast, informatics-based methods. Community investment, not punishment, he says, is the key to reducing crime. She points out that, just as governors have been leading the charge to combat the COVID-19 pandemic, state leaders are at the forefront of innovative health policy development to protect consumers in a multitude of ways. Deep sequencing of large library selections Interests: Computational molecular biology, as well as its interface with machine learning and algorithms.

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