Samuel A. Danziger - researchr alias

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Viewing Publication 1 - 5 from 5

2015

Bicluster Sampled Coherence Metric (BSCM) provides an accurate environmental context for phenotype predictionsSamuel A. Danziger, David J. Reiss, Alexander V. Ratushny, Jennifer J. Smith, Christopher L. Plaisier, John D. Aitchison, Nitin S. Baliga. bmcsb, 9(S-2), 2015. [doi]

2013

PhosphoChain: a novel algorithm to predict kinase and phosphatase networks from high-throughput expression dataWei-Ming Chen, Samuel A. Danziger, Jung-Hsien Chiang, John D. Aitchison. bioinformatics, 29(19):2435-2444, 2013. [doi]

2009

Predicting Positive p53 Cancer Rescue Regions Using Most Informative Positive (MIP) Active LearningSamuel A. Danziger, Roberta Baronio, Lydia Ho, Linda Hall, Kirsty Salmon, G. Wesley Hatfield, Peter Kaiser, Richard H. Lathrop. ploscb, 5(9), 2009. [doi]

2007

Choosing where to look next in a mutation sequence space: Active Learning of informative p53 cancer rescue mutantsSamuel A. Danziger, Jue Zeng, Ying Wang, Rainer K. Brachmann, Richard H. Lathrop. ismb 2007: 104-114 [doi]

2006

Functional Census of Mutation Sequence Spaces: The Example of p53 Cancer Rescue MutantsSamuel A. Danziger, Sanjay Joshua Swamidass, Jue Zeng, Lawrence R. Dearth, Qiang Lu, Jonathan H. Chen, Jianlin Cheng, Vinh P. Hoang, Hiroto Saigo, Ray Luo, Pierre Baldi, Rainer K. Brachmann, Richard H. Lathrop. tcbb, 3(2):114-125, 2006. [doi]

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