Oliver Serang, Ph.D.
Affiliations: | University of Washington, Seattle, Seattle, WA |
Area:
modeling biological processes at the molecular levelGoogle:
"Oliver Serang"Mean distance: 21.31 (cluster 23)
Parents
Sign in to add mentor| William Stafford Noble | grad student | 2011 | University of Washington | |
| (A practically efficient graph-theoretic approach to protein identification in mass spectrometry.) | ||||
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Publications
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| Pfeuffer J, Sachsenberg T, Dijkstra TMH, et al. (2020) EPIFANY - A method for efficient high-confidence protein inference. Journal of Proteome Research |
| Kretizberg PA, Bern M, Shu Q, et al. (2019) The alphabet projection of spectra. Journal of Proteome Research |
| Serang O, Heyl F. (2017) TRIOT: Faster tensor manipulation in C++11 The Art, Science, and Engineering of Programming. 1 |
| Nilse L, Avci D, Heisterkamp P, et al. (2016) Yeast membrane proteomics using leucine metabolic labelling: Bioinformatic data processing and exemplary application to the ER-intramembrane protease Ypf1. Biochimica Et Biophysica Acta |
| Serang O, Käll L. (2015) Solution to Statistical Challenges in Proteomics Is More Statistics, Not Less. Journal of Proteome Research. 14: 4099-103 |
| Serang O. (2015) A Fast Numerical Method for Max-Convolution and the Application to Efficient Max-Product Inference in Bayesian Networks. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 22: 770-83 |
| Serang O. (2014) The probabilistic convolution tree: efficient exact Bayesian inference for faster LC-MS/MS protein inference. Plos One. 9: e91507 |
| Serang O, Cansizoglu AE, Käll L, et al. (2013) Nonparametric bayesian evaluation of differential protein quantification Journal of Proteome Research. 12: 4556-4565 |
| Serang O, Froehlich JW, Muntel J, et al. (2013) SweetSEQer, simple de novo filtering and annotation of glycoconjugate mass spectra Molecular and Cellular Proteomics. 12: 1735-1740 |
| Froehlich JW, Dodds ED, Wilhelm M, et al. (2013) A classifier based on accurate mass measurements to aid large scale, unbiased glycoproteomics Molecular and Cellular Proteomics. 12: 1017-1025 |