| Year |
Citation |
Score |
| 2020 |
Pfeuffer J, Sachsenberg T, Dijkstra TMH, Serang O, Reinert K, Kohlbacher O. EPIFANY - A method for efficient high-confidence protein inference. Journal of Proteome Research. PMID 31975601 DOI: 10.1021/acs.jproteome.9b00566 |
0.532 |
|
| 2019 |
Kretizberg PA, Bern M, Shu Q, Yang F, Serang O. The alphabet projection of spectra. Journal of Proteome Research. PMID 31318211 DOI: 10.1021/Acs.Jproteome.9B00216 |
0.314 |
|
| 2017 |
Serang O, Heyl F. TRIOT: Faster tensor manipulation in C++11 The Art, Science, and Engineering of Programming. 1. DOI: 10.22152/Programming-Journal.Org/2017/1/6 |
0.306 |
|
| 2016 |
Nilse L, Avci D, Heisterkamp P, Serang O, Lemberg MK, Schilling O. Yeast membrane proteomics using leucine metabolic labelling: Bioinformatic data processing and exemplary application to the ER-intramembrane protease Ypf1. Biochimica Et Biophysica Acta. PMID 27426920 DOI: 10.1016/J.Bbapap.2016.07.002 |
0.37 |
|
| 2015 |
Serang O, Käll L. Solution to Statistical Challenges in Proteomics Is More Statistics, Not Less. Journal of Proteome Research. 14: 4099-103. PMID 26257019 DOI: 10.1021/Acs.Jproteome.5B00568 |
0.482 |
|
| 2015 |
Serang O. 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. PMID 26161499 DOI: 10.1089/Cmb.2015.0013 |
0.34 |
|
| 2014 |
Serang O. The probabilistic convolution tree: efficient exact Bayesian inference for faster LC-MS/MS protein inference. Plos One. 9: e91507. PMID 24626234 DOI: 10.1371/Journal.Pone.0091507 |
0.452 |
|
| 2013 |
Serang O, Cansizoglu AE, Käll L, Steen H, Steen JA. Nonparametric bayesian evaluation of differential protein quantification Journal of Proteome Research. 12: 4556-4565. PMID 24024742 DOI: 10.1021/Pr400678M |
0.445 |
|
| 2013 |
Serang O, Froehlich JW, Muntel J, McDowell G, Steen H, Lee RS, Steen JA. SweetSEQer, simple de novo filtering and annotation of glycoconjugate mass spectra Molecular and Cellular Proteomics. 12: 1735-1740. PMID 23443135 DOI: 10.1074/Mcp.O112.025940 |
0.407 |
|
| 2013 |
Froehlich JW, Dodds ED, Wilhelm M, Serang O, Steen JA, Lee RS. A classifier based on accurate mass measurements to aid large scale, unbiased glycoproteomics Molecular and Cellular Proteomics. 12: 1017-1025. PMID 23438733 DOI: 10.1074/Mcp.M112.025494 |
0.444 |
|
| 2013 |
Serang O, Paulo J, Steen H, Steen JA. A non-parametric cutout index for robust evaluation of identified proteins Molecular and Cellular Proteomics. 12: 807-812. PMID 23292186 DOI: 10.1074/Mcp.O112.022863 |
0.569 |
|
| 2013 |
Serang O. Concerning the accuracy of Fido and parameter choice. Bioinformatics (Oxford, England). 29: 412. PMID 23193221 DOI: 10.1093/Bioinformatics/Bts687 |
0.361 |
|
| 2012 |
Serang O, Moruz L, Hoopmann MR, Käll L. Recognizing uncertainty increases robustness and reproducibility of mass spectrometry-based protein inferences. Journal of Proteome Research. 11: 5586-91. PMID 23148905 DOI: 10.1021/Pr300426S |
0.487 |
|
| 2012 |
Serang O, Noble W. A review of statistical methods for protein identification using tandem mass spectrometry. Statistics and Its Interface. 5: 3-20. PMID 22833779 DOI: 10.4310/Sii.2012.V5.N1.A2 |
0.56 |
|
| 2012 |
Serang O, Noble WS. Faster mass spectrometry-based protein inference: junction trees are more efficient than sampling and marginalization by enumeration. Ieee/Acm Transactions On Computational Biology and Bioinformatics / Ieee, Acm. 9: 809-17. PMID 22331862 DOI: 10.1109/Tcbb.2012.26 |
0.6 |
|
| 2010 |
Serang O, MacCoss MJ, Noble WS. Efficient marginalization to compute protein posterior probabilities from shotgun mass spectrometry data. Journal of Proteome Research. 9: 5346-57. PMID 20712337 DOI: 10.1021/Pr100594K |
0.584 |
|
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