Citations

[BVS+20]

Jürgen Bartel, Adithi R. Varadarajan, Thomas Sura, Christian H. Ahrens, Sandra Maaß, and Dörte Becher. Optimized proteomics workflow for the detection of small proteins. Journal of Proteome Research, 19(10):4004–4018, 2020. doi:10.1021/acs.jproteome.0c00286.

[CCB04]

Robertson Craig, John P. Cortens, and Ronald C. Beavis. Open source system for analyzing, validating, and storing protein identification data. Journal of proteome research, 3(6):1234–1242, 2004. doi:10.1021/pr049882h.

[GTL+14]

Xiaofeng Guo, David C. Trudgian, Andrew Lemoff, Sivaramakrishna Yadavalli, and Hamid Mirzaei. Confetti: a multiprotease map of the hela proteome for comprehensive proteomics. Molecular & cellular proteomics : MCP, 13(6):1573–1584, 2014. doi:10.1074/mcp.M113.035170.

[KCB+21]

Philipp T. Kaulich, Liam Cassidy, Jürgen Bartel, Ruth A. Schmitz, and Andreas Tholey. Multi-protease approach for the improved identification and molecular characterization of small proteins and short open reading frame-encoded peptides. Journal of Proteome Research, 20(5):2895–2903, 2021. doi:10.1021/acs.jproteome.1c00115.

[KGL+13]

Ja Koziol, Nm Griffin, F. Long, Y. Li, M. Latterich, and Je Schnitzer. On protein abundance distributions in complex mixtures. Proteome science, 11(1):5, 2013. doi:10.1186/1477-5956-11-5.

[SGS20]

Guillermo Serrano, Elizabeth Guruceaga, and Victor Segura. Deepmspeptide: peptide detectability prediction using deep learning. Bioinformatics, 36(4):1279–1280, 2020. doi:10.1093/bioinformatics/btz708.