Xie J, Chen S, Zhao L, Dong X
J Pharm Anal. 2025; 15(1):101155.
PMID: 39896319
PMC: 11782803.
DOI: 10.1016/j.jpha.2024.101155.
Gogishvili D, Minois-Genin E, van Eck J, Abeln S
Bioinform Adv. 2024; 4(1):vbae154.
PMID: 39483526
PMC: 11525051.
DOI: 10.1093/bioadv/vbae154.
Weaver C, Nam A, Settle C, Overton M, Giddens M, Richardson K
Cancers (Basel). 2024; 16(9).
PMID: 38730581
PMC: 11083044.
DOI: 10.3390/cancers16091629.
Rehfeldt T, Krawczyk K, Gregersen Echers S, Marcatili P, Palczynski P, Rottger R
Gigascience. 2023; 12.
PMID: 37983748
PMC: 10659119.
DOI: 10.1093/gigascience/giad096.
Skiadopoulou D, Vasicek J, Kuznetsova K, Bouyssie D, Kall L, Vaudel M
J Proteome Res. 2023; 22(10):3190-3199.
PMID: 37656829
PMC: 10563157.
DOI: 10.1021/acs.jproteome.3c00243.
How sticky are our proteins? Quantifying hydrophobicity of the human proteome.
van Gils J, Gogishvili D, van Eck J, Bouwmeester R, van Dijk E, Abeln S
Bioinform Adv. 2023; 2(1):vbac002.
PMID: 36699344
PMC: 9710682.
DOI: 10.1093/bioadv/vbac002.
Prediction of peptides retention behavior in reversed-phase liquid chromatography based on their hydrophobicity.
Al Musaimi O, Valenzo O, Williams D
J Sep Sci. 2022; 46(2):e2200743.
PMID: 36349538
PMC: 10098489.
DOI: 10.1002/jssc.202200743.
Probabilistic metabolite annotation using retention time prediction and meta-learned projections.
Garcia C, Gil-de-la-Fuente A, Barbas C, Otero A
J Cheminform. 2022; 14(1):33.
PMID: 35672784
PMC: 9172150.
DOI: 10.1186/s13321-022-00613-8.
Evaluation of Machine Learning Models for Proteoform Retention and Migration Time Prediction in Top-Down Mass Spectrometry.
Chen W, McCool E, Sun L, Zang Y, Ning X, Liu X
J Proteome Res. 2022; 21(7):1736-1747.
PMID: 35616364
PMC: 9250612.
DOI: 10.1021/acs.jproteome.2c00124.
Deep learning neural network tools for proteomics.
Meyer J
Cell Rep Methods. 2022; 1(2):100003.
PMID: 35475237
PMC: 9017218.
DOI: 10.1016/j.crmeth.2021.100003.
DeepLC can predict retention times for peptides that carry as-yet unseen modifications.
Bouwmeester R, Gabriels R, Hulstaert N, Martens L, Degroeve S
Nat Methods. 2021; 18(11):1363-1369.
PMID: 34711972
DOI: 10.1038/s41592-021-01301-5.
An Introduction to Advanced Targeted Acquisition Methods.
van Bentum M, Selbach M
Mol Cell Proteomics. 2021; 20:100165.
PMID: 34673283
PMC: 8600983.
DOI: 10.1016/j.mcpro.2021.100165.
Identification, mapping and relative quantitation of SARS-CoV-2 Spike glycopeptides by Mass-Retention Time Fingerprinting.
Chalk R, Greenland W, Moreira T, Coker J, Mukhopadhyay S, Williams E
Commun Biol. 2021; 4(1):934.
PMID: 34345007
PMC: 8333269.
DOI: 10.1038/s42003-021-02455-w.
[Research progress and application of retention time prediction method based on deep learning].
Du Z, Shao W, Qin W
Se Pu. 2021; 39(3):211-218.
PMID: 34227303
PMC: 9403805.
DOI: 10.3724/SP.J.1123.2020.08015.
Prediction of Chromatography Conditions for Purification in Organic Synthesis Using Deep Learning.
Vaskevicius M, Kapociute-Dzikiene J, Slepikas L
Molecules. 2021; 26(9).
PMID: 33922736
PMC: 8123027.
DOI: 10.3390/molecules26092474.
Structure Driven Prediction of Chromatographic Retention Times: Applications to Pharmaceutical Analysis.
Szucs R, Brown R, Brunelli C, Heaton J, Hradski J
Int J Mol Sci. 2021; 22(8).
PMID: 33917733
PMC: 8068189.
DOI: 10.3390/ijms22083848.
The Role of Data-Independent Acquisition for Glycoproteomics.
Ye Z, Vakhrushev S
Mol Cell Proteomics. 2020; 20:100042.
PMID: 33372048
PMC: 8724878.
DOI: 10.1074/mcp.R120.002204.
In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics.
Yang Y, Liu X, Shen C, Lin Y, Yang P, Qiao L
Nat Commun. 2020; 11(1):146.
PMID: 31919359
PMC: 6952453.
DOI: 10.1038/s41467-019-13866-z.
Non-targeted and targeted analysis of collagen hydrolysates during the course of digestion and absorption.
Kleinnijenhuis A, van Holthoon F, Maathuis A, Vanhoecke B, Prawitt J, Wauquier F
Anal Bioanal Chem. 2019; 412(4):973-982.
PMID: 31872275
PMC: 7005076.
DOI: 10.1007/s00216-019-02323-x.
DART-ID increases single-cell proteome coverage.
Chen A, Franks A, Slavov N
PLoS Comput Biol. 2019; 15(7):e1007082.
PMID: 31260443
PMC: 6625733.
DOI: 10.1371/journal.pcbi.1007082.