2024
38. Natalizumab promotes anti-inflammatory and repair effects in multiple sclerosis.
Lereim RR, Nytrova P, Guldbrandsen A, Havrdova EK, Myhr KM, Barsnes H, Berven FS. PLoS One. 2024 Mar 25;19(3):e0300914. 10.1371/journal.pone.0300914
2023
37. Extending protein interaction networks using proteoforms and small molecules.
Hernández Sánchez LF, Burger B, Castro Campos RA, Johansson S, Njølstad PR, Barsnes H, Vaudel M. Bioinformatics. 2023 Oct 3;39(10):btad598. 10.1093/bioinformatics/btad598
36. Automated splitting into batches for observational biomedical studies with sequential processing.
Burger B, Vaudel M, Barsnes H. Biostatistics. 2023 Oct 18;24(4):1031-1044. 10.1093/biostatistics/kxac014
2021
35. PeptideShaker Online: a user-friendly web-based framework for the identification of mass spectrometry-based proteomics data.
Farag YM, Horro C, Vaudel M, Barsnes H. J Proteome Res. 2021 Dec 3;20(12):5419-5423. 10.1021/acs.jproteome.1c00678
34. Cuprizone and EAE mouse frontal cortex proteomics revealed proteins altered in multiple sclerosis.
Oveland E, Ahmad I, Lereim RR, Kroksveen AC, Barsnes H, Guldbrandsen A, Myhr KM, Bø L, Berven FS, Wergeland S. Sci Rep. 2021 Mar 30;11(1):7174. 10.1038/s41598-021-86191-5
33. Importance of block randomization when designing proteomics experiments.
Burger B, Vaudel M, Barsnes H. J Proteome Res. 2021 Jan 1;20(1):122-128. 10.1021/acs.jproteome.0c00536
32. Leptin Receptor Signaling Regulates Protein Synthesis Pathways and Neuronal Differentiation in Pluripotent Stem Cells.
Gupta MK, Vethe H, Softic S, Rao TN, Wagh V, Shirakawa J, Barsnes H, Vaudel M, Takatani T, Kahraman S, Sakaguchi M, Martinez R, Hu J, Bjørlykke Y, Raeder H, Kulkarni RN. Stem Cell Reports. 2020 Nov 10;15(5):1067-1079. 10.1016/j.stemcr.2020.10.001
2020
31. Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis.
Guldbrandsen A, Lereim RR, Jacobsen M, Garberg H, Kroksveen AC, Barsnes H, Berven FS. Clin Proteomics. 2020 Sep 18;17:33. 10.1186/s12014-020-09296-5
30. Connecting MetaProteomeAnalyzer and PeptideShaker to Unipept for seamless end-to-end metaproteomics data analysis.
Van Den Bossche T, Verschaffelt P, Schallert K, Barsnes H, Dawyndt P, Benndorf D, Renard BY, Mesuere B, Martens L, Muth T. J Proteome Res. 2020 Aug 7;19(8):3562-3566. 10.1021/acs.jproteome.0c00136
29. Anatomy and evolution of database search engines, a central cog in mass spectrometry based proteomic workflows.
Verheggen K, Berven FS, Martens L, Barsnes H, Vaudel M. Mass Spectrom Rev. 2020 May;39(3):292-306. 10.1002/mas.21543
28. Dynamic proteome profiling of human pluripotent stem cell-derived pancreatic progenitors.
Loo LSW, Vethe H, Soetedjo AAP, Paulo JA, Jasmen J, Jackson N, Bjørlykke Y, Valdez IA, Vaudel M, Barsnes H, Gygi SP, Raeder H, Teo AKK, Kulkarni RN. Stem Cells. 2020 Apr;38(4):542-555. 10.1002/stem.3135
27. ThermoRawFileParser: modular, scalable and cross-platform RAW file conversion.
Hulstaert N, Shofstahl J, Sachsenberg T, Walzer Mathias, Barsnes H, Martens L, Perez-Riverol Y. J Proteome Res. 2020 Jan 3;19(1):537-542. 10.1021/acs.jproteome.9b00328
2019
26. PathwayMatcher: proteoform-centric network construction enables fine-granularity multi-omics pathway mapping.
Sánchez LFH, Burger B, Horro C, Fabregat A, Johansson S, Njølstad PR, Barsnes H, Hermjakob H, Vaudel M. Gigascience. 2019 Aug 1;8(8). 10.1093/gigascience/giz088
25. Essential Features and Use Cases of the Cerebrospinal Fluid Proteome Resource (CSF-PR).
Guldbrandsen A, Farag Y, Lereim RR, Berven FS, Barsnes H. Methods Mol Biol. 2019;2044:377-391. 10.1007/978-1-4939-9706-0_25
24. Protein Post-Translational Modification Crosstalk in Acute Myeloid Leukemia Calls for Action.
Hernandez M, Wangen R, Berven F, Guldbrandsen A. Curr Med Chem. 2019;26(28):5317-5337. 10.2174/0929867326666190503164004
23. Detecting single amino acids and small peptides by combining isobaric tags and peptidomics.
Burger B, Lereim RR, Berven FS, Barsnes H. Eur J Mass Spectrom (Chichester). 2019 Dec;25(6):451-456. 10.1177/1469066719857006
22. Proteomics Standards Initiative Extended FASTA Format (PEFF).
Binz PA, Shofstahl J, Vizcaíno J, Barsnes H, Chalkley R, Menschaert G, Alpi E, Clauser K, Eng JK. Lane L, Seymour S, Sánchez LFH, Mayer G, Eisenacher M, Perez-Riverol Y, Kapp E, Mendoza L, Baker PR, Collins A, Van Den Bossche T, Deutsch EW. J Proteome Res. 2019 Jun 7;18(6):2686-2692. 10.1021/acs.jproteome.9b00064
2018
21. Analysing the structure of pathways and its influence on the interpretation of biomedical proteomics datasets.
Burger B, Hernández Sánchez LF, Lereim RR, Barsnes H, Vaudel M. J Proteome Res. 2018 Nov 2;17(11):3801-3809. 10.1021/acs.jproteome.8b00464
20. SearchGUI: a highly adaptable common interface for proteomics search and de novo engines.
Barsnes H, Vaudel M. J Proteome Res. 2018 Jul 6;17(7):2552-2555. 10.1021/acs.jproteome.8b00175
2017
19. OLS Client and OLS Dialog: Open source tools to annotate public omics datasets.
Perez-Riverol Y, Ternent T, Koch M, Barsnes H, Vrousgou O, Jupp S, Vizcaíno JA. Proteomics. 2017 Oct;17(19). 10.1002/pmic.201700244
18. An accessible proteogenomics informatics resource for cancer researchers.
Chambers MC, Jagtap PD, Johnson JE, McGowan T, Kumar P, Onsongo G, Guerrero CR, Barsnes H, Vaudel M, Martens L, Grüning B, Cooke IR, Heydarian M, Reddy KL, Griffin TJ. Cancer Res. 2017 Nov 1;77(21):e43-e46. 10.1158/0008-5472.CAN-17-0331
17. The mzIdentML data standard v1.2 – supporting advances in proteome informatics.
Vizcaíno JA, Mayer G, Perkins S, Barsnes H, Vaudel M, Perez-Riverol Y, Ternent T, Uszkoreit J, Eisenacher M, Fischer L, Rappsilber J, Netz E, Walzer M, Kohlbacher O, Leitner A, Chalkley RJ, Ghali F, Martínez-Bartolomé S, Deutsch EW, Jones AR. Mol Cell Proteomics. 2017 Jul;16(7):1275-1285. 10.1074/mcp.M117.068429
16. BioContainers: an open-source and community-driven framework for software standardization.
Leprevost FdV, Aflitos SA, Grüning BA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeufferz J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. Bioinformatics. 2017 Aug 15;33(16):2580-2582. 10.1093/bioinformatics/btx192
15. PeptideMapper: efficient and versatile amino acid sequence and tag mapping.
Kopczynski D, Barsnes H, Njølstad PR, Sickmann A, Vaudel M, Ahrends R. Bioinformatics. 2017 Jul 1;33(13):2042-2044. 10.1093/bioinformatics/btx122
14. CSF-PR 2.0: an interactive literature guide to quantitative cerebrospinal fluid mass spectrometry data from neurodegenerative disorders.
Guldbrandsen A, Farag Y, Kroksveen AC, Oveland E, Lereim RR, Opsahl JA, Myhr KM, Berven FS, Barsnes H. Mol Cell Proteomics. 2017 Feb;16(2):300-309. 10.1074/mcp.O116.064477
13. In-depth cerebrospinal fluid quantitative proteome and deglycoproteome analysis; presenting a comprehensive picture of pathways and processes affected by multiple sclerosis.
Kroksveen AC, Guldbrandsen A, Vaudel M, Lereim RR, Barsnes H, Myhr KM, Torkildsen Ø, Berven FS. J Proteome Res. 2017 Jan 6;16(1):179-194. 10.1021/acs.jproteome.6b00659
2016
12. Database search engines. Paradigms, challenges and solutions.
Verheggen K, Martens L, Berven FS, Barsnes H and Vaudel M. Adv Exp Med Biol. 2016;919:147-156. 10.1007/978-3-319-41448-5_6
11. Visualization, inspection and interpretation of shotgun proteomics identification results.
Lereim RR, Oveland E, Berven FS, Vaudel M and Barsnes H. Adv Exp Med Biol. 2016;919:227-235. 10.1007/978-3-319-41448-5_11
10. Tandem mass spectrum sequencing: an alternative to database search engines in shotgun proteomics.
Muth T, Rapp E, Berven FS, Barsnes H and Vaudel M. Adv Exp Med Biol. 2016;919:217-226. 10.1007/978-3-319-41448-5_10
9. Using Proteomics Bioinformatics Tools and Resources in Proteogenomic Studies.
Vaudel M, Barsnes H, Ræder H, Berven FS. Adv Exp Med Biol. 2016;926:65-75. 10.1007/978-3-319-42316-6_5
8. A pipeline for differential proteomics in unsequenced species.
Yılmaz Ş, Victor B, Hulstaert N, Vandermarliere E, Barsnes H, Degroeve S, Gupta S, Sticker A, Gabriël S, Dorny P, Palmblad M, Martens L. J Proteome Res. 2016 Jun 3;15(6):1963-70. 10.1021/acs.jproteome.6b00140
7. Label free analysis of human cerebrospinal fluid addressing various normalization strategies and revealing protein groups affected by multiple sclerosis.
Opsahl JA, Vaudel M, Guldbrandsen A, Aasebø E, van Pesch V, Franciotta D, Myhr KM, Barsnes H, Berle M, Torkildsen Ø, Kroksveen AC, Berven FS. Proteomics. 2016 Apr;16(7):1154-65. 10.1021/acs.jproteome.6b00140
6. Pladipus enables universal distributed computing in proteomics bioinformatics.
Verheggen K, Maddelein D, Hulstaert N, Martens L, Barsnes H, Vaudel M. J Proteome Res. 2016 Mar 4;15(3):707-12. 10.1021/acs.jproteome.5b00850
5. Exploring the potential of public proteomics data.
Vaudel M, Verheggen K, Csordas A, Ræder H, Berven FS, Martens L, Vizcaíno JA, Barsnes H. Proteomics. 2016 Jan;16(2):214-25. 10.1002/pmic.201500295
4. Systemic analysis of regulated functional networks.
Sánchez LFH, Aasebø E, Selheim F, Berven F, Ræder H, Barsnes H, Vaudel M. Methods Mol Biol. 2016;1394:287-310. 10.1007/978-1-4939-3341-9_21
3. A simple workflow for large scale shotgun glycoproteomics.
Guldbrandsen A, Barsnes H, Kroksveen AC, Berven F, Vaudel M. Methods Mol Biol. 2016;1394:275-86. 10.1007/978-1-4939-3341-9_20
2. Interpretation of quantitative shotgun proteomics data.
Aasebø E, Berven FS, Selheim F, Barsnes H, Vaudel M. Methods Mol Biol. 2016;1394:261-73. 10.1007/978-1-4939-3341-9_19
1. Practical considerations for omics experiments in biomedical sciences.
Vaudel M, Barsnes H, Bjerkvig R, Bikfalvi A, Selheim F, Berven FS, Daubon T. Curr Pharm Biotechnol. 2016;17(1):105-14. 10.2174/1389201016666150817095348