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Deficiency in outer dense fiber 1 is a marker and potential driver of idiopathic male infertility.

Molecular & cellular proteomics : MCP

Hetherington L, Schneider EK, Scott C, DeKretser D, Muller CH, Hondermarck H, Velkov T, Baker MA.
PMID: 28572402
Mol Cell Proteomics. 2017 Jun;16(6):1172. doi: 10.1074/mcp.A116.060343.

No abstract available.

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Hetherington L, Schneider EK, Scott C, et al. Deficiency in outer dense fiber 1 is a marker and potential driver of idiopathic male infertility. Mol Cell Proteomics. 2017;16(6):1172doi: 10.1074/mcp.A116.060343.
Hetherington, L., Schneider, E. K., Scott, C., DeKretser, D., Muller, C. H., Hondermarck, H., Velkov, T., & Baker, M. A. (2017). Deficiency in outer dense fiber 1 is a marker and potential driver of idiopathic male infertility. Molecular & cellular proteomics : MCP, 16(6), 1172. https://doi.org/10.1074/mcp.A116.060343
Hetherington, Louise, et al. "Deficiency in outer dense fiber 1 is a marker and potential driver of idiopathic male infertility." Molecular & cellular proteomics : MCP vol. 16,6 (2017): 1172. doi: https://doi.org/10.1074/mcp.A116.060343
Hetherington L, Schneider EK, Scott C, DeKretser D, Muller CH, Hondermarck H, Velkov T, Baker MA. Deficiency in outer dense fiber 1 is a marker and potential driver of idiopathic male infertility. Mol Cell Proteomics. 2017 Jun;16(6):1172. doi: 10.1074/mcp.A116.060343. PMID: 28572402; PMCID: PMC5461546.
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The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data.

Glycobiology

Liu Y, McBride R, Stoll M, Palma AS, Silva L, Agravat S, Aoki-Kinoshita KF, Campbell MP, Costello CE, Dell A, Haslam SM, Karlsson NG, Khoo KH, Kolarich D, Novotny MV, Packer NH, Ranzinger R, Rapp E, Rudd PM, Struwe WB, Tiemeyer M, Wells L, York WS, Zaia J, Kettner C, Paulson JC, Feizi T, Smith DF.
PMID: 27993942
Glycobiology. 2017 Apr;27(4):280-284. doi: 10.1093/glycob/cww118. Epub 2016 Nov 22.

MIRAGE (Minimum Information Required for A Glycomics Experiment) is an initiative that was created by experts in the fields of glycobiology, glycoanalytics and glycoinformatics to produce guidelines for reporting results from the diverse types of experiments and analyses used...

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Liu Y, McBride R, Stoll M, et al. The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data. Glycobiology. 2016;27(4):280-284doi: 10.1093/glycob/cww118.
Liu, Y., McBride, R., Stoll, M., Palma, A. S., Silva, L., Agravat, S., Aoki-Kinoshita, K. F., Campbell, M. P., Costello, C. E., Dell, A., Haslam, S. M., Karlsson, N. G., Khoo, K. H., Kolarich, D., Novotny, M. V., Packer, N. H., Ranzinger, R., Rapp, E., Rudd, P. M., Struwe, W. B., Tiemeyer, M., Wells, L., York, W. S., Zaia, J., Kettner, C., Paulson, J. C., Feizi, T., & Smith, D. F. (2017). The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data. Glycobiology, 27(4), 280-284. https://doi.org/10.1093/glycob/cww118
Liu, Yan, et al. "The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data." Glycobiology vol. 27,4 (2017): 280-284. doi: https://doi.org/10.1093/glycob/cww118
Liu Y, McBride R, Stoll M, Palma AS, Silva L, Agravat S, Aoki-Kinoshita KF, Campbell MP, Costello CE, Dell A, Haslam SM, Karlsson NG, Khoo KH, Kolarich D, Novotny MV, Packer NH, Ranzinger R, Rapp E, Rudd PM, Struwe WB, Tiemeyer M, Wells L, York WS, Zaia J, Kettner C, Paulson JC, Feizi T, Smith DF. The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data. Glycobiology. 2017 Apr;27(4):280-284. doi: 10.1093/glycob/cww118. Epub 2016 Nov 22. PMID: 27993942; PMCID: PMC5444268.
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Phospho-iTRAQ data article: Assessing isobaric labels for the large-scale study of phosphopeptide stoichiometry.

Data in brief

Glibert P, Meert P, Van Steendam K, Martens L, Deforce D, Dhaenens M.
PMID: 26217764
Data Brief. 2015 May 06;4:60-5. doi: 10.1016/j.dib.2015.04.012. eCollection 2015 Sep.

The ability to distinguish between phosphopeptides of high and low stoichiometry is essential to discover the true extent of protein phosphorylation. We here extend the strategy whereby a peptide sample is briefly split in two identical parts and differentially...

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Glibert P, Meert P, Van Steendam K, et al. Phospho-iTRAQ data article: Assessing isobaric labels for the large-scale study of phosphopeptide stoichiometry. Data Brief. 2015;4:60-5doi: 10.1016/j.dib.2015.04.012.
Glibert, P., Meert, P., Van Steendam, K., Martens, L., Deforce, D., & Dhaenens, M. (2015). Phospho-iTRAQ data article: Assessing isobaric labels for the large-scale study of phosphopeptide stoichiometry. Data in brief, 460-5. https://doi.org/10.1016/j.dib.2015.04.012
Glibert, Pieter, et al. "Phospho-iTRAQ data article: Assessing isobaric labels for the large-scale study of phosphopeptide stoichiometry." Data in brief vol. 4 (2015): 60-5. doi: https://doi.org/10.1016/j.dib.2015.04.012
Glibert P, Meert P, Van Steendam K, Martens L, Deforce D, Dhaenens M. Phospho-iTRAQ data article: Assessing isobaric labels for the large-scale study of phosphopeptide stoichiometry. Data Brief. 2015 May 06;4:60-5. doi: 10.1016/j.dib.2015.04.012. eCollection 2015 Sep. PMID: 26217764; PMCID: PMC4510381.
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HUPO (Human Proteome Organization) 1st World Congress. 21-24 November 2002, Versailles, France. Abstracts.

Molecular & cellular proteomics : MCP

[No authors listed]
PMID: 12474872
Mol Cell Proteomics. 2002 Sep;1(9):651-752.

No abstract available.

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HUPO (Human Proteome Organization) 1st World Congress. 21-24 November 2002, Versailles, France. Abstracts. Mol Cell Proteomics. 2002;1(9):651-752
(2002). HUPO (Human Proteome Organization) 1st World Congress. 21-24 November 2002, Versailles, France. Abstracts. Molecular & cellular proteomics : MCP, 1(9), 651-752.
"HUPO (Human Proteome Organization) 1st World Congress. 21-24 November 2002, Versailles, France. Abstracts." Molecular & cellular proteomics : MCP vol. 1,9 (2002): 651-752.
HUPO (Human Proteome Organization) 1st World Congress. 21-24 November 2002, Versailles, France. Abstracts. Mol Cell Proteomics. 2002 Sep;1(9):651-752. PMID: 12474872.
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Correction: Phytoplasma-induced Changes in the Acetylome and Succinylome of Paulownia Tomentosa Provide Evidence for Involvement of Acetylated Proteins in Witches' Broom Disease.

Molecular & cellular proteomics : MCP

Cao Y, Fan G, Wang Z, Gu Z.
PMID: 31371573
Mol Cell Proteomics. 2019 Aug;18(8):1703. doi: 10.1074/mcp.AAC119.001627.

No abstract available.

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Cao Y, Fan G, Wang Z, et al. Correction: Phytoplasma-induced Changes in the Acetylome and Succinylome of Paulownia Tomentosa Provide Evidence for Involvement of Acetylated Proteins in Witches' Broom Disease. Mol Cell Proteomics. 2019;18(8):1703doi: 10.1074/mcp.AAC119.001627.
Cao, Y., Fan, G., Wang, Z., & Gu, Z. (2019). Correction: Phytoplasma-induced Changes in the Acetylome and Succinylome of Paulownia Tomentosa Provide Evidence for Involvement of Acetylated Proteins in Witches' Broom Disease. Molecular & cellular proteomics : MCP, 18(8), 1703. https://doi.org/10.1074/mcp.AAC119.001627
Cao, Yabing, et al. "Correction: Phytoplasma-induced Changes in the Acetylome and Succinylome of Paulownia Tomentosa Provide Evidence for Involvement of Acetylated Proteins in Witches' Broom Disease." Molecular & cellular proteomics : MCP vol. 18,8 (2019): 1703. doi: https://doi.org/10.1074/mcp.AAC119.001627
Cao Y, Fan G, Wang Z, Gu Z. Correction: Phytoplasma-induced Changes in the Acetylome and Succinylome of Paulownia Tomentosa Provide Evidence for Involvement of Acetylated Proteins in Witches' Broom Disease. Mol Cell Proteomics. 2019 Aug;18(8):1703. doi: 10.1074/mcp.AAC119.001627. PMID: 31371573; PMCID: PMC6682999.
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Integrated Glycoproteomics Identifies a Role of N-Glycosylation and Galectin-1 on Myogenesis and Muscle Development.

Molecular & cellular proteomics : MCP

Blazev R, Ashwood C, Abrahams JL, Chung LH, Francis D, Yang P, Watt KI, Qian H, Quaife-Ryan GA, Hudson JE, Gregorevic P, Thaysen-Andersen M, Parker BL.
PMID: 33583770
Mol Cell Proteomics. 2020 Dec 19;20:100030. doi: 10.1074/mcp.RA120.002166. Epub 2020 Dec 19.

Many cell surface and secreted proteins are modified by the covalent addition of glycans that play an important role in the development of multicellular organisms. These glycan modifications enable communication between cells and the extracellular matrix via interactions with...

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Blazev R, Ashwood C, Abrahams JL, et al. Integrated Glycoproteomics Identifies a Role of N-Glycosylation and Galectin-1 on Myogenesis and Muscle Development. Mol Cell Proteomics. 2020;20:100030doi: 10.1074/mcp.RA120.002166.
Blazev, R., Ashwood, C., Abrahams, J. L., Chung, L. H., Francis, D., Yang, P., Watt, K. I., Qian, H., Quaife-Ryan, G. A., Hudson, J. E., Gregorevic, P., Thaysen-Andersen, M., & Parker, B. L. (2020). Integrated Glycoproteomics Identifies a Role of N-Glycosylation and Galectin-1 on Myogenesis and Muscle Development. Molecular & cellular proteomics : MCP, 20100030. https://doi.org/10.1074/mcp.RA120.002166
Blazev, Ronnie, et al. "Integrated Glycoproteomics Identifies a Role of N-Glycosylation and Galectin-1 on Myogenesis and Muscle Development." Molecular & cellular proteomics : MCP vol. 20 (2020): 100030. doi: https://doi.org/10.1074/mcp.RA120.002166
Blazev R, Ashwood C, Abrahams JL, Chung LH, Francis D, Yang P, Watt KI, Qian H, Quaife-Ryan GA, Hudson JE, Gregorevic P, Thaysen-Andersen M, Parker BL. Integrated Glycoproteomics Identifies a Role of N-Glycosylation and Galectin-1 on Myogenesis and Muscle Development. Mol Cell Proteomics. 2020 Dec 19;20:100030. doi: 10.1074/mcp.RA120.002166. Epub 2020 Dec 19. PMID: 33583770.
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Virtual Issue: Technological Innovations.

Molecular & cellular proteomics : MCP

Gingras AC, Carr SA, Burlingame AL.
PMID: 32184224
Mol Cell Proteomics. 2020 Apr;19(4):572-573. doi: 10.1074/mcp.E120.002042. Epub 2020 Mar 17.

No abstract available.

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Gingras AC, Carr SA, Burlingame AL. Virtual Issue: Technological Innovations. Mol Cell Proteomics. 2020;19(4):572-573doi: 10.1074/mcp.E120.002042.
Gingras, A. C., Carr, S. A., & Burlingame, A. L. (2020). Virtual Issue: Technological Innovations. Molecular & cellular proteomics : MCP, 19(4), 572-573. https://doi.org/10.1074/mcp.E120.002042
Gingras, Anne-Claude, et al. "Virtual Issue: Technological Innovations." Molecular & cellular proteomics : MCP vol. 19,4 (2020): 572-573. doi: https://doi.org/10.1074/mcp.E120.002042
Gingras AC, Carr SA, Burlingame AL. Virtual Issue: Technological Innovations. Mol Cell Proteomics. 2020 Apr;19(4):572-573. doi: 10.1074/mcp.E120.002042. Epub 2020 Mar 17. PMID: 32184224; PMCID: PMC7124464.
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Integrated Redox Proteomic Analysis Highlights New Mechanisms of Sensitivity to Silver Nanoparticles.

Molecular & cellular proteomics : MCP

Holmila R, Wu H, Lee J, Tsang AW, Singh R, Furdui CM.
PMID: 33757833
Mol Cell Proteomics. 2021;20:100073. doi: 10.1016/j.mcpro.2021.100073. Epub 2021 Mar 20.

Silver nanoparticles (AgNPs) are widely used nanomaterials in both commercial and clinical biomedical applications, but the molecular mechanisms underlying their activity remain elusive. In this study we profiled proteomics and redox proteomics changes induced by AgNPs in two lung...

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Holmila R, Wu H, Lee J, et al. Integrated Redox Proteomic Analysis Highlights New Mechanisms of Sensitivity to Silver Nanoparticles. Mol Cell Proteomics. 2021;20:100073doi: 10.1016/j.mcpro.2021.100073.
Holmila, R., Wu, H., Lee, J., Tsang, A. W., Singh, R., & Furdui, C. M. (2021). Integrated Redox Proteomic Analysis Highlights New Mechanisms of Sensitivity to Silver Nanoparticles. Molecular & cellular proteomics : MCP, 20100073. https://doi.org/10.1016/j.mcpro.2021.100073
Holmila, Reetta, et al. "Integrated Redox Proteomic Analysis Highlights New Mechanisms of Sensitivity to Silver Nanoparticles." Molecular & cellular proteomics : MCP vol. 20 (2021): 100073. doi: https://doi.org/10.1016/j.mcpro.2021.100073
Holmila R, Wu H, Lee J, Tsang AW, Singh R, Furdui CM. Integrated Redox Proteomic Analysis Highlights New Mechanisms of Sensitivity to Silver Nanoparticles. Mol Cell Proteomics. 2021;20:100073. doi: 10.1016/j.mcpro.2021.100073. Epub 2021 Mar 20. PMID: 33757833; PMCID: PMC8724861.
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Feature Selection Methods for Protein Biomarker Discovery from Proteomics or Multiomics Data.

Molecular & cellular proteomics : MCP

Shi Z, Wen B, Gao Q, Zhang B.
PMID: 33887487
Mol Cell Proteomics. 2021;20:100083. doi: 10.1016/j.mcpro.2021.100083. Epub 2021 Apr 20.

Untargeted mass spectrometry (MS)-based proteomics provides a powerful platform for protein biomarker discovery, but clinical translation depends on the selection of a small number of proteins for downstream verification and validation. Due to the small sample size of typical...

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Shi Z, Wen B, Gao Q, et al. Feature Selection Methods for Protein Biomarker Discovery from Proteomics or Multiomics Data. Mol Cell Proteomics. 2021;20:100083doi: 10.1016/j.mcpro.2021.100083.
Shi, Z., Wen, B., Gao, Q., & Zhang, B. (2021). Feature Selection Methods for Protein Biomarker Discovery from Proteomics or Multiomics Data. Molecular & cellular proteomics : MCP, 20100083. https://doi.org/10.1016/j.mcpro.2021.100083
Shi, Zhiao, et al. "Feature Selection Methods for Protein Biomarker Discovery from Proteomics or Multiomics Data." Molecular & cellular proteomics : MCP vol. 20 (2021): 100083. doi: https://doi.org/10.1016/j.mcpro.2021.100083
Shi Z, Wen B, Gao Q, Zhang B. Feature Selection Methods for Protein Biomarker Discovery from Proteomics or Multiomics Data. Mol Cell Proteomics. 2021;20:100083. doi: 10.1016/j.mcpro.2021.100083. Epub 2021 Apr 20. PMID: 33887487; PMCID: PMC8165452.
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The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires.

Molecular & cellular proteomics : MCP

Parker R, Tailor A, Peng X, Nicastri A, Zerweck J, Reimer U, Wenschuh H, Schnatbaum K, Ternette N.
PMID: 34303857
Mol Cell Proteomics. 2021;20:100124. doi: 10.1016/j.mcpro.2021.100124. Epub 2021 Jul 23.

Standardization of immunopeptidomics experiments across laboratories is a pressing issue within the field, and currently a variety of different methods for sample preparation and data analysis tools are applied. Here, we compared different software packages to interrogate immunopeptidomics datasets...

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Parker R, Tailor A, Peng X, et al. The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires. Mol Cell Proteomics. 2021;20:100124doi: 10.1016/j.mcpro.2021.100124.
Parker, R., Tailor, A., Peng, X., Nicastri, A., Zerweck, J., Reimer, U., Wenschuh, H., Schnatbaum, K., & Ternette, N. (2021). The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires. Molecular & cellular proteomics : MCP, 20100124. https://doi.org/10.1016/j.mcpro.2021.100124
Parker, Robert, et al. "The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires." Molecular & cellular proteomics : MCP vol. 20 (2021): 100124. doi: https://doi.org/10.1016/j.mcpro.2021.100124
Parker R, Tailor A, Peng X, Nicastri A, Zerweck J, Reimer U, Wenschuh H, Schnatbaum K, Ternette N. The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires. Mol Cell Proteomics. 2021;20:100124. doi: 10.1016/j.mcpro.2021.100124. Epub 2021 Jul 23. PMID: 34303857; PMCID: PMC8724928.
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Change in Publication Schedule.

Molecular & cellular proteomics : MCP

Hodak H.
PMID: 34922281
Mol Cell Proteomics. 2021 Dec 15;21(1):100161. doi: 10.1016/j.mcpro.2021.100161. Epub 2021 Dec 15.

No abstract available.

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Hodak H. Change in Publication Schedule. Mol Cell Proteomics. 2021;21(1):100161doi: 10.1016/j.mcpro.2021.100161.
Hodak, H. (2021). Change in Publication Schedule. Molecular & cellular proteomics : MCP, 21(1), 100161. https://doi.org/10.1016/j.mcpro.2021.100161
Hodak, Hélène. "Change in Publication Schedule." Molecular & cellular proteomics : MCP vol. 21,1 (2021): 100161. doi: https://doi.org/10.1016/j.mcpro.2021.100161
Hodak H. Change in Publication Schedule. Mol Cell Proteomics. 2021 Dec 15;21(1):100161. doi: 10.1016/j.mcpro.2021.100161. Epub 2021 Dec 15. PMID: 34922281.
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Calculating Sample Size Requirements for Temporal Dynamics in Single-Cell Proteomics.

Molecular & cellular proteomics : MCP

Boekweg H, Guise AJ, Plowey ED, Kelly RT, Payne SH.
PMID: 33915259
Mol Cell Proteomics. 2021;20:100085. doi: 10.1016/j.mcpro.2021.100085. Epub 2021 Apr 27.

Single-cell measurements are uniquely capable of characterizing cell-to-cell heterogeneity and have been used to explore the large diversity of cell types and physiological functions present in tissues and other complex cell assemblies. An intriguing application of single-cell proteomics is...

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Boekweg H, Guise AJ, Plowey ED, et al. Calculating Sample Size Requirements for Temporal Dynamics in Single-Cell Proteomics. Mol Cell Proteomics. 2021;20:100085doi: 10.1016/j.mcpro.2021.100085.
Boekweg, H., Guise, A. J., Plowey, E. D., Kelly, R. T., & Payne, S. H. (2021). Calculating Sample Size Requirements for Temporal Dynamics in Single-Cell Proteomics. Molecular & cellular proteomics : MCP, 20100085. https://doi.org/10.1016/j.mcpro.2021.100085
Boekweg, Hannah, et al. "Calculating Sample Size Requirements for Temporal Dynamics in Single-Cell Proteomics." Molecular & cellular proteomics : MCP vol. 20 (2021): 100085. doi: https://doi.org/10.1016/j.mcpro.2021.100085
Boekweg H, Guise AJ, Plowey ED, Kelly RT, Payne SH. Calculating Sample Size Requirements for Temporal Dynamics in Single-Cell Proteomics. Mol Cell Proteomics. 2021;20:100085. doi: 10.1016/j.mcpro.2021.100085. Epub 2021 Apr 27. PMID: 33915259; PMCID: PMC8165548.
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Showing 1 to 12 of 665 entries