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Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments
by
Derks, Jason
, Emmott, Edward
, Perlman, David H.
, Yates, John R.
, Demichev, Vadim
, MacCoss, Michael J.
, Khoury, Luke
, Rose, Christopher M.
, Franks, Alexander M.
, Leduc, Andrew
, Kelly, Ryan T.
, Vanderaa, Christophe
, Aebersold, Ruedi
, Ivanov, Alexander R.
, Cox, Juergen
, Schoof, Erwin M.
, Van Eyk, Jennifer
, Petelski, Aleksandra A.
, Gatto, Laurent
, Nemes, Peter
, Slavov, Nikolai
in
631/1647/2067
/ 631/1647/296
/ 631/45/475
/ 706/648/697
/ Benchmarking - methods
/ Best practice
/ Biochemistry
/ Bioengineering
/ Bioinformatics
/ Biological Microscopy
/ Biological Techniques
/ Biology
/ Biomedical and Life Sciences
/ Biomedical Engineering/Biotechnology
/ Cells
/ Chemistry
/ Computer applications
/ Data acquisition
/ Data analysis
/ Data processing
/ Design factors
/ Design of experiments
/ Experimental design
/ Flow cytometry
/ Guidelines
/ Life Sciences
/ Mass spectrometry
/ Mass spectroscopy
/ Neurosciences
/ Perspective
/ Proteins
/ Proteins - analysis
/ Proteome - analysis
/ Proteomics
/ Proteomics - methods
/ Reproducibility
/ Reproducibility of Results
/ Sample preparation
/ Tandem Mass Spectrometry - methods
2023
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Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments
by
Derks, Jason
, Emmott, Edward
, Perlman, David H.
, Yates, John R.
, Demichev, Vadim
, MacCoss, Michael J.
, Khoury, Luke
, Rose, Christopher M.
, Franks, Alexander M.
, Leduc, Andrew
, Kelly, Ryan T.
, Vanderaa, Christophe
, Aebersold, Ruedi
, Ivanov, Alexander R.
, Cox, Juergen
, Schoof, Erwin M.
, Van Eyk, Jennifer
, Petelski, Aleksandra A.
, Gatto, Laurent
, Nemes, Peter
, Slavov, Nikolai
in
631/1647/2067
/ 631/1647/296
/ 631/45/475
/ 706/648/697
/ Benchmarking - methods
/ Best practice
/ Biochemistry
/ Bioengineering
/ Bioinformatics
/ Biological Microscopy
/ Biological Techniques
/ Biology
/ Biomedical and Life Sciences
/ Biomedical Engineering/Biotechnology
/ Cells
/ Chemistry
/ Computer applications
/ Data acquisition
/ Data analysis
/ Data processing
/ Design factors
/ Design of experiments
/ Experimental design
/ Flow cytometry
/ Guidelines
/ Life Sciences
/ Mass spectrometry
/ Mass spectroscopy
/ Neurosciences
/ Perspective
/ Proteins
/ Proteins - analysis
/ Proteome - analysis
/ Proteomics
/ Proteomics - methods
/ Reproducibility
/ Reproducibility of Results
/ Sample preparation
/ Tandem Mass Spectrometry - methods
2023
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Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments
by
Derks, Jason
, Emmott, Edward
, Perlman, David H.
, Yates, John R.
, Demichev, Vadim
, MacCoss, Michael J.
, Khoury, Luke
, Rose, Christopher M.
, Franks, Alexander M.
, Leduc, Andrew
, Kelly, Ryan T.
, Vanderaa, Christophe
, Aebersold, Ruedi
, Ivanov, Alexander R.
, Cox, Juergen
, Schoof, Erwin M.
, Van Eyk, Jennifer
, Petelski, Aleksandra A.
, Gatto, Laurent
, Nemes, Peter
, Slavov, Nikolai
in
631/1647/2067
/ 631/1647/296
/ 631/45/475
/ 706/648/697
/ Benchmarking - methods
/ Best practice
/ Biochemistry
/ Bioengineering
/ Bioinformatics
/ Biological Microscopy
/ Biological Techniques
/ Biology
/ Biomedical and Life Sciences
/ Biomedical Engineering/Biotechnology
/ Cells
/ Chemistry
/ Computer applications
/ Data acquisition
/ Data analysis
/ Data processing
/ Design factors
/ Design of experiments
/ Experimental design
/ Flow cytometry
/ Guidelines
/ Life Sciences
/ Mass spectrometry
/ Mass spectroscopy
/ Neurosciences
/ Perspective
/ Proteins
/ Proteins - analysis
/ Proteome - analysis
/ Proteomics
/ Proteomics - methods
/ Reproducibility
/ Reproducibility of Results
/ Sample preparation
/ Tandem Mass Spectrometry - methods
2023
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Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments
Journal Article
Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments
2023
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Overview
Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at
https://single-cell.net/guidelines
.
A community of researchers working in the emerging field of single-cell proteomics propose best-practice experimental and computational recommendations and reporting guidelines for studies analyzing proteins from single cells by mass spectrometry.
Publisher
Nature Publishing Group US,Nature Publishing Group
Subject
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