On the Dependency of Cellular Protein Levels on mRNA Abundance

[1]  M. Mann,et al.  Proteomic maps of breast cancer subtypes , 2016, Nature Communications.

[2]  Voichita D. Marinescu,et al.  Simultaneous Multiplexed Measurement of RNA and Proteins in Single Cells , 2015, Cell reports.

[3]  S. Itzkovitz,et al.  Nuclear Retention of mRNA in Mammalian Tissues , 2015, Cell reports.

[4]  L. Pelkmans,et al.  Control of Transcript Variability in Single Mammalian Cells , 2015, Cell.

[5]  J. Doudna,et al.  Tunable protein synthesis by transcript isoforms in human cells , 2015, bioRxiv.

[6]  Matthias Mann,et al.  Cell type– and brain region–resolved mouse brain proteome , 2015, Nature Neuroscience.

[7]  Hiromi W L Koh,et al.  Differential dynamics of the mammalian mRNA and protein expression response to misfolding stress , 2015, bioRxiv.

[8]  Allon M. Klein,et al.  On the Relationship of Protein and mRNA Dynamics in Vertebrate Embryonic Development. , 2015, Developmental cell.

[9]  Peer Bork,et al.  Integrated Transcriptome and Proteome Analyses Reveal Organ-Specific Proteome Deterioration in Old Rats , 2015, Cell systems.

[10]  C. Vogel,et al.  Next-generation analysis of gene expression regulation--comparing the roles of synthesis and degradation. , 2015, Molecular bioSystems.

[11]  J. Weissman,et al.  Regulation of mRNA translation during mitosis , 2015, eLife.

[12]  Michael P Snyder,et al.  Integrative analysis of RNA, translation, and protein levels reveals distinct regulatory variation across humans , 2015, Genome research.

[13]  Ruedi Aebersold,et al.  Absolute Proteome Composition and Dynamics during Dormancy and Resuscitation of Mycobacterium tuberculosis. , 2015, Cell host & microbe.

[14]  Hongye Li,et al.  Evolution of Gene Regulation during Transcription and Translation , 2015, Genome biology and evolution.

[15]  Mark D. Biggin,et al.  Statistics requantitates the central dogma , 2015, Science.

[16]  Maxwell R. Mumbach,et al.  Dynamic profiling of the protein life cycle in response to pathogens , 2015, Science.

[17]  P. Hoen,et al.  Alternative mRNA transcription, processing, and translation: insights from RNA sequencing , 2015 .

[18]  Oliver M. Bernhardt,et al.  Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues* , 2015, Molecular & Cellular Proteomics.

[19]  P. Khaitovich,et al.  Transcript and protein expression decoupling reveals RNA binding proteins and miRNAs as potential modulators of human aging , 2015, Genome Biology.

[20]  Alexis Battle,et al.  Impact of regulatory variation from RNA to protein , 2015, Science.

[21]  Fabian J Theis,et al.  Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells , 2015, Nature Biotechnology.

[22]  Ruedi Aebersold,et al.  Quantitative variability of 342 plasma proteins in a human twin population , 2015 .

[23]  G. von Heijne,et al.  Tissue-based map of the human proteome , 2015, Science.

[24]  Oliver M. Bernhardt,et al.  Reproducible and Consistent Quantification of the Saccharomyces cerevisiae Proteome by SWATH-mass spectrometry* , 2015, Molecular & Cellular Proteomics.

[25]  Daniel M Bader,et al.  Negative feedback buffers effects of regulatory variants , 2015, Molecular systems biology.

[26]  P. ’. ‘t Hoen,et al.  Alternative mRNA transcription, processing, and translation: insights from RNA sequencing. , 2015, Trends in genetics : TIG.

[27]  M. Mann,et al.  Cell-type-resolved quantitative proteomics of murine liver. , 2014, Cell metabolism.

[28]  Paul Taylor,et al.  Integrated Omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact , 2014, Nature Communications.

[29]  D. Gresham,et al.  Determination of in vivo RNA kinetics using RATE-seq , 2014, RNA.

[30]  S. Mathavan,et al.  Functional mapping of the zebrafish early embryo proteome and transcriptome. , 2014, Journal of proteome research.

[31]  Marco Y. Hein,et al.  A “Proteomic Ruler” for Protein Copy Number and Concentration Estimation without Spike-in Standards* , 2014, Molecular & Cellular Proteomics.

[32]  David P. Kreil,et al.  The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance , 2014, Nature Biotechnology.

[33]  M. Zavolan,et al.  Identification and consequences of miRNA–target interactions — beyond repression of gene expression , 2014, Nature Reviews Genetics.

[34]  Evan G. Williams,et al.  Multilayered Genetic and Omics Dissection of Mitochondrial Activity in a Mouse Reference Population , 2014, Cell.

[35]  David P. Kreil,et al.  A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control consortium , 2014, Nature Biotechnology.

[36]  S. Gygi,et al.  Quantitative proteomic analysis reveals posttranslational responses to aneuploidy in yeast , 2014, eLife.

[37]  Manikandan Narayanan,et al.  Characterization of Functional Reprogramming during Osteoclast Development Using Quantitative Proteomics and mRNA Profiling* , 2014, Molecular & Cellular Proteomics.

[38]  Jeffrey R. Whiteaker,et al.  Proteogenomic characterization of human colon and rectal cancer , 2014, Nature.

[39]  C. Perou,et al.  Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling , 2014, BMC Genomics.

[40]  Gavin Sherlock,et al.  Extensive and coordinated control of allele-specific expression by both transcription and translation in Candida albicans , 2014, Genome research.

[41]  L. Ponnala,et al.  Correlation of mRNA and protein abundance in the developing maize leaf. , 2014, The Plant journal : for cell and molecular biology.

[42]  David H Burkhardt,et al.  Quantifying Absolute Protein Synthesis Rates Reveals Principles Underlying Allocation of Cellular Resources , 2014, Cell.

[43]  J. Buhmann,et al.  Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry , 2014, Nature Methods.

[44]  Tamar Geiger,et al.  Genome-wide identification and quantification of protein synthesis in cultured cells and whole tissues by puromycin-associated nascent chain proteomics (PUNCH-P) , 2014, Nature Protocols.

[45]  Leonid Kruglyak,et al.  Genetic Influences on Translation in Yeast , 2014, bioRxiv.

[46]  S. Sanyal,et al.  Organization of Ribosomes and Nucleoids in Escherichia coli Cells during Growth and in Quiescence* , 2014, The Journal of Biological Chemistry.

[47]  M. Mann,et al.  Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cells , 2014, Nature Methods.

[48]  Nicholas T. Ingolia.  Ribosome profiling: new views of translation, from single codons to genome scale , 2014, Nature Reviews Genetics.

[49]  Sean M. Grimmond,et al.  SnapShot-Seq: A Method for Extracting Genome-Wide, In Vivo mRNA Dynamics from a Single Total RNA Sample , 2014, PloS one.

[50]  I. Amit,et al.  Massively Parallel Single-Cell RNA-Seq for Marker-Free Decomposition of Tissues into Cell Types , 2014, Science.

[51]  N. Rajewsky,et al.  Conservation of mRNA and protein expression during development of C. elegans. , 2014, Cell reports.

[52]  Michael B. Black,et al.  Comparison of microarrays and RNA-seq for gene expression analyses of dose-response experiments. , 2014, Toxicological sciences : an official journal of the Society of Toxicology.

[53]  R. Aebersold,et al.  CHAPTER 4:Getting Absolute: Determining Absolute Protein Quantities via Selected Reaction Monitoring Mass Spectrometry , 2014 .

[54]  Katrin Eichelbaum,et al.  Rapid Temporal Dynamics of Transcription, Protein Synthesis, and Secretion during Macrophage Activation* , 2014, Molecular & Cellular Proteomics.

[55]  Hyungwon Choi,et al.  PECA: a novel statistical tool for deconvoluting time-dependent gene expression regulation. , 2014, Journal of proteome research.

[56]  M. Mann,et al.  In-Vivo Quantitative Proteomics Reveals a Key Contribution of Post-Transcriptional Mechanisms to the Circadian Regulation of Liver Metabolism , 2014, PLoS genetics.

[57]  Gemma E. May,et al.  Ribosome profiling reveals post-transcriptional buffering of divergent gene expression in yeast , 2013, Genome research.

[58]  Hunter B. Fraser,et al.  Evolution at two levels of gene expression in yeast , 2013, Genome research.

[59]  P. Bickel,et al.  System wide analyses have underestimated protein abundances and the importance of transcription in mammals , 2012, PeerJ.

[60]  Ido Golding,et al.  Genetic Determinants and Cellular Constraints in Noisy Gene Expression , 2013, Science.

[61]  Karl Mechtler,et al.  Transcriptome and proteome quantification of a tumor model provides novel insights into post‐transcriptional gene regulation , 2013, Genome Biology.

[62]  Jonathan K. Pritchard,et al.  Primate Transcript and Protein Expression Levels Evolve Under Compensatory Selection Pressures , 2013, Science.

[63]  Ruedi Aebersold,et al.  Mass spectrometric protein maps for biomarker discovery and clinical research , 2013, Expert review of molecular diagnostics.

[64]  Miler T. Lee,et al.  Nanog, Pou5f1 and SoxB1 activate zygotic gene expression during the maternal-to-zygotic transition , 2013, Nature.

[65]  R. Milo.  What is the total number of protein molecules per cell volume? A call to rethink some published values , 2013, BioEssays : news and reviews in molecular, cellular and developmental biology.

[66]  L. Foster,et al.  Protein synthesis rate is the predominant regulator of protein expression during differentiation , 2013, Molecular systems biology.

[67]  Tamar Geiger,et al.  Novel proteomic approach (PUNCH-P) reveals cell cycle-specific fluctuations in mRNA translation , 2013, Genes & development.

[68]  Mathias Wilhelm,et al.  Global proteome analysis of the NCI-60 cell line panel. , 2013, Cell reports.

[69]  J. Plotkin,et al.  Rate-Limiting Steps in Yeast Protein Translation , 2013, Cell.

[70]  Jeff Hasty,et al.  Translational cross talk in gene networks. , 2013, Biophysical journal.

[71]  Nicholas T. Ingolia,et al.  Ribosome Profiling Provides Evidence that Large Noncoding RNAs Do Not Encode Proteins , 2013, Cell.

[72]  Ruedi Aebersold,et al.  The Mtb proteome library: a resource of assays to quantify the complete proteome of Mycobacterium tuberculosis. , 2013, Cell host & microbe.

[73]  Bing Zhang,et al.  Integrative Omics Analysis Reveals the Importance and Scope of Translational Repression in microRNA-mediated Regulation , 2013, Molecular & Cellular Proteomics.

[74]  Eric W. Deutsch,et al.  A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis , 2013, Nature.

[75]  Yun-chi Tang,et al.  Gene Copy-Number Alterations: A Cost-Benefit Analysis , 2013, Cell.

[76]  Angus I. Lamond,et al.  Global Subcellular Characterization of Protein Degradation Using Quantitative Proteomics , 2012, Molecular & Cellular Proteomics.

[77]  R. Beynon,et al.  Proteome Dynamics: Revisiting Turnover with a Global Perspective* , 2012, Molecular & Cellular Proteomics.

[78]  R. Aebersold,et al.  Quantitative Analysis of Fission Yeast Transcriptomes and Proteomes in Proliferating and Quiescent Cells , 2012, Cell.

[79]  M. Mann,et al.  Global analysis of genome, transcriptome and proteome reveals the response to aneuploidy in human cells , 2012, Molecular Systems Biology.

[80]  T. Gedeon,et al.  Delayed protein synthesis reduces the correlation between mRNA and protein fluctuations. , 2012, Biophysical journal.

[81]  R. Aebersold,et al.  Selected reaction monitoring–based proteomics: workflows, potential, pitfalls and future directions , 2012, Nature Methods.

[82]  Nicholas T. Ingolia,et al.  The translational landscape of mTOR signalling steers cancer initiation and metastasis , 2012, Nature.

[83]  L. Aravind,et al.  Interplay between gene expression noise and regulatory network architecture. , 2012, Trends in genetics : TIG.

[84]  Sue Fletcher,et al.  Regulation of eukaryotic gene expression by the untranslated gene regions and other non-coding elements , 2012, Cellular and Molecular Life Sciences.

[85]  Margaret S. Ebert,et al.  Roles for MicroRNAs in Conferring Robustness to Biological Processes , 2012, Cell.

[86]  E. Marcotte,et al.  Insights into the regulation of protein abundance from proteomic and transcriptomic analyses , 2012, Nature Reviews Genetics.

[87]  P. A. Futreal,et al.  Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. , 2012, The New England journal of medicine.

[88]  Ludovic C. Gillet,et al.  Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis* , 2012, Molecular & Cellular Proteomics.

[89]  Nicholas T. Ingolia,et al.  High-Resolution View of the Yeast Meiotic Program Revealed by Ribosome Profiling , 2011, Science.

[90]  Jürg Bähler,et al.  Regulation of transcriptome, translation, and proteome in response to environmental stress in fission yeast , 2012, Genome Biology.

[91]  Ruedi Aebersold,et al.  Estimation of Absolute Protein Quantities of Unlabeled Samples by Selected Reaction Monitoring Mass Spectrometry , 2011, Molecular & Cellular Proteomics.

[92]  J. Ellenberg,et al.  The quantitative proteome of a human cell line , 2011, Molecular systems biology.

[93]  M. Mann,et al.  Systems-wide proteomic analysis in mammalian cells reveals conserved, functional protein turnover. , 2011, Journal of proteome research.

[94]  K. Dill,et al.  Physical limits of cells and proteomes , 2011, Proceedings of the National Academy of Sciences.

[95]  Michelle S. Scott,et al.  A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells* , 2011, Molecular & Cellular Proteomics.

[96]  A. Gasch,et al.  Molecular Systems Biology Peer Review Process File a Dynamic Model of Proteome Changes Reveals New Roles for Transcript Alteration in Yeast Transaction Report , 2022 .

[97]  Reinhard Guthke,et al.  Optimal regulatory strategies for metabolic pathways in Escherichia coli depending on protein costs , 2011, Molecular Systems Biology.

[98]  Henry H. N. Lam,et al.  Absolute quantification of microbial proteomes at different states by directed mass spectrometry , 2011, Molecular systems biology.

[99]  Dominique Chu,et al.  The role of tRNA and ribosome competition in coupling the expression of different mRNAs in Saccharomyces cerevisiae , 2011, Nucleic acids research.

[100]  M. Selbach,et al.  Global quantification of mammalian gene expression control , 2011, Nature.

[101]  N. Friedman,et al.  Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells , 2011, Nature Biotechnology.

[102]  Uri Alon,et al.  Proteome Half-Life Dynamics in Living Human Cells , 2011, Science.

[103]  Robert H. Singer,et al.  Transcription of functionally related constitutive genes is not coordinated , 2010, Nature Structural &Molecular Biology.

[104]  M. Mann,et al.  Defining the transcriptome and proteome in three functionally different human cell lines , 2010, Molecular systems biology.

[105]  E. Lundberg,et al.  Towards a knowledge-based Human Protein Atlas , 2010, Nature Biotechnology.

[106]  Harkamal Walia,et al.  Protein abundances are more conserved than mRNA abundances across diverse taxa , 2010, Proteomics.

[107]  R. Aebersold,et al.  A quantitative targeted proteomics approach to validate predicted microRNA targets in C. elegans , 2010, Nature Methods.

[108]  Klaus Wethmar,et al.  Upstream open reading frames: Molecular switches in (patho)physiology , 2010, BioEssays : news and reviews in molecular, cellular and developmental biology.

[109]  Matthias Mann,et al.  Proteomic Changes Resulting from Gene Copy Number Variations in Cancer Cells , 2010, PLoS genetics.

[110]  Paul J. Choi,et al.  Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells , 2010, Science.

[111]  S. Cohen,et al.  MicroRNAs and gene regulatory networks: managing the impact of noise in biological systems. , 2010, Genes & development.

[112]  Elizabeth A. Calle,et al.  Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells , 2010, Science.

[113]  Luis Serrano,et al.  Correlation of mRNA and protein in complex biological samples , 2009, FEBS letters.

[114]  E. Marcotte,et al.  Global signatures of protein and mRNA expression levelsw , 2009 .

[115]  Norman Pavelka,et al.  Delayed Correlation of mRNA and Protein Expression in Rapamycin-treated Cells and a Role for Ggc1 in Cellular Sensitivity to Rapamycin* , 2009, Molecular & Cellular Proteomics.

[116]  F. Markowetz,et al.  Systems-level dynamic analyses of fate change in murine embryonic stem cells , 2009, Nature.

[117]  L. Dölken,et al.  Metabolic tagging and purification of nascent RNA: implications for transcriptomics. , 2009, Molecular bioSystems.

[118]  P. Liberali,et al.  Population context determines cell-to-cell variability in endocytosis and virus infection , 2009, Nature.

[119]  R. Aebersold,et al.  Proteome-wide cellular protein concentrations of the human pathogen Leptospira interrogans , 2009, Nature.

[120]  Nicholas T. Ingolia,et al.  Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling , 2009, Science.

[121]  R. Aebersold,et al.  Comparative Functional Analysis of the Caenorhabditis elegans and Drosophila melanogaster Proteomes , 2009, PLoS biology.

[122]  K. Martin,et al.  mRNA Localization: Gene Expression in the Spatial Dimension , 2009, Cell.

[123]  M. Gerstein,et al.  RNA-Seq: a revolutionary tool for transcriptomics , 2009, Nature Reviews Genetics.

[124]  Florence Besse,et al.  Translational control of localized mRNAs: restricting protein synthesis in space and time , 2008, Nature Reviews Molecular Cell Biology.

[125]  Qikai Xu,et al.  Global Protein Stability Profiling in Mammalian Cells , 2008, Science.

[126]  M. Mann,et al.  Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast , 2008, Nature.

[127]  B. Williams,et al.  Mapping and quantifying mammalian transcriptomes by RNA-Seq , 2008, Nature Methods.

[128]  D. Hochstrasser,et al.  Relative quantification of proteins in human cerebrospinal fluids by MS/MS using 6-plex isobaric tags. , 2008, Analytical chemistry.

[129]  Jennifer L. Osborn,et al.  Direct multiplexed measurement of gene expression with color-coded probe pairs , 2008, Nature Biotechnology.

[130]  Naama Barkai,et al.  Noise Propagation and Signaling Sensitivity in Biological Networks: A Role for Positive Feedback , 2007, PLoS Comput. Biol..

[131]  Matthew J. Brauer,et al.  Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast. , 2008, Molecular biology of the cell.

[132]  Blagoy Blagoev,et al.  Quantitative proteomic assessment of very early cellular signaling events , 2007, Nature Biotechnology.

[133]  Andreas Beyer,et al.  Posttranscriptional Expression Regulation: What Determines Translation Rates? , 2007, PLoS Comput. Biol..

[134]  E. Marcotte,et al.  Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation , 2007, Nature Biotechnology.

[135]  M. Washburn,et al.  Quantitative proteomic analysis of distinct mammalian Mediator complexes using normalized spectral abundance factors , 2006, Proceedings of the National Academy of Sciences.

[136]  Richard Bonneau,et al.  Quantitative proteomic analysis of the budding yeast cell cycle using acid‐cleavable isotope‐coded affinity tag reagents , 2006, Proteomics.

[137]  K. Nakayama,et al.  Ubiquitin ligases: cell-cycle control and cancer , 2006, Nature Reviews Cancer.

[138]  R. Aebersold,et al.  Mass Spectrometry and Protein Analysis , 2006, Science.

[139]  K. Resing,et al.  Comparison of Label-free Methods for Quantifying Human Proteins by Shotgun Proteomics*S , 2005, Molecular & Cellular Proteomics.

[140]  M. Mann,et al.  Exponentially Modified Protein Abundance Index (emPAI) for Estimation of Absolute Protein Amount in Proteomics by the Number of Sequenced Peptides per Protein*S , 2005, Molecular & Cellular Proteomics.

[141]  U. Alon,et al.  Optimality and evolutionary tuning of the expression level of a protein , 2005, Nature.

[142]  P. Bork,et al.  Dynamic Complex Formation During the Yeast Cell Cycle , 2005, Science.

[143]  K. Parker,et al.  Multiplexed Protein Quantitation in Saccharomyces cerevisiae Using Amine-reactive Isobaric Tagging Reagents*S , 2004, Molecular & Cellular Proteomics.

[144]  Andreas Beyer,et al.  Post-transcriptional Expression Regulation in the Yeast Saccharomyces cerevisiae on a Genomic Scale*S , 2004, Molecular & Cellular Proteomics.

[145]  Yingyao Zhou,et al.  Global analysis of transcript and protein levels across the Plasmodium falciparum life cycle. , 2004, Genome research.

[146]  J. Yates,et al.  A model for random sampling and estimation of relative protein abundance in shotgun proteomics. , 2004, Analytical chemistry.

[147]  E. O’Shea,et al.  Global analysis of protein expression in yeast , 2003, Nature.

[148]  S. Gygi,et al.  Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[149]  Mads Kærn,et al.  Noise in eukaryotic gene expression , 2003, Nature.

[150]  John D. Storey,et al.  Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[151]  R. Aebersold,et al.  Mass spectrometry-based proteomics , 2003, Nature.

[152]  M. Mann,et al.  Stable Isotope Labeling by Amino Acids in Cell Culture, SILAC, as a Simple and Accurate Approach to Expression Proteomics* , 2002, Molecular & Cellular Proteomics.

[153]  Krishnamurthy Natarajan,et al.  Gcn4p, a Master Regulator of Gene Expression, Is Controlled at Multiple Levels by Diverse Signals of Starvation and Stress , 2002, Eukaryotic Cell.

[154]  J. Warner,et al.  The economics of ribosome biosynthesis in yeast. , 1999, Trends in biochemical sciences.

[155]  S. Gygi,et al.  Quantitative analysis of complex protein mixtures using isotope-coded affinity tags , 1999, Nature Biotechnology.

[156]  S. Gygi,et al.  Correlation between Protein and mRNA Abundance in Yeast , 1999, Molecular and Cellular Biology.

[157]  Michael R. Green,et al.  Gene Expression , 1993, Progress in Gene Expression.

[158]  K. Kellerman,et al.  Mutations affecting the stability of the fushi tarazu protein of Drosophila. , 1990, Genes & development.

[159]  Alexander Varshavsky,et al.  In vivo degradation of a transcriptional regulator: The yeast α2 repressor , 1990, Cell.

[160]  A. Varshavsky,et al.  In vivo degradation of a transcriptional regulator: the yeast alpha 2 repressor. , 1990, Cell.

[161]  Y. Tsay,et al.  Ribosomal protein synthesis is not regulated at the translational level in Saccharomyces cerevisiae: balanced accumulation of ribosomal proteins L16 and rp59 is mediated by turnover of excess protein. , 1988, Genes & development.

[162]  P. O’Farrell.  High resolution two-dimensional electrophoresis of proteins. , 1975, The Journal of biological chemistry.