Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings.

[1]  D. Vrazhnov,et al.  Supplemental Materials , 2021, Medical Applications of Laser Molecular Imaging and Machine Learning.

[2]  E. Mohammadi,et al.  Barriers and facilitators related to the implementation of a physiological track and trigger system: A systematic review of the qualitative evidence , 2017, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[3]  Jennifer E. Gilda,et al.  The necessity of and strategies for improving confidence in the accuracy of western blots , 2014, Expert review of proteomics.

[4]  C. Parikh,et al.  Key concepts and limitations of statistical methods for evaluating biomarkers of kidney disease. , 2014, Journal of the American Society of Nephrology : JASN.

[5]  Hui Zhang,et al.  Cardiac extracellular proteome profiling and membrane topology analysis using glycoproteomics , 2014, Proteomics. Clinical applications.

[6]  Nobel C. Zong,et al.  Lysine ubiquitination and acetylation of human cardiac 20S proteasomes , 2014, Proteomics. Clinical applications.

[7]  G. Agnetti,et al.  Protein post‐translational modifications and misfolding: New concepts in heart failure , 2014, Proteomics. Clinical applications.

[8]  Jennifer E Van Eyk,et al.  Identification of cardiac myofilament protein isoforms using multiple mass spectrometry based approaches , 2014, Proteomics. Clinical applications.

[9]  Melanie Y. White,et al.  The role of post‐translational modifications in acute and chronic cardiovascular disease , 2014, Proteomics. Clinical applications.

[10]  J. Sokolove,et al.  Proteomics of citrullination in cardiovascular disease , 2014, Proteomics. Clinical applications.

[11]  Deyang Yu,et al.  Top‐down mass spectrometry of cardiac myofilament proteins in health and disease , 2014, Proteomics. Clinical applications.

[12]  T. Vondriska,et al.  Epigenomes: The missing heritability in human cardiovascular disease? , 2014, Proteomics. Clinical applications.

[13]  J. V. Van Eyk,et al.  Cardiovascular disease: The leap towards translational and clinical proteomics , 2014, Proteomics. Clinical applications.

[14]  Pingbo Zhang,et al.  Targeted proteomics of myofilament phosphorylation and other protein posttranslational modifications , 2014, Proteomics. Clinical applications.

[15]  L. Mbuagbaw,et al.  Performance of the high-sensitivity troponin assay in diagnosing acute myocardial infarction: systematic review and meta-analysis. , 2014, CMAJ open.

[16]  Brian J. Bleakley,et al.  Abstract 353: Characterization Of Human Plasma Proteome Dynamics Using Deuterium Oxide , 2014 .

[17]  J. Canty,et al.  Quantitative proteomics in cardiovascular research: Global and targeted strategies , 2014, Proteomics. Clinical applications.

[18]  S. Sadayappan,et al.  Surviving the infarct: A profile of cardiac myosin binding protein-C pathogenicity, diagnostic utility, and proteomics in the ischemic myocardium , 2014, Proteomics. Clinical applications.

[19]  D. Lacaille,et al.  2013 ACC/AHA guideline on the assessment of cardiovascular risk. , 2014, Journal of the American College of Cardiology.

[20]  Ying Ge,et al.  Top-down Proteomics Reveals Concerted Reductions in Myofilament and Z-disc Protein Phosphorylation after Acute Myocardial Infarction* , 2014, Molecular & Cellular Proteomics.

[21]  A. Galande,et al.  Sample collection in clinical proteomics—Proteolytic activity profile of serum and plasma , 2014, Proteomics. Clinical applications.

[22]  Gary D Bader,et al.  A draft map of the human proteome , 2014, Nature.

[23]  B. Kuster,et al.  Mass-spectrometry-based draft of the human proteome , 2014, Nature.

[24]  J. Zoidakis,et al.  Mass spectrometry-based membrane proteomics in cancer biomarker discovery , 2014, Expert review of molecular diagnostics.

[25]  K. Blennow,et al.  Cerebrospinal fluid analysis in Alzheimer’s disease: technical issues and future developments , 2014, Journal of Neurology.

[26]  Jared B Shaw,et al.  The first pilot project of the consortium for top‐down proteomics: A status report , 2014, Proteomics.

[27]  Sanjeeva Srivastava,et al.  Challenges and prospects for biomarker research: a current perspective from the developing world. , 2014, Biochimica et biophysica acta.

[28]  Sandro Santagata,et al.  Artifacts to avoid while taking advantage of top‐down mass spectrometry based detection of protein S‐thiolation , 2014, Proteomics.

[29]  M. Eisenacher,et al.  The Membrane Proteome of Sensory Cilia to the Depth of Olfactory Receptors* , 2014, Molecular & Cellular Proteomics.

[30]  Je-Hyun Baek,et al.  Reciprocal Changes in Phosphorylation and Methylation of Mammalian Brain Sodium Channels in Response to Seizures* , 2014, The Journal of Biological Chemistry.

[31]  B. Domon,et al.  A simple protocol to routinely assess the uniformity of proteomics analyses. , 2014, Journal of proteome research.

[32]  E. P. Hudson,et al.  Proteome-wide Epitope Mapping of Antibodies Using Ultra-dense Peptide Arrays* , 2014, Molecular & Cellular Proteomics.

[33]  C. Baines,et al.  Proteomic mapping of proteins released during necrosis and apoptosis from cultured neonatal cardiac myocytes. , 2014, American journal of physiology. Cell physiology.

[34]  U. Walter,et al.  What can proteomics tell us about platelets? , 2014, Circulation research.

[35]  W. Cho Proteomics in translational cancer research: biomarker discovery for clinical applications , 2014, Expert review of proteomics.

[36]  J. Hernandez-Fernaud,et al.  Quantitative phosphoproteomics unveils temporal dynamics of thrombin signaling in human endothelial cells. , 2014, Blood.

[37]  Ying Ge,et al.  Proteomics in heart failure: top-down or bottom-up? , 2014, Pflügers Archiv - European Journal of Physiology.

[38]  Hui Zhang,et al.  Glycoproteomic analysis identifies human glycoproteins secreted from HIV latently infected T cells and reveals their presence in HIV+ plasma , 2014, Clinical Proteomics.

[39]  Seungjin Choi,et al.  Inference of dynamic networks using time-course data , 2014, Briefings Bioinform..

[40]  Cathy H. Wu,et al.  Integrative Computational and Experimental Approaches to Establish a Post-Myocardial Infarction Knowledge Map , 2014, PLoS Comput. Biol..

[41]  Yong Sun,et al.  Activation of AKT by O-Linked N-Acetylglucosamine Induces Vascular Calcification in Diabetes Mellitus , 2014, Circulation research.

[42]  J. Coorssen,et al.  Deep Imaging: How Much of the Proteome Does Current Top-Down Technology Already Resolve? , 2014, PloS one.

[43]  Mark S Lowenthal,et al.  Quantitative bottom-up proteomics depends on digestion conditions. , 2014, Analytical chemistry.

[44]  Amos Bairoch,et al.  Metrics for the Human Proteome Project 2013-2014 and strategies for finding missing proteins. , 2014, Journal of proteome research.

[45]  Sophia Tsoka,et al.  Gene Network and Proteomic Analyses of Cardiac Responses to Pathological and Physiological Stress , 2013, Circulation. Cardiovascular genetics.

[46]  S. Franklin,et al.  Systems proteomics of cardiac chromatin identifies nucleolin as a regulator of growth and cellular plasticity in cardiomyocytes. , 2013, American journal of physiology. Heart and circulatory physiology.

[47]  M. Mann,et al.  Status of Large-scale Analysis of Post-translational Modifications by Mass Spectrometry* , 2013, Molecular & Cellular Proteomics.

[48]  Ludovic C. Gillet,et al.  Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system , 2013, Nature Methods.

[49]  M. Drazner,et al.  2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. , 2013, Journal of the American College of Cardiology.

[50]  Nobel C. Zong,et al.  Integration of Cardiac Proteome Biology and Medicine by a Specialized Knowledgebase , 2013, Circulation research.

[51]  Nobel C. Zong,et al.  Regulation of Acetylation Restores Proteolytic Function of Diseased Myocardium in Mouse and Human* , 2013, Molecular & Cellular Proteomics.

[52]  Jeanine J. Houwing-Duistermaat,et al.  Targeted Biomarker Discovery by High Throughput Glycosylation Profiling of Human Plasma Alpha1-Antitrypsin and Immunoglobulin A , 2013, PloS one.

[53]  D. Billheimer,et al.  Mass spectrometric immunoassay and MRM as targeted MS‐based quantitative approaches in biomarker development: Potential applications to cardiovascular disease and diabetes , 2013, Proteomics. Clinical applications.

[54]  Daniel A. Polasky,et al.  C-terminal methylation of truncated neuropeptides: An enzyme-assisted extraction artifact involving methanol , 2013, Peptides.

[55]  Amber L. Couzens,et al.  The CRAPome: a Contaminant Repository for Affinity Purification Mass Spectrometry Data , 2013, Nature Methods.

[56]  R. Cole,et al.  The Cardiac Acetyl-Lysine Proteome , 2013, PloS one.

[57]  A. Scholten,et al.  Targeted Phosphotyrosine Profiling of Glycoprotein VI Signaling Implicates Oligophrenin-1 in Platelet Filopodia Formation , 2013, Arteriosclerosis, thrombosis, and vascular biology.

[58]  G. Vanpoucke,et al.  Integrated Proteomics Pipeline Yields Novel Biomarkers for Predicting Preeclampsia , 2013, Hypertension.

[59]  H. Mischak,et al.  Recent advances in capillary electrophoresis coupled to mass spectrometry for clinical proteomic applications , 2013, Electrophoresis.

[60]  U. Sauer,et al.  Quantitative Phosphoproteomics Reveal mTORC1 Activates de Novo Pyrimidine Synthesis , 2013, Science.

[61]  John R Yates,et al.  The revolution and evolution of shotgun proteomics for large-scale proteome analysis. , 2013, Journal of the American Chemical Society.

[62]  Mario J. Garcia,et al.  ACCF 2012 expert consensus document on practical clinical considerations in the interpretation of troponin elevations: a report of the American College of Cardiology Foundation task force on Clinical Expert Consensus Documents. , 2012, Journal of the American College of Cardiology.

[63]  A. Heck,et al.  Next-generation proteomics: towards an integrative view of proteome dynamics , 2012, Nature Reviews Genetics.

[64]  George Poste,et al.  Biospecimens, biomarkers, and burgeoning data: the imperative for more rigorous research standards. , 2012, Trends in molecular medicine.

[65]  Hsien-Da Huang,et al.  dbPTM 3.0: an informative resource for investigating substrate site specificity and functional association of protein post-translational modifications , 2012, Nucleic Acids Res..

[66]  Lennart Martens,et al.  The first comprehensive and quantitative analysis of human platelet protein composition allows the comparative analysis of structural and functional pathways. , 2012, Blood.

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

[68]  Raymond Vanholder,et al.  Implementation of proteomic biomarkers: making it work , 2012, European journal of clinical investigation.

[69]  G. Filippatos,et al.  Troponin elevation in patients with heart failure: on behalf of the third Universal Definition of Myocardial Infarction Global Task Force: Heart Failure Section. , 2012, European heart journal.

[70]  Andre Terzic,et al.  Systems proteomics for translational network medicine. , 2012, Circulation. Cardiovascular genetics.

[71]  M. Tress,et al.  Chimeras taking shape: Potential functions of proteins encoded by chimeric RNA transcripts , 2012, Genome research.

[72]  M. Dunn,et al.  Partitioning the Proteome: Phase Separation for Targeted Analysis of Membrane Proteins in Human Post-Mortem Brain , 2012, PloS one.

[73]  K. Jellinger,et al.  Comparative platelet proteome analysis reveals an increase of monoamine oxidase-B protein expression in Alzheimer's disease but not in non-demented Parkinson's disease patients. , 2012, Journal of proteomics.

[74]  V. Marx Targeted proteomics , 2012, Nature Methods.

[75]  Juncong Yang,et al.  MRM‐based multiplexed quantitation of 67 putative cardiovascular disease biomarkers in human plasma , 2012, Proteomics.

[76]  Albert J R Heck,et al.  Trends in ultrasensitive proteomics. , 2012, Current opinion in chemical biology.

[77]  S. Gygi,et al.  Hyperplexing: A Method for Higher-Order Multiplexed Quantitative Proteomics Provides a Map of the Dynamic Response to Rapamycin in Yeast , 2012, Science Signaling.

[78]  D. Laskowitz,et al.  Evolving role of biomarkers in acute cerebrovascular disease , 2012, Annals of neurology.

[79]  M. Lindsey,et al.  Using Extracellular Matrix Proteomics to Understand Left Ventricular Remodeling , 2012, Circulation. Cardiovascular genetics.

[80]  James D Brooks,et al.  Translational genomics: the challenge of developing cancer biomarkers. , 2012, Genome research.

[81]  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.

[82]  Mona Singh,et al.  Accurate proteome-wide protein quantification from high-resolution 15N mass spectra , 2011, Genome Biology.

[83]  Christopher A. Penfold,et al.  How to infer gene networks from expression profiles, revisited , 2011, Interface Focus.

[84]  Ying Ge,et al.  Comprehensive Analysis of Protein Modifications by Top-Down Mass Spectrometry , 2011, Circulation. Cardiovascular genetics.

[85]  N. Zachara,et al.  Defining the Heart and Cardiovascular O-GlcNAcome: A Review of Approaches and Methods , 2011, Circulation. Cardiovascular genetics.

[86]  S. Hanash Why have protein biomarkers not reached the clinic? , 2011, Genome Medicine.

[87]  M. Mann,et al.  System-wide Perturbation Analysis with Nearly Complete Coverage of the Yeast Proteome by Single-shot Ultra HPLC Runs on a Bench Top Orbitrap* , 2011, Molecular & Cellular Proteomics.

[88]  Ying Ge,et al.  Top-down quantitative proteomics identified phosphorylation of cardiac troponin I as a candidate biomarker for chronic heart failure. , 2011, Journal of proteome research.

[89]  Christopher M Overall,et al.  Identifying and quantifying proteolytic events and the natural N terminome by terminal amine isotopic labeling of substrates , 2011, Nature Protocols.

[90]  P. Pandolfi,et al.  A ceRNA Hypothesis: The Rosetta Stone of a Hidden RNA Language? , 2011, Cell.

[91]  Andre Terzic,et al.  Somatic oxidative bioenergetics transitions into pluripotency-dependent glycolysis to facilitate nuclear reprogramming. , 2011, Cell metabolism.

[92]  Zhen Zhang,et al.  Effectiveness of a Multivariate Index Assay in the Preoperative Assessment of Ovarian Tumors , 2011, Obstetrics and gynecology.

[93]  Erin F. Simonds,et al.  Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum , 2011, Science.

[94]  Xiang-Sun Zhang,et al.  NOA: a novel Network Ontology Analysis method , 2011, Nucleic acids research.

[95]  D. K. Arrell,et al.  K(ATP) channel-dependent metaboproteome decoded: systems approaches to heart failure prediction, diagnosis, and therapy. , 2011, Cardiovascular research.

[96]  L. Poston,et al.  Urinary Proteomics for Prediction of Preeclampsia , 2011, Hypertension.

[97]  Jennifer E Van Eyk,et al.  Overview: The Maturing of Proteomics in Cardiovascular Research , 2011, Circulation research.

[98]  S. Chien,et al.  PDGF-BB and TGF-β1 on cross-talk between endothelial and smooth muscle cells in vascular remodeling induced by low shear stress , 2011, Proceedings of the National Academy of Sciences.

[99]  Ruedi Aebersold,et al.  On the development of plasma protein biomarkers. , 2011, Journal of proteome research.

[100]  J. Camarero,et al.  Protein Microarrays: Novel Developments and Applications , 2010, Pharmaceutical Research.

[101]  Timothy J. Nelson,et al.  ATP‐Sensitive K+ Channel‐Deficient Dilated Cardiomyopathy Proteome Remodeled by Embryonic Stem Cell Therapy , 2010, Stem cells.

[102]  R. Aebersold,et al.  Increased Selectivity, Analytical Precision, and Throughput in Targeted Proteomics , 2010, Molecular & Cellular Proteomics.

[103]  D. K. Arrell,et al.  Network Systems Biology for Drug Discovery , 2010, Clinical pharmacology and therapeutics.

[104]  Karl Mechtler,et al.  Peptide Labeling with Isobaric Tags Yields Higher Identification Rates Using iTRAQ 4-Plex Compared to TMT 6-Plex and iTRAQ 8-Plex on LTQ Orbitrap , 2010, Analytical chemistry.

[105]  Tracy R. Keeney,et al.  Aptamer-based multiplexed proteomic technology for biomarker discovery , 2010, PloS one.

[106]  Rogelio Zamilpa,et al.  Proteomic analysis identifies in vivo candidate matrix metalloproteinase‐9 substrates in the left ventricle post‐myocardial infarction , 2010, Proteomics.

[107]  Ronald J. Moore,et al.  Enhanced Sensitivity for Selected Reaction Monitoring Mass Spectrometry-based Targeted Proteomics Using a Dual Stage Electrodynamic Ion Funnel Interface* , 2010, Molecular & Cellular Proteomics.

[108]  Yufang Jin,et al.  Combining experimental and mathematical modeling to reveal mechanisms of macrophage-dependent left ventricular remodeling , 2010, BMC Systems Biology.

[109]  F. Guillonneau,et al.  Serum profile in preeclampsia and intra-uterine growth restriction revealed by iTRAQ technology. , 2010, Journal of proteomics.

[110]  Gary D Bader,et al.  Pathway analysis of dilated cardiomyopathy using global proteomic profiling and enrichment maps , 2010, Proteomics.

[111]  B. Cravatt,et al.  Activity-based Proteomics of Enzyme Superfamilies: Serine Hydrolases as a Case Study* , 2010, The Journal of Biological Chemistry.

[112]  D. Kass,et al.  Modulation of Mitochondrial Proteome and Improved Mitochondrial Function by Biventricular Pacing of Dyssynchronous Failing Hearts , 2010, Circulation. Cardiovascular genetics.

[113]  N. Anderson,et al.  The clinical plasma proteome: a survey of clinical assays for proteins in plasma and serum. , 2010, Clinical chemistry.

[114]  E. Fung,et al.  A recipe for proteomics diagnostic test development: the OVA1 test, from biomarker discovery to FDA clearance. , 2010, Clinical chemistry.

[115]  Benjamin A. Garcia,et al.  Combinatorial profiling of chromatin-binding modules reveals multi-site discrimination , 2009, Nature chemical biology.

[116]  Ishtiaq Rehman,et al.  iTRAQ underestimation in simple and complex mixtures: "the good, the bad and the ugly". , 2009, Journal of proteome research.

[117]  R. Apweiler,et al.  Finding one's way in proteomics: a protein species nomenclature , 2009, Chemistry Central journal.

[118]  D. K. Arrell,et al.  ATP-sensitive K+ channel knockout induces cardiac proteome remodeling predictive of heart disease susceptibility. , 2009, Journal of proteome research.

[119]  Ying Zhang,et al.  Effect of dynamic exclusion duration on spectral count based quantitative proteomics. , 2009, Analytical chemistry.

[120]  K. Killeen,et al.  Profile of native N‐linked glycan structures from human serum using high performance liquid chromatography on a microfluidic chip and time‐of‐flight mass spectrometry , 2009, Proteomics.

[121]  D. K. Arrell,et al.  Proteomic profiling of KATP channel‐deficient hypertensive heart maps risk for maladaptive cardiomyopathic outcome , 2009, Proteomics.

[122]  Ruedi Aebersold,et al.  Targeted proteomic strategy for clinical biomarker discovery , 2009, Molecular oncology.

[123]  J. Thomson,et al.  Human embryonic stem cell phosphoproteome revealed by electron transfer dissociation tandem mass spectrometry , 2009, Proceedings of the National Academy of Sciences.

[124]  S. Kasner,et al.  Clinical Usefulness of a Biomarker-Based Diagnostic Test for Acute Stroke: The Biomarker Rapid Assessment in Ischemic Injury (BRAIN) Study , 2009, Stroke.

[125]  A. Gordus,et al.  System-wide investigation of ErbB4 reveals 19 sites of Tyr phosphorylation that are unusually selective in their recruitment properties. , 2008, Chemistry & biology.

[126]  Yufang Jin,et al.  Stability analysis of genetic regulatory network with additive noises , 2008, BMC Genomics.

[127]  D. K. Arrell,et al.  Cardioinductive Network Guiding Stem Cell Differentiation Revealed by Proteomic Cartography of Tumor Necrosis Factor α‐Primed Endodermal Secretome , 2008, Stem cells.

[128]  Michael L. Creech,et al.  Integration of biological networks and gene expression data using Cytoscape , 2007, Nature Protocols.

[129]  P. Khatri,et al.  A systems biology approach for pathway level analysis. , 2007, Genome research.

[130]  M. Mann,et al.  Higher-energy C-trap dissociation for peptide modification analysis , 2007, Nature Methods.

[131]  Lennart Martens,et al.  The minimum information about a proteomics experiment (MIAPE) , 2007, Nature Biotechnology.

[132]  D. di Bernardo,et al.  How to infer gene networks from expression profiles , 2007, Molecular systems biology.

[133]  S. Mohammed,et al.  Evaluation and optimization of ZIC-HILIC-RP as an alternative MudPIT strategy. , 2007, Journal of proteome research.

[134]  Michael I. Jordan,et al.  Hierarchical Dirichlet Processes , 2006 .

[135]  Chris Orsi,et al.  Improved immobilized metal affinity chromatography for large-scale phosphoproteomics applications. , 2006, Journal of proteome research.

[136]  S. Hanash,et al.  Challenges in deriving high-confidence protein identifications from data gathered by a HUPO plasma proteome collaborative study , 2006, Nature Biotechnology.

[137]  David M Bunk,et al.  Characterization of a new certified reference material for human cardiac troponin I. , 2006, Clinical chemistry.

[138]  D. Roote,et al.  Status Report , 2006, Journal of periodontology.

[139]  Gavin MacBeath,et al.  A quantitative protein interaction network for the ErbB receptors using protein microarrays , 2006, Nature.

[140]  K. S. Deshpande,et al.  Human protein reference database—2006 update , 2005, Nucleic Acids Res..

[141]  Eugene A. Kapp,et al.  Overview of the HUPO Plasma Proteome Project: Results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly‐available database , 2005, Proteomics.

[142]  F. Pontén,et al.  Antibody-based Proteomics for Human Tissue Profiling , 2005, Molecular & Cellular Proteomics.

[143]  D. Ransohoff Bias as a threat to the validity of cancer molecular-marker research , 2005, Nature reviews. Cancer.

[144]  Rovshan G Sadygov,et al.  Large-scale database searching using tandem mass spectra: Looking up the answer in the back of the book , 2004, Nature Methods.

[145]  John D. Venable,et al.  Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra , 2004, Nature Methods.

[146]  J. Stelling,et al.  Mathematical modeling of complex regulatory networks , 2004, IEEE Transactions on NanoBioscience.

[147]  R. Bast,et al.  Three Biomarkers Identified from Serum Proteomic Analysis for the Detection of Early Stage Ovarian Cancer , 2004, Cancer Research.

[148]  J. Shabanowitz,et al.  Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[149]  K. Gevaert,et al.  Global differential non-gel proteomics by quantitative and stable labeling of tryptic peptides with oxygen-18. , 2004, Journal of proteome research.

[150]  O. Jensen Modification-specific proteomics: characterization of post-translational modifications by mass spectrometry. , 2004, Current opinion in chemical biology.

[151]  Richard D. Smith,et al.  Proteome analyses using accurate mass and elution time peptide tags with capillary LC time-of-flight mass spectrometry , 2003, Journal of the American Society for Mass Spectrometry.

[152]  John R Yates,et al.  Large-scale protein identification using mass spectrometry. , 2003, Biochimica et biophysica acta.

[153]  P. Manow ‚The Good, the Bad, and the Ugly‘ , 2002 .

[154]  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.

[155]  Geoffrey E. Hinton,et al.  Variational Learning for Switching State-Space Models , 2000, Neural Computation.

[156]  F. McLafferty,et al.  Electron capture dissociation for structural characterization of multiply charged protein cations. , 2000, Analytical chemistry.

[157]  F. Sanger,et al.  Nucleotide sequence of bacteriophage φX174 DNA , 1977, Nature.

[158]  Yu-Fang Jin,et al.  Using systems biology approaches to understand cardiac inflammation and extracellular matrix remodeling in the setting of myocardial infarction , 2014, Wiley interdisciplinary reviews. Systems biology and medicine.

[159]  A. Tiss,et al.  Innovative tools for early detection of cancer , 2014 .

[160]  J. Alpert,et al.  The third universal definition of myocardial infarction , 2013 .

[161]  Jeroen J. Bax,et al.  Third universal definition of myocardial infarction. , 2012, Circulation.

[162]  F. Lottspeich,et al.  ICPLQuant – A software for non‐isobaric isotopic labeling proteomics , 2010, Proteomics.

[163]  P. Sandercock,et al.  Progress Review Blood Markers for the Prognosis of Ischemic Stroke A Systematic Review , 2009 .

[164]  J. Alpert,et al.  Joint ESC/ACCF/AHA/WHF Task Force for the Redefinition of Myocardial Infarction , 2008 .

[165]  John R Yates,et al.  Quantitative mass spectrometry identifies insulin signaling targets in C. elegans. , 2007, Nature Reviews Molecular Cell Biology.

[166]  P. Davidsson,et al.  Comparison of different depletion strategies for improved resolution in proteomic analysis of human serum samples , 2005, Proteomics.

[167]  D. Hochstrasser,et al.  From Proteins to Proteomes: Large Scale Protein Identification by Two-Dimensional Electrophoresis and Arnino Acid Analysis , 1996, Bio/Technology.

[168]  F. Sanger,et al.  Nucleotide sequence of bacteriophage phi X174 DNA. , 1977, Nature.

[169]  Brendan MacLean,et al.  Skyline: an open source document editor for creating and analyzing targeted proteomics experiments , 2010, Bioinform..