Integrative Computational and Experimental Approaches to Establish a Post-Myocardial Infarction Knowledge Map

Nguyen, Nguyen T.; Zhang, Xiaolin; Wu, Cathy H.; Lange, Richard A.; Chilton, Robert; Lindsey, Merry L.; Jin, Yu

doi:10.1371/journal.pcbi.1003472

Cited by 10 publications

(12 citation statements)

References 152 publications

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“…151 As a consequence, an emerging component of systems proteomics is the application of spatiotemporal modeling, including recent forays into the cardiovascular proteomic field. 137,152 Ordinary differential equations, partial differential equations, and stochastic differential equations have been applied to model temporal and spatial changes of biological and physical variables in continuous format. 133,134,153 Partial differential Figure 2.…”

Section: Network Modelingmentioning

confidence: 99%

“…Beyond differential equation models in continuous format, there also exist Boolean network models, network ontology analysis, and switching state space models for the nonstationary nature of the network. 151,152,[154][155][156] These modeling methods generally require prior information of associated regulatory mechanisms, including protein-protein interactions or configuration of specific pathways. Available analysis methods also integrate structural properties of networks to classify proteins into functional groups.…”

Section: Network Modelingmentioning

confidence: 99%

“…Available analysis methods also integrate structural properties of networks to classify proteins into functional groups. 152,157,158 Proteomics data with accurate protein quantification facilitate the examination of regulatory interactions among proteins such that every regulation may be considered as an input and output relationship. Although these regulatory processes may not be controlled by direct molecular interactions, modeling can shed light on hidden indirect associations among proteins.…”

Section: Network Modelingmentioning

confidence: 99%

See 2 more Smart Citations

Transformative Impact of Proteomics on Cardiovascular Health and Disease

Lindsey¹,

Mayr²,

Gomes³

et al. 2015

Circulation

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148

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Abstract-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.

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Section: Network Modelingmentioning

confidence: 99%

Section: Network Modelingmentioning

confidence: 99%

Section: Network Modelingmentioning

confidence: 99%

See 1 more Smart Citation

Transformative Impact of Proteomics on Cardiovascular Health and Disease

Lindsey¹,

Mayr²,

Gomes³

et al. 2015

Circulation

Self Cite

148

View full text Add to dashboard Cite

show abstract

“…We have previously developed cellular-level models of macrophage polarization kinetics and cardiac remodeling post-MI on a limited scale [42, 43]. More complete knowledge maps and models that incorporate detailed signaling networks are needed to identify molecular drivers of macrophage polarization [44]. Building these models will require a framework that integrates both existing knowledge from the literature and new comprehensive molecular profiling with pathway analysis (Figure 2) [42–49].…”

Section: Establishing a Macrophage Classification Systemmentioning

confidence: 99%

Knowledge gaps to understanding cardiac macrophage polarization following myocardial infarction

Lindsey

Saucerman

DeLeon‐Pennell

2016

Biochimica et Biophysica Acta (BBA) - Molecular Basis of Diseas

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Following myocardial infarction (MI), macrophages coordinate both pro-inflammatory and reparative responses of the left ventricle (LV) by reacting to and secreting cytokines, chemokines, and growth factors and by stimulating endothelial cells and fibroblasts to modulate neovascularization and scar formation. Healing of the infarcted LV can be divided into three distinct, but overlapping phases: inflammatory, proliferative, and maturation. Macrophages are involved in all phases. Despite macrophages being a major leukocyte cell type in the post-MI LV, how this cell type regulates LV remodeling over the post-MI time continuum is not completely understood. In this review, we summarize the current literature as a foundation to discuss the major knowledge gaps that remain. Defining the post-MI temporal macrophage phenotypes to establish a classification system is the first step in exploring how macrophage phenotypes are regulated, how temporal stimulation and secretion profiles evolve, and how best to modify stimuli to yield predictable cell responses.

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“…For a set of proteins or genes with enriched pathways and GOBPs, we propose a method that integrates molecular interaction, biological pathways and GOBP to standardize descriptions of pathways using GOBPs through the establishment of the functional biological pathway-process network. We demonstrated with the set of 613 proteins related to myocardial infarction (MI) from the MI-specific protein-protein interaction network [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses

2015

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BackgroundPathway analysis has been widely used to gain insight into essential mechanisms of the response to myocardial infarction (MI). Currently, there exist multiple pathway databases that organize molecular datasets and manually curate pathway maps for biological interpretation at varying forms of organization. However, inconsistencies among different databases in pathway descriptions, frequently due to conflicting results in the literature, can generate incorrect interpretations. Furthermore, although pathway analysis software provides detailed images of interactions among molecules, it does not exhibit how pathways interact with one another or with other biological processes under specific conditions.MethodsWe propose a novel method to standardize descriptions of enriched pathways for a set of genes/proteins using Gene Ontology terms. We used this method to examine the relationships among pathways and biological processes for a set of condition-specific genes/proteins, represented as a functional biological pathway-process network. We applied this algorithm to a set of 613 MI-specific proteins we previously identified.ResultsA total of 96 pathways from Biocarta, KEGG, and Reactome, and 448 Gene Ontology Biological Processes were enriched with these 613 proteins. The pathways were represented as Boolean functions of biological processes, delivering an interactive scheme to organize enriched information with an emphasis on involvement of biological processes in pathways. We extracted a network focusing on MI to demonstrate that tyrosine phosphorylation of Signal Transducer and Activator of Transcription (STAT) protein, positive regulation of collagen metabolic process, coagulation, and positive/negative regulation of blood coagulation have immediate impacts on the MI response.ConclusionsOur method organized biological processes and pathways in an unbiased approach to provide an intuitive way to identify biological properties of pathways under specific conditions. Pathways from different databases have similar descriptions yet diverse biological processes, indicating variation in their ability to share similar functional characteristics. The coverages of pathways can be expanded with the incorporation of more biological processes, predicting involvement of protein members in pathways. Further, detailed analyses of the functional biological pathway-process network will allow researchers and scientists to explore critical routes in biological systems in the progression of disease.

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Integrative Computational and Experimental Approaches to Establish a Post-Myocardial Infarction Knowledge Map

Cited by 10 publications

References 152 publications

Transformative Impact of Proteomics on Cardiovascular Health and Disease

Transformative Impact of Proteomics on Cardiovascular Health and Disease

Knowledge gaps to understanding cardiac macrophage polarization following myocardial infarction

Systems analysis of gene ontology and biological pathways involved in post-myocardial infarction responses

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