ReviewCurrent opinion in cardiology2012
Deciphering the molecular basis of human cardiovascular disease through network biology.
Review in Current opinion in cardiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 33 citations in OpenAlex.
- Deciphering the Basis of Molecular Biology of Selected Cardiovascular Diseases: A View on Network Medicine.International journal of molecular sciences · 2022Review
- The Potential of Metabolomics in Biomedical Applications.Metabolites · 2022Review
- Network medicine in Cardiovascular Research.Cardiovascular research · 2021Review
- Integrative Omics to Characterize and Classify Pulmonary Vascular Disease.Clinics in chest medicine · 2021Review
- Ophidiomycosis surveillance of snakes in Georgia, USA reveals new host species and taxonomic associations with disease.Scientific reports · 2020Article
- Bipartite graphs in systems biology and medicine: a survey of methods and applications.GigaScience · 2018Review
- A Network-Biology Informed Computational Drug Repositioning Strategy to Target Disease Risk Trajectories and Comorbidities of Peripheral Artery Disease.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- Insights from systems pharmacology into cardiovascular drug discovery and therapy.BMC systems biology · 2014Article
- Beyond single-nucleotide polymorphisms: genetics, genomics, and other 'omic approaches to acute respiratory distress syndrome.Clinics in chest medicine · 2014Review
- Systems biology applied to heart failure with normal ejection fraction.Arquivos brasileiros de cardiologia · 2014Review
- Survey of network-based approaches to research of cardiovascular diseases.BioMed research international · 2014Review
- Review
- Systems analysis of oxidant stress in the vasculature.IUBMB life · 2013Article
- Human growth is associated with distinct patterns of gene expression in evolutionarily conserved networks.BMC genomics · 2013Article
- Nodes and biological processes identified on the basis of network analysis in the brain of the senescence accelerated mice as an Alzheimer's disease animal model.Frontiers in aging neuroscience · 2013Article
- The emerging paradigm of network medicine in the study of human disease.Circulation research · 2012Review
- Holding our breath: The emerging and anticipated roles of microRNA in pulmonary hypertension.Pulmonary circulation · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
purpose of reviewThis review introduces the fundamental concepts of network medicine and explores the feasibility and potential impact of network-based methods on predicting and ameliorating individual manifestations of human cardiovascular disease. RECENT
findingsComplex cardiovascular diseases rarely result from an abnormality in a single molecular effector, but, rather, nearly always are the net result of multiple pathobiological pathways that interact through an interconnected network. In the postgenomic era, a framework has emerged of the potential complexity of the interacting pathways that govern molecular actions in the human cell. As a result, network approaches have been developed to understand more comprehensively those interconnections that influence human disease. 'Network medicine' has already led to tangible discoveries of novel disease genes and pathways as well as improved mechanisms for rational drug development. SUMMARY: As methodologies evolve, network medicine may better capture the complexity of human pathogenesis and, thus, re-define personalized disease classification and therapies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.