ReviewJournal of thrombosis and haemostasis : JTH2013
Systems biology of coagulation.
Review in Journal of thrombosis and haemostasis : JTH, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 52 citations in OpenAlex.
- Article
- QSP-Copilot: An AI-Augmented Platform for Accelerating Quantitative Systems Pharmacology Model Development.CPT: pharmacometrics & systems pharmacology · 2025Article
- Article
- A new look at TFPI inhibition of factor X activation.PLoS computational biology · 2024Article
- Thromboelastogram and coagulation function index: relevance for female breast cancer.Frontiers in oncology · 2024Article
- clotFoam: An open-source framework to simulate blood clot formation under arterial flow.SoftwareX · 2023Article
- An Accelerated Thrombosis Model for Computational Fluid Dynamics Simulations in Rotary Blood Pumps.Cardiovascular engineering and technology · 2022Article
- A System-Wide Investigation and Stratification of the Hemostatic Proteome in Premature Myocardial Infarction.Frontiers in cardiovascular medicine · 2022Article
- Computationally Driven Discovery in Coagulation.Arteriosclerosis, thrombosis, and vascular biology · 2021Review
- Dynamic Optimization with Particle Swarms (DOPS): a meta-heuristic for parameter estimation in biochemical models.BMC systems biology · 2018Article
- Measuring fibrinolysis: from research to routine diagnostic assays.Journal of thrombosis and haemostasis : JTH · 2018Review
- Multiscale simulation of thrombus growth and vessel occlusion triggered by collagen/tissue factor using a data-driven model of combinatorial platelet signalling.Mathematical medicine and biology : a journal of the IMA · 2017Article
- Systems Analysis of Thrombus Formation.Circulation research · 2016Review
- Computational Study of Thrombus Formation and Clotting Factor Effects under Venous Flow Conditions.Biophysical journal · 2016Article
- A Novel Pentapeptide Targeting Integrin β3-Subunit Inhibits Platelet Aggregation and Its Application in Rat for Thrombosis Prevention.Frontiers in pharmacology · 2016Article
- Regulation of Early Steps of GPVI Signal Transduction by Phosphatases: A Systems Biology Approach.PLoS computational biology · 2015Article
- Mechanistic Modeling of the Effects of Acidosis on Thrombin Generation.Anesthesia and analgesia · 2015Article
- Candida albicans Shaving to Profile Human Serum Proteins on Hyphal Surface.Frontiers in microbiology · 2015Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Accurate computer simulation of blood function can inform drug target selection, patient-specific dosing, clinical trial design, biomedical device design, as well as the scoring of patient-specific disease risk and severity. These large-scale simulations rely on hundreds of independently measured physical parameters and kinetic rate constants. However, the models can be validated against large-scale, patient-specific laboratory measurements. By validation with high-dimensional data, modeling becomes a powerful tool to predict clinically complex scenarios. Currently, it is possible to accurately predict the clotting rate of plasma or blood in a tube as it is activated with a dose of tissue factor, even as numerous coagulation factors are altered by exogenous attenuation or potentiation. Similarly, the dynamics of platelet activation, as indicated by calcium mobilization or inside-out signaling, can now be numerically simulated with accuracy in cases where platelets are exposed to combinations of agonists. Multiscale models have emerged to combine platelet function and coagulation kinetics into complete physics-based descriptions of thrombosis under flow. Blood flow controls platelet fluxes, delivery and removal of coagulation factors, adhesive bonding, and von Willebrand factor conformation. The field of blood systems biology has now reached a stage that anticipates the inclusion of contact, complement, and fibrinolytic pathways along with models of neutrophil and endothelial activation. Along with '-omics' data sets, such advanced models seek to predict the multifactorial range of healthy responses and diverse bleeding and clotting scenarios, ultimately to understand and improve patient outcomes.
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.