ReviewAnnual review of biophysics and biomolecular structure2005
Toward predictive models of mammalian cells.
Review in Annual review of biophysics and biomolecular structure, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed.
- Article
- Bayesian parameter estimation for dynamical models in systems biology.PLoS computational biology · 2022Article
- Convergent and distributed effects of the 3q29 deletion on the human neural transcriptome.Translational psychiatry · 2021Article
- A systems approach to infectious disease.Nature reviews. Genetics · 2020Review
- Pathway and network approaches for identification of cancer signature markers from omics data.Journal of Cancer · 2015Review
- Complex diseases require complex therapies.EMBO reports · 2013Article
- Systems approaches for synthetic biology: a pathway toward mammalian design.Frontiers in physiology · 2013Article
- A network-oriented perspective on cardiac calcium signaling.American journal of physiology. Cell physiology · 2012Review
- Merging systems biology with pharmacodynamics.Science translational medicine · 2012Review
- Article
- The autoimmune tautology: an in silico approach.Autoimmune diseases · 2012Article
- Systems pharmacology of complex diseases.Annals of the New York Academy of Sciences · 2011Review
- Introduction to network analysis in systems biology.Science signaling · 2011Article
- Lists2Networks: integrated analysis of gene/protein lists.BMC bioinformatics · 2010Article
- Effects of macromolecular crowding on intracellular diffusion from a single particle perspective.Biophysical reviews · 2010Article
- Insights into the organization of biochemical regulatory networks using graph theory analyses.The Journal of biological chemistry · 2009Review
- SNAVI: Desktop application for analysis and visualization of large-scale signaling networks.BMC systems biology · 2009Article
- PI3K-dependent cross-talk interactions converge with Ras as quantifiable inputs integrated by Erk.Molecular systems biology · 2009Article
- Network integration and graph analysis in mammalian molecular systems biology.IET systems biology · 2008Review
- 4Pi microscopy of the nuclear pore complex.Biophysical journal · 2008Article
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.
Funding
Abstract
Progress in experimental and theoretical biology is likely to provide us with the opportunity to assemble detailed predictive models of mammalian cells. Using a functional format to describe the organization of mammalian cells, we describe current approaches for developing qualitative and quantitative models using data from a variety of experimental sources. Recent developments and applications of graph theory to biological networks are reviewed. The use of these qualitative models to identify the topology of regulatory motifs and functional modules is discussed. Cellular homeostasis and plasticity are interpreted within the framework of balance between regulatory motifs and interactions between modules. From this analysis we identify the need for detailed quantitative models on the basis of the representation of the chemistry underlying the cellular process. The use of deterministic, stochastic, and hybrid models to represent cellular processes is reviewed, and an initial integrated approach for the development of large-scale predictive models of a mammalian cell is presented.
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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.