ArticleMolecular systems biology2006
Systems-level analyses identify extensive coupling among gene expression machines.
Article in Molecular systems biology, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 44 citations in OpenAlex.
- Localization and Functional Roles of Components of the Translation Apparatus in the Eukaryotic Cell Nucleus.Cells · 2021Review
- Interlog protein network: an evolutionary benchmark of protein interaction networks for the evaluation of clustering algorithms.BMC bioinformatics · 2015Article
- Predicting functions of proteins in mouse based on weighted protein-protein interaction network and protein hybrid properties.PloS one · 2011Article
- Distinct patterns of expression and evolution of intronless and intron-containing mammalian genes.Molecular biology and evolution · 2010Article
- "Genes".Theory in biosciences = Theorie in den Biowissenschaften · 2008Article
- A simple principle concerning the robustness of protein complex activity to changes in gene expression.BMC systems biology · 2008Article
- Conceptual modeling in systems biology fosters empirical findings: the mRNA lifecycle.PloS one · 2007Article
- A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality.BMC bioinformatics · 2007Article
- CellCircuits: a database of protein network models.Nucleic acids research · 2007Article
- Network-based prediction of protein function.Molecular systems biology · 2007Review
- How complete are current yeast and human protein-interaction networks?Genome biology · 2006Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Here, we develop computational methods to assess and consolidate large, diverse protein interaction data sets, with the objective of identifying proteins involved in the coupling of multicomponent complexes within the yeast gene expression pathway. From among approximately 43 000 total interactions and 2100 proteins, our methods identify known structural complexes, such as the spliceosome and SAGA, and functional modules, such as the DEAD-box helicases, within the interaction network of proteins involved in gene expression. Our process identifies and ranks instances of three distinct, biologically motivated motifs, or patterns of coupling among distinct machineries involved in different subprocesses of gene expression. Our results confirm known coupling among transcription, RNA processing, and export, and predict further coupling with translation and nonsense-mediated decay. We systematically corroborate our analysis with two independent, comprehensive experimental data sets. The methods presented here may be generalized to other biological processes and organisms to generate principled, systems-level network models that provide experimentally testable hypotheses for coupling among biological machines.
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.