ArticleNucleic acids research2011
Discovering pathways by orienting edges in protein interaction networks.
Article in Nucleic acids research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 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
51 citing papers in PubMed.
- A Framework for Benchmarking Pathway Reconstruction Algorithms.bioRxiv : the preprint server for biology · 2026Article
- D'or: deep orienter of protein-protein interaction networks.Bioinformatics (Oxford, England) · 2024Article
- A gray box framework that optimizes a white box logical model using a black box optimizer for simulating cellular responses to perturbations.Cell reports methods · 2024Article
- Article
- Influence network model uncovers relations between biological processes and mutational signatures.Genome medicine · 2023Article
- Network-Based Analysis to Identify Drivers of Metastatic Prostate Cancer Using GoNetic.Cancers · 2021Article
- Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence.Scientific reports · 2021Article
- Comparative Analyses of Gene Co-expression Networks: Implementations and Applications in the Study of Evolution.Frontiers in genetics · 2021Review
- Connecting signaling and metabolic pathways in EGF receptor-mediated oncogenesis of glioblastoma.PLoS computational biology · 2019Article
- Reconstructing signaling pathways using regular language constrained paths.Bioinformatics (Oxford, England) · 2019Article
- Inferring signalling dynamics by integrating interventional with observational data.Bioinformatics (Oxford, England) · 2019Article
- A systematic approach to orient the human protein-protein interaction network.Nature communications · 2019Article
- Stems cells, big data and compendium-based analyses for identifying cell types, signalling pathways and gene regulatory networks.Biophysical reviews · 2019Review
- Identification of active signaling pathways by integrating gene expression and protein interaction data.BMC systems biology · 2018Article
- Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data.Cell reports · 2018Article
- The latent geometry of the human protein interaction network.Bioinformatics (Oxford, England) · 2018Article
- An optimization framework for network annotation.Bioinformatics (Oxford, England) · 2018Article
- Network inference reveals novel connections in pathways regulating growth and defense in the yeast salt response.PLoS computational biology · 2018Article
- Reconstructing phylogenetic tree using a protein-protein interaction technique.IET nanobiotechnology · 2017Article
- Network-Based Identification of Adaptive Pathways in Evolved Ethanol-Tolerant Bacterial Populations.Molecular biology and evolution · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Modern experimental technology enables the identification of the sensory proteins that interact with the cells' environment or various pathogens. Expression and knockdown studies can determine the downstream effects of these interactions. However, when attempting to reconstruct the signaling networks and pathways between these sources and targets, one faces a substantial challenge. Although pathways are directed, high-throughput protein interaction data are undirected. In order to utilize the available data, we need methods that can orient protein interaction edges and discover high-confidence pathways that explain the observed experimental outcomes. We formalize the orientation problem in weighted protein interaction graphs as an optimization problem and present three approximation algorithms based on either weighted Boolean satisfiability solvers or probabilistic assignments. We use these algorithms to identify pathways in yeast. Our approach recovers twice as many known signaling cascades as a recent unoriented signaling pathway prediction technique and over 13 times as many as an existing network orientation algorithm. The discovered paths match several known signaling pathways and suggest new mechanisms that are not currently present in signaling databases. For some pathways, including the pheromone signaling pathway and the high-osmolarity glycerol pathway, our method suggests interesting and novel components that extend current annotations.
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.