ArticlePLoS computational biology2016
Fused Regression for Multi-source Gene Regulatory Network Inference.
Article in PLoS computational biology, 2016. 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.
- Leveraging transcription factor physical proximity for enhancing gene regulation inference.Bioinformatics (Oxford, England) · 2025Article
- NetREX-CF integrates incomplete transcription factor data with gene expression to reconstruct gene regulatory networks.Communications biology · 2022Article
- Network reconstruction for trans acting genetic loci using multi-omics data and prior information.Genome medicine · 2022Article
- Inferring TF activities and activity regulators from gene expression data with constraints from TF perturbation data.Bioinformatics (Oxford, England) · 2021Article
- Intracellular and Intercellular Gene Regulatory Network Inference From Time-Course Individual RNA-Seq.Frontiers in bioinformatics · 2021Article
- Network inference in systems biology: recent developments, challenges, and applications.Current opinion in biotechnology · 2020Review
- Article
- Gene Regulatory Networks ofFrontiers in microbiology · 2020Article
- Multi-study inference of regulatory networks for more accurate models of gene regulation.PLoS computational biology · 2019Article
- NetProphet 2.0: mapping transcription factor networks by exploiting scalable data resources.Bioinformatics (Oxford, England) · 2018Article
- Machine learning in postgenomic biology and personalized medicine.Wiley interdisciplinary reviews. Data mining and knowledge discoveryArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms) and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. This approach improves network inference performance even when orthology mapping and conservation are incomplete. We refine this method by presenting an algorithm that extracts the true conserved subnetwork from a larger set of potentially conserved interactions and demonstrate the utility of our method in cross species network inference. Last, we demonstrate our method's utility in learning from data collected on different experimental platforms.
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.