SynthesisPloS one2011
Gene regulatory network reconstruction using Bayesian networks, the Dantzig Selector, the Lasso and their meta-analysis.
Synthesis in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 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
33 citing papers in PubMed.
- Recent advances in exploring transcriptional regulatory landscape of crops.Frontiers in plant science · 2024Review
- Integrative genetic and genomic networks identify microRNA associated with COPD and ILD.Scientific reports · 2023Article
- Comparing methods for statistical inference with model uncertainty.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Transcriptional differentiation driving Cucumis sativus-Botrytis cinerea interactions based on the Skellam model and Bayesian networks.AMB Express · 2021Article
- A new Bayesian piecewise linear regression model for dynamic network reconstruction.BMC bioinformatics · 2021Article
- Exploring the differentially expressed genes in human lymphocytes upon response to ionizing radiation: a network biology approach.Radiation oncology journal · 2021Article
- Biological Network Inference With GRASP: A Bayesian Network Structure Learning Method Using Adaptive Sequential Monte Carlo.Frontiers in genetics · 2021Article
- Molecular networks in Network Medicine: Development and applications.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Parallel Tempering with Lasso for model reduction in systems biology.PLoS computational biology · 2020Article
- WormQTL2: an interactive platform for systems genetics in Caenorhabditis elegans.Database : the journal of biological databases and curation · 2020Article
- Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling.Frontiers in genetics · 2020Review
- Integrative and theoretical research on the architecture of a biological system and its disorder.The journal of physiological sciences : JPS · 2019Review
- Hierarchical parameter estimation of GRN based on topological analysis.IET systems biology · 2018Article
- An integrated approach to infer cross-talks between intracellular protein transport and signaling pathways.BMC bioinformatics · 2018Article
- LASSIM-A network inference toolbox for genome-wide mechanistic modeling.PLoS computational biology · 2017Article
- BGRMI: A method for inferring gene regulatory networks from time-course gene expression data and its application in breast cancer research.Scientific reports · 2016Article
- Compartmentalized gene regulatory network of the pathogenic fungus Fusarium graminearum.The New phytologist · 2016Article
- Nonlinear Network Reconstruction from Gene Expression Data Using Marginal Dependencies Measured by DCOL.PloS one · 2016Article
- Learning from Co-expression Networks: Possibilities and Challenges.Frontiers in plant science · 2016Review
- Semi-supervised prediction of gene regulatory networks using machine learning algorithms.Journal of biosciences · 2015Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern technologies and especially next generation sequencing facilities are giving a cheaper access to genotype and genomic data measured on the same sample at once. This creates an ideal situation for multifactorial experiments designed to infer gene regulatory networks. The fifth "Dialogue for Reverse Engineering Assessments and Methods" (DREAM5) challenges are aimed at assessing methods and associated algorithms devoted to the inference of biological networks. Challenge 3 on "Systems Genetics" proposed to infer causal gene regulatory networks from different genetical genomics data sets. We investigated a wide panel of methods ranging from Bayesian networks to penalised linear regressions to analyse such data, and proposed a simple yet very powerful meta-analysis, which combines these inference methods. We present results of the Challenge as well as more in-depth analysis of predicted networks in terms of structure and reliability. The developed meta-analysis was ranked first among the 16 teams participating in Challenge 3A. It paves the way for future extensions of our inference method and more accurate gene network estimates in the context of genetical genomics.
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.