ReviewNature reviews. Microbiology2010
Advantages and limitations of current network inference methods.
Review in Nature reviews. Microbiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 225 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
225 citing papers in PubMed, 1 synthesis or guideline pooled it, 526 citations in OpenAlex.
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- GRNFormer: accurate gene regulatory network inference using graph transformer.Bioinformatics (Oxford, England) · 2026Article
- Network-based exploration of 4-(phenylsulfonyl)morpholine molecules for metastatic triple-negative breast cancer suppression.PLoS computational biology · 2026Article
- Identification of miRNA biomarkers for essential hypertension in small samples based on MPGAM.Scientific reports · 2025Article
- Quantifying interventional causality by knockoff operation.Science advances · 2025Article
- CONSTRUCTING GENE REGULATORY NETWORK USING CHATTERJEE'S RANK CORRELATION WITH SINGLE-CELL TRANSCRIPTOMIC DATA.bioRxiv : the preprint server for biology · 2025Article
- How far are we from the era of big data in transcriptomics? Lessons from the bacterial data in GEO.Briefings in bioinformatics · 2025Review
- Article
- Exploring the transmission of cognitive task information through optimal brain pathways.PLoS computational biology · 2025Article
- Development of a Pre-Modification Strategy to Overcome Restriction-Modification Barriers and Enhance Genetic Engineering inInternational journal of molecular sciences · 2025Article
- Tensor product algorithms for inference of contact network from epidemiological data.BMC bioinformatics · 2024Article
- Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights.BioEssays : news and reviews in molecular, cellular and developmental biology · 2024Review
- scGREAT: Transformer-based deep-language model for gene regulatory network inference from single-cell transcriptomics.iScience · 2024Article
- Causal connectivity measures for pulse-output network reconstruction: Analysis and applications.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Gene Co-Expression Analysis of Multiple Brain Tissues Reveals Correlation of FAM222A Expression with Multiple Alzheimer's Disease-Related Genes.Journal of Alzheimer's disease : JAD · 2024Article
- Approaches for Benchmarking Single-Cell Gene Regulatory Network Methods.Bioinformatics and biology insights · 2024Review
- Inferred regulons are consistent with regulator binding sequences in E. coli.PLoS computational biology · 2024Article
- Inferring gene regulatory networks using transcriptional profiles as dynamical attractors.PLoS computational biology · 2023Article
- Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation.PLoS computational biology · 2023Article
- SWEET: a single-sample network inference method for deciphering individual features in disease.Briefings in bioinformatics · 2023Article
165 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Network inference, which is the reconstruction of biological networks from high-throughput data, can provide valuable information about the regulation of gene expression in cells. However, it is an underdetermined problem, as the number of interactions that can be inferred exceeds the number of independent measurements. Different state-of-the-art tools for network inference use specific assumptions and simplifications to deal with underdetermination, and these influence the inferences. The outcome of network inference therefore varies between tools and can be highly complementary. Here we categorize the available tools according to the strategies that they use to deal with the problem of underdetermination. Such categorization allows an insight into why a certain tool is more appropriate for the specific research question or data set at hand.
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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.