ReviewCurrent opinion in biotechnology2020
Network inference in systems biology: recent developments, challenges, and applications.
Review in Current opinion in biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 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
48 citing papers in PubMed.
- From prior knowledge to data-informed models: a review of Boolean network inference.Briefings in bioinformatics · 2026Review
- Deciphering global transcriptional dynamics coordinated by gene-gene regulatory interactions using single-cell data.Molecular systems biology · 2026Article
- Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer.Molecular oncology · 2026Article
- Network methods for diagonal integration of unpaired single-cell multiomics data: a review.Bioinformatics (Oxford, England) · 2026Review
- Impact of variability in cell generation times on cell-to-cell variability of protein concentrations.bioRxiv : the preprint server for biology · 2026Article
- Inference of Genetic Networks from Pseudo Time Series of Single-cell Gene Expression Data using Modified Random Forests.Bulletin of mathematical biology · 2026Article
- AI-based methods for the assessment of DNA damage and repair mechanisms.Frontiers in systems biology · 2026Review
- Monod: model-based discovery and integration through fitting stochastic transcriptional dynamics to single-cell sequencing data.Nature methods · 2025Article
- Uncovering Cellular Interactome Drivers of Immune Checkpoint Inhibitor Response in Advanced Melanoma Patients.Cellular and molecular bioengineering · 2025Article
- CYB5R4 sustains endothelial proliferation and ischemia-induced angiogenesis by maintaining RRM2-dependent nucleotide balance.bioRxiv : the preprint server for biology · 2025Article
- Cyclo-stationary distributions of mRNA and Protein counts for random cell division times.bioRxiv : the preprint server for biology · 2025Article
- Gene expression inference based on graph neural networks using L1000 data.Briefings in bioinformatics · 2025Article
- The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.Annual review of biomedical engineering · 2025Review
- Are the tools fit for purpose? Network inference algorithms evaluated on a simulated lipidomics network.Bioinformatics advances · 2025Article
- Unlocking hematopoietic stem cell potential: integrative computational approaches for genomic and transcriptomic analysis.Frontiers in cell and developmental biology · 2025Review
- Unifying fragmented perspectives with additive deep learning for high-dimensional models from partial faceted datasets.npj biological physics and mechanics · 2025Article
- Unravelling the genetic basis and regulation networks related to fibre quality improvement using chromosome segment substitution lines in cotton.Plant biotechnology journal · 2024Article
- k- Strong Inference Algorithm: A Hybrid Information Theory Based Gene Network Inference Algorithm.Molecular biotechnology · 2024Article
- Inference of gene regulatory networks based on directed graph convolutional networks.Briefings in bioinformatics · 2024Article
- Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data.Bioinformatics (Oxford, England) · 2024Article
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.
Funding
Abstract
One of the most interesting, difficult, and potentially useful topics in computational biology is the inference of gene regulatory networks (GRNs) from expression data. Although researchers have been working on this topic for more than a decade and much progress has been made, it remains an unsolved problem and even the most sophisticated inference algorithms are far from perfect. In this paper, we review the latest developments in network inference, including state-of-the-art algorithms like PIDC, Phixer, and more. We also discuss unsolved computational challenges, including the optimal combination of algorithms, integration of multiple data sources, and pseudo-temporal ordering of static expression data. Lastly, we discuss some exciting applications of network inference in cancer research, and provide a list of useful software tools for researchers hoping to conduct their own network inference analyses.
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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.