Open research questions in Gene Regulatory Network Analysis
217 gap statements mined from Gene Regulatory Network Analysis papers in our 7.9M-paper local library, which holds 1,153 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.
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What the literature leaves open
The need to balance local and global regulatory relationships.
scHGNN: A single-cell gene regulatory network inference method based on heuristic graph neural networks · 2026 · DOIThe method is limited to stochastic chemical kinetics. The computational cost is still a challenge for very large state spaces. The method requires careful selection of parameters such as ε ∆t and α.
Flux-Preserving Adaptive Finite State Projection for Multiscale Stochastic Reaction Networks · 2026 · DOIBeyond the validated examples of multi-metal detection, it remains an open challenge whether ELMs can be designed to couple fundamentally different classes of inputs—for instance, linking cytokine sensing with mechanical stress in tissue, or combining pH and toxin monitoring in environmental settings.
While cell-machine interfaces have been employed to modulate host-gene circuit interactions, environmental perturbations typical of industrial bioreactor conditions remain underexplored.
Overriding Bioprocess Perturbations With a Cell–Machine Interface for Reliable Microbial Stress‐Response Control · 2026 · DOIHowever, to date, CRNs have only been described at the cell-type level: their characteristics in the distinct states that a single cell type can adopt have not been examined.
An invariant network architecture with broadly expressed regulators distinguishes cell-type from cell-state identity in situ · 2026 · DOIHow biological networks achieve robust control despite relying on imperfect, local information remains an important open question.
Local imperfect feedback control in nonequilibrium biophysical systems enabled by response constraints · 2026 · DOILabels of the y-axis are red when no data exists in the dataset for these mixtures and green when some data points exists in our database.
A Bayesian neural ordinary differential equations framework to study the effects of chemical mixtures on survival · 2025 · DOIThere is a need for efficient and viable methods for parameter identification problems in mathematical biology. Prior methods may not be suitable for large-scale coupled linear systems.
Future research could build on the study's findings to further understand cellular differentiation and developmental biology. The paper's framework could be used to analyze and understand the behavior of other biological systems.
A Unified Control of Cellular Differentiation: From Temporal Multistability to Spatial Pattern Formation in Gene Regulatory Networks · 2026 · DOIThe study notes that prior work has not fully addressed the challenge of understanding how genetically identical cells break symmetry to assume divergent fates.
A Unified Control of Cellular Differentiation: From Temporal Multistability to Spatial Pattern Formation in Gene Regulatory Networks · 2026 · DOIOne limitation of PGF-based inference is its dependence on analytical PGF solutions, which are generally unavailable for arbitrary reaction networks.
Efficiency, accuracy and robustness of probability generating function based parameter inference method for stochastic biochemical reactions · 2026 · DOIThe existing literature does not provide a clear understanding of the conditions under which the law of the diffusion approximation is identifiable. The paper aims to fill this gap by establishing necessary and sufficient conditions for identifiability.
The paper suggests that future research can apply the model to other areas of research, such as the study of stochastic thermodynamics and Maxwellian information ratchets. The paper suggests that future research can use the methodology to understand the deterioration of information transcription in biological systems.
The paper identifies the need for a model that can capture the deterioration of information transcription in biological systems. The paper identifies the need for a general recipe for modeling the decay in biological processes using stochastic thermodynamics and Maxwellian information ratchets.
As future work, we plan to include support for reachability properties using the Most Permissive update scheme. We included three different output formats, notably the JSON format, with the aim to include PYMODREV within the CoLoMoTo Notebook for easier integration with other analysis pipelines, already used by the community.
pyModRev: a Python Tool for Model Revision of Boolean Networks · 2026Despite the maturity of the theory, modern open-source implementations that combine CRNT structural analysis with symbolic ordinary differential equation (ODE) construction and robust numerical steady-state finding remain scarce.
Mantis-Delta: Mass-Action Network Theory and Steady-State Characterization for Chemical Reaction Networks · 2026 · DOIWhile we focused on step input responses, future investigations could explore other input types to determine whether additional functions emerge with different perturbation patterns, and incorporate noise, which has been shown to produce richer dynamics.
UNified FramewOrk for reguLatory Dynamics (UNFOLD): Dissecting robustness, plasticity, evolvability and canalisation of biological function · 2026 · DOIPrevious GRN inference methods have several limitations, including requiring substantial cost and time investment and being susceptible to individual and environmental variations.
The designs had noncentrality parameter 𝜆 = N/2 at all frequencies of interest and hence their performance was not limited by the restriction to an underlying grid.
Since Antonie van Leeuwenhoek’s improvements to microscopy centuries ago, we have looked at cells and seen what they do. But to see patterns, especially ones that dynamically morph and disappear, we must know what to look for, and theoretical models have regularly guided empirical study of cell behavior.
Current anti-counterfeiting research employs strategies like photoresponsive polymers and 3D printing of specialized materials.
Current progress and open challenges for applying deep learning across the biosciences.
From Mechanistic Models to AI Synergy: A Roadmap for Predictive and Personalized Biology · 2026 · DOIExperimental validation of the approach. Comparison with other methods for parameter identification problems in mathematical biology. Application of the approach to various problems in mathematical biology.
Evaluating the performance of SIGMA on larger datasets. Comparing SIGMA with other state-of-the-art methods. Exploring the potential applications of SIGMA in understanding molecular mechanisms, target identification, and drug design.
Further study of the mechanisms underlying acquisition of transcriptional cell states and cell-state switching in melanoma. Development of therapies that target the bistable parameter regions identified in the model. Experimental validation of the predictions made by the model.
Travelling Waves in Gene Expression: A Mathematical Model of Cell-State Dynamics in Melanoma · 2026 · DOI
Most-cited papers in Gene Regulatory Network Analysis
- Stochastic Gene Expression in a Single Cell · Science · 2002 · 4,949 citations
- A synthetic oscillatory network of transcriptional regulators · Nature · 2000 · 4,026 citations
- Molecular Computation of Solutions to Combinatorial Problems · Science · 1994 · 3,487 citations
- Functional cartography of complex metabolic networks · Nature · 2005 · 3,464 citations
- Systems Biology: A Brief Overview · Science · 2002 · 3,320 citations
- Specificity and Stability in Topology of Protein Networks · Science · 2002 · 2,598 citations
- Transcriptional Regulatory Networks in Saccharomyces cerevisiae · Science · 2002 · 2,314 citations
- Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data · Nature Methods · 2020 · 833 citations
- Quantitative and logic modelling of molecular and gene networks · Nature Reviews Genetics · 2015 · 430 citations
- A scalable pipeline for designing reconfigurable organisms · Proceedings of the National Academy of Sciences · 2020 · 392 citations
Most recent work
- Modelling drug-induced cellular perturbation responses with a biologically informed dual-branch transformer · Nature Machine Intelligence · 2026
- Foundation Models Improve Perturbation Response Prediction · bioRxiv · 2026
- Observability and approximate observability of Boolean control networks from finite offline data · Science China Information Sciences · 2026
- D-SPIN constructs regulatory network models from scRNA-seq that reveal organizing principles of perturbation response · Cell · 2026
- geneRNIB: a living benchmark for gene regulatory network inference · bioRxiv · 2026
- Non-oscillation of asynchronous stochastic logical networks through negative circuits of the joint interaction graph · Science China Information Sciences · 2026
- Engineering smart bacteria for the next generation · Cell Reports Medicine · 2026
- Molecular systems engineering of synthetic cells · Nature Chemistry · 2026
- Computational and AI-Driven Ecosystem for Structure-Based Covalent Drug Discovery · Accounts of Chemical Research · 2026
- Clustered stochastic gene circuits in dual-node heterogeneous systems: Adaptive learning strategies under a discrete spatio-temporal framework · Information Sciences · 2026
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