ArticleNature communications2021
Finding gene network topologies for given biological function with recurrent neural network.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Investigation Into the Collection and Isolation Workflows of Extracellular Vesicles From Tears.Journal of extracellular biology · 2026Article
- GCAD: A Computational Framework for Mammalian Genetic Program Computer-Aided Design.ACS synthetic biology · 2026Article
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- Decoding protein binding plasticity via integrated deep ribosome display and deep learning.Communications biology · 2025Article
- Practical indistinguishability in a gene regulatory network inference problem, a case study.ArXiv · 2025Article
- Learning stochastic processes with intrinsic noise from cross-sectional biological data.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- GCAD: a Computational Framework for Mammalian Genetic Program Computer-Aided Design.bioRxiv : the preprint server for biology · 2025Article
- AI-Empowered Electrochemical Sensors for Biomedical Applications: Technological Advances and Future Challenges.Biosensors · 2025Review
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- An end-to-end mass spectrometry data classification model with a unified architecture.Scientific reports · 2025Article
- AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks.eLife · 2025Article
- BADDADAN: Mechanistic modelling of time-series gene module expression.Quantitative plant biology · 2025Article
- Progress and opportunities of foundation models in bioinformatics.Briefings in bioinformatics · 2024Review
- Learning interpretable dynamics of stochastic complex systems from experimental data.Nature communications · 2024Article
- Estimation of multiple networks with common structures in heterogeneous subgroups.Journal of multivariate analysis · 2024Article
- Contact lenses as novel tear fluid sampling vehicles for total RNA isolation, precipitation, and amplification.Scientific reports · 2024Article
- Model-based parcellation of diffusion MRI of injured spinal cord predicts hand use impairment and recovery in squirrel monkeys.Behavioural brain research · 2024Article
- Applications of artificial intelligence and machine learning in dynamic pathway engineering.Biochemical Society transactions · 2023Review
- Bayesian Optimization for Design of Multiscale Biological Circuits.ACS synthetic biology · 2023Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Searching for possible biochemical networks that perform a certain function is a challenge in systems biology. For simple functions and small networks, this can be achieved through an exhaustive search of the network topology space. However, it is difficult to scale this approach up to larger networks and more complex functions. Here we tackle this problem by training a recurrent neural network (RNN) to perform the desired function. By developing a systematic perturbative method to interrogate the successfully trained RNNs, we are able to distill the underlying regulatory network among the biological elements (genes, proteins, etc.). Furthermore, we show several cases where the regulation networks found by RNN can achieve the desired biological function when its edges are expressed by more realistic response functions, such as the Hill-function. This method can be used to link topology and function by helping uncover the regulation logic and network topology for complex tasks.
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Registered trials
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