ArticleProceedings of the National Academy of Sciences of the United States of America2020
Genome-scale transcriptional dynamics and environmental biosensing.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
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Who cites it
13 citing papers in PubMed.
- Advances and perspectives in genetically encoded biosensors for biomarker detection and theranostic circuits.Synthetic and systems biotechnology · 2027Review
- Bacteria as living biosensors for DNA.Nature reviews bioengineering · 2026Article
- Environmental monitoring from the air with hyperspectral reporters.Nature biotechnology · 2026Article
- Genome-wide analysis of the SnRK gene family in Caragana Korshinskii and their expression profiling under drought and nitrogen deposition.BMC genomics · 2025Article
- Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology.Biodesign research · 2024Article
- High-resolution temporal profiling of E. coli transcriptional response.Nature communications · 2023Article
- A Microfluidic Platform for Screening Gene Expression Dynamics across Yeast Strain Libraries.Bio-protocol · 2023Article
- Genes selection using deep learning and explainable artificial intelligence for chronic lymphocytic leukemia predicting the need and time to therapy.Frontiers in oncology · 2023Article
- Article
- Sensory Systems and Transcriptional Regulation inFrontiers in bioengineering and biotechnology · 2022Review
- Applications, challenges, and needs for employing synthetic biology beyond the lab.Nature communications · 2021Review
- Genome-scale transcriptional dynamics and environmental biosensing.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Deep learning models in genomics; are we there yet?Computational and structural biotechnology journal · 2020Review
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
Genome-scale technologies have enabled mapping of the complex molecular networks that govern cellular behavior. An emerging theme in the analyses of these networks is that cells use many layers of regulatory feedback to constantly assess and precisely react to their environment. The importance of complex feedback in controlling the real-time response to external stimuli has led to a need for the next generation of cell-based technologies that enable both the collection and analysis of high-throughput temporal data. Toward this end, we have developed a microfluidic platform capable of monitoring temporal gene expression from over 2,000 promoters. By coupling the "Dynomics" platform with deep neural network (DNN) and associated explainable artificial intelligence (XAI) algorithms, we show how machine learning can be harnessed to assess patterns in transcriptional data on a genome scale and identify which genes contribute to these patterns. Furthermore, we demonstrate the utility of the Dynomics platform as a field-deployable real-time biosensor through prediction of the presence of heavy metals in urban water and mine spill samples, based on the the dynamic transcription profiles of 1,807 unique
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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.