ReviewEngineering biology2024
Engineering biology and automation-Replicability as a design principle.
Review in Engineering biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Mechanobiology in Action: Biomaterials, Devices, and the Cellular Machinery of Force Sensing.Biomolecules · 2025Review
- Engineering biology and automation-Replicability as a design principle.Engineering biology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Applications in engineering biology increasingly share the need to run operations on very large numbers of biological samples. This is a direct consequence of the application of good engineering practices, the limited predictive power of current computational models and the desire to investigate very large design spaces in order to solve the hard, important problems the discipline promises to solve. Automation has been proposed as a key component for running large numbers of operations on biological samples. This is because it is strongly associated with higher throughput, and with higher replicability (thanks to the reduction of human input). The authors focus on replicability and make the point that, far from being an additional burden for automation efforts, replicability should be considered central to the design of the automated pipelines processing biological samples at scale-as trialled in biofoundries. There cannot be successful automation without effective error control. Design principles for an IT infrastructure that supports replicability are presented. Finally, the authors conclude with some perspectives regarding the evolution of automation in engineering biology. In particular, they speculate that the integration of hardware and software will show rapid progress, and offer users a degree of control and abstraction of the robotic infrastructure on a level significantly greater than experienced today.
Indexed as
Identifiers
What OpenQuestion holds
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.