Toolkit/input reconstruction algorithm
input reconstruction algorithm
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
The input reconstruction algorithm is a computational method used to infer prior light pulse inputs from cellular signaling outputs. In the cited MAPK/ERK communication study, it detected light pulses with 1-minute accuracy 5 minutes after their occurrence.
Usefulness & Problems
Why this is useful
This method is useful for decoding temporally patterned light stimulation from downstream signaling measurements in an optogenetic communication setting. The available evidence indicates that it enabled reconstruction of pulse timing in a MAPK/ERK pathway study and supported quantification of pathway information transmission.
Problem solved
It addresses the problem of inferring when light pulses occurred from observed cellular signaling outputs rather than from direct input logs alone. In the cited study, this reconstruction capability was used in the context of random light pulse train stimulation to analyze MAPK/ERK signaling communication.
Problem links
Need precise spatiotemporal control with light input
DerivedThe input reconstruction algorithm is a computational method used to infer prior light pulse inputs from cellular signaling outputs. In the cited MAPK/ERK communication study, it detected light pulses with 1-minute accuracy 5 minutes after their occurrence.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete computational method used to design, rank, or analyze an engineered system.
Mechanisms
computational reconstruction of light pulse timing from signaling outputscomputational reconstruction of light pulse timing from signaling outputsTechniques
Computational DesignTarget processes
No target processes tagged yet.
Input: Light
Implementation Constraints
The available evidence places the method in an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter under random light pulse train stimulation. No further implementation details are provided here regarding software, model inputs, preprocessing, parameterization, or deployment requirements.
The supplied evidence only documents pulse detection accuracy in one MAPK/ERK optogenetic study and does not describe the algorithmic architecture, training procedure, or generalizability. No independent replication, benchmarking against alternative reconstruction methods, or validation across other pathways, cell types, or input modalities is provided here.
Validation
Supporting Sources
Ranked Claims
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
In an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter, the MAPK/ERK pathway channel capacity is at least 6 bits per hour under random light pulse train stimulation.
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
Approval Evidence
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence
Source:
The input reconstruction algorithm detects light pulses with 1-minute accuracy 5 minutes after their occurrence.
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence.
Source:
Comparisons
Source-backed strengths
The reported performance is detection of light pulses with 1-minute accuracy 5 minutes after pulse occurrence. The method was applied in a system where an epithelial cell line expressed a light-activatable FGF receptor and an ERK activity reporter, within a study reporting at least 6 bits per hour of MAPK/ERK channel capacity.
Source:
By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour.
Compared with mathematical model of light-induced expression kinetics
input reconstruction algorithm and mathematical model of light-induced expression kinetics address a similar problem space.
Shared frame: same top-level item type; same primary input modality: light
Compared with model bioinformatics analysis
input reconstruction algorithm and model bioinformatics analysis address a similar problem space.
Shared frame: same top-level item type; same primary input modality: light
Compared with molecular dynamics simulations
input reconstruction algorithm and molecular dynamics simulations address a similar problem space.
Shared frame: same top-level item type; same primary input modality: light
Relative tradeoffs: appears more independently replicated; looks easier to implement in practice.
Ranked Citations
- 1.