Toolkit/input reconstruction algorithm

input reconstruction algorithm

Computational Method·Research·Since 2023

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

Derived

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.

Taxonomy & Function

Primary hierarchy

Technique Branch

Method: A concrete computational method used to design, rank, or analyze an engineered system.

Target processes

No target processes tagged yet.

Input: Light

Implementation Constraints

cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationimplementation constraint: spectral hardware requirementoperating role: builder

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

Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication

Supporting Sources

Ranked Claims

Claim 1algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 2algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 3algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 4algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 5algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 6algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 7algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 8algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 9algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 10algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 11algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 12algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 13algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 14algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 15algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 16algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 17algorithm performancesupports2023Source 1needs review

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.
detection accuracy window 1 mindetection delay 5 min
Claim 18performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour
Claim 19performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour
Claim 20performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour
Claim 21performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour
Claim 22performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour
Claim 23performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour
Claim 24performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour
Claim 25performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour
Claim 26performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour
Claim 27performancesupports2023Source 1needs review

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.
channel capacity 6 bits per hour

Approval Evidence

1 source1 linked approval claimfirst-pass slug input-reconstruction-algorithm
The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence

Source:

algorithm performancesupports

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.

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

input reconstruction algorithm and model bioinformatics analysis address a similar problem space.

Shared frame: same top-level item type; same primary input modality: light

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. 1.
    StructuralSource 1PLoS Computational Biology2023Claim 16Claim 17Claim 17

    Extracted from this source document.