Evidence map›Paper›PMID 35265950›Full record

ArticleIFAC-PapersOnLine2021

Information Optimal Control for Single Particle Tracking Microscopy.

Nicholas A Vickers, Sean B Andersson

Abstract read
In one paragraph

Article in IFAC-PapersOnLine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Perspective: An outlook on fluorescence tracking.The Journal of chemical physics · 2025
    Article
  2. Article
  3. Real-Time Feedback-Driven Single-Particle Tracking: A Survey and Perspective.Small (Weinheim an der Bergstrasse, Germany) · 2022
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Nicholas A VickersDepartment of Mechanical Engineering, Boston University, Boston, MA 02155 USA.
Sean B AnderssonDepartment of Mechanical Engineering, Boston University, Boston, MA 02155 USA.

Funding

Joint estimation of motion model, model parameters, and particle trajectories in single particle trackingR01GM117039 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI ANDERSSON, SEAN B. · 2017 to 2021
$1.7M
NIGMS NIH HHS R01 GM117039
6 · The paper itself

Abstract

We consider the problem of designing a control policy for a laser scanning microscope (LSM) which will minimize the estimation uncertainty when identifying the state and motion model of a fluorescent biological particle. Using the information optimal design framework we pose an optimization problem which seeks to maximize the Fisher information of the particle's state. We then apply optimal control methods to determine the laser trajectory that maximizes a criterion based on the Fisher information. The resulting optimal control policy is a Bang-Singular control which moves the laser to the set of measurement locations that maximize the rate of information accumulation. Simulations demonstrate the ability of the resulting control system to position the laser to measure the particles location with a minimum uncertainty.

Indexed as

Information TheoryMicroscopesOptimal ControlOptimal Experimental DesignParameter EstimationSingle Particle Tracking

Identifiers

PMID35265950
PMCPMC8903092

What OpenQuestion holds

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Registered trials

None linked

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.