Evidence map›Paper›PMID 26200870›Full record

ArticleBiophysical journal2015

An information-based approach to change-point analysis with applications to biophysics and cell biology.

Paul A Wiggins

Abstract read
In one paragraph

Article in Biophysical journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Stepwise DNA unwinding gates TnpB genome-editing activity.bioRxiv : the preprint server for biology · 2026
    Article
  3. Sensing the shape of a surface by tightly surface-bound filaments.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Article
  5. Article
  6. Article
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  9. Article
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  11. Patterns (New York, N.Y.) · 2021
    Article
  12. Article
  13. Article
  14. Cas9 interrogates DNA in discrete steps modulated by mismatches and supercoiling.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  15. Article
  16. Article
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

1 author.

Paul A WigginsDepartments of Physics, Bioengineering and Microbiology, University of Washington, Seattle, Washington. Electronic address: pwiggins@uw.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article describes the application of a change-point algorithm to the analysis of stochastic signals in biological systems whose underlying state dynamics consist of transitions between discrete states. Applications of this analysis include molecular-motor stepping, fluorophore bleaching, electrophysiology, particle and cell tracking, detection of copy number variation by sequencing, tethered-particle motion, etc. We present a unified approach to the analysis of processes whose noise can be modeled by Gaussian, Wiener, or Ornstein-Uhlenbeck processes. To fit the model, we exploit explicit, closed-form algebraic expressions for maximum-likelihood estimators of model parameters and estimated information loss of the generalized noise model, which can be computed extremely efficiently. We implement change-point detection using the frequentist information criterion (which, to our knowledge, is a new information criterion). The frequentist information criterion specifies a single, information-based statistical test that is free from ad hoc parameters and requires no prior probability distribution. We demonstrate this information-based approach in the analysis of simulated and experimental tethered-particle-motion data.

Indexed as

AlgorithmsModels, BiologicalComputer SimulationDNAInformation TheoryLac RepressorsLikelihood FunctionsMotionStochastic ProcessesDNALac Repressors

Identifiers

PMID26200870
PMCPMC4621614

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.