Evidence map›Paper›PMID 38384132›Full record

ArticleBiophysical journal2024

Deep-LASI, single-molecule data analysis software.

Pooyeh Asadiatouei, Clemens-Bässem Salem, Simon Wanninger, Evelyn Ploetz, Don C Lamb

Abstract read
In one paragraph

Article in Biophysical journal, 2024. 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. Article
  2. Review
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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

5 authors.

Pooyeh AsadiatoueiDepartment of Chemistry and Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, Munich, Germany.
Clemens-Bässem SalemDepartment of Chemistry and Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, Munich, Germany.
Simon WanningerDepartment of Chemistry and Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, Munich, Germany.
Evelyn PloetzDepartment of Chemistry and Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, Munich, Germany. Electronic address: evelyn.ploetz@lmu.de.
Don C LambDepartment of Chemistry and Center for NanoScience (CeNS), Ludwig-Maximilians-Universität München, Munich, Germany. Electronic address: d.lamb@lmu.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

By avoiding ensemble averaging, single-molecule methods provide novel means of extracting mechanistic insights into function of material and molecules at the nanoscale. However, one of the big limitations is the vast amount of data required for analyzing and extracting the desired information, which is time-consuming and user dependent. Here, we introduce Deep-LASI, a software suite for the manual and automatic analysis of single-molecule traces, interactions, and the underlying kinetics. The software can handle data from one-, two- and three-color fluorescence data, and was particularly designed for the analysis of two- and three-color single-molecule fluorescence resonance energy transfer experiments. The functionalities of the software include: the registration of multiple-channels, trace sorting and categorization, determination of the photobleaching steps, calculation of fluorescence resonance energy transfer correction factors, and kinetic analyses based on hidden Markov modeling or deep neural networks. After a kinetic analysis, the ensuing transition density plots are generated, which can be used for further quantification of the kinetic parameters of the system. Each step in the workflow can be performed manually or with the support of machine learning algorithms. Upon reading in the initial data set, it is also possible to perform the remaining analysis steps automatically without additional supervision. Hence, the time dedicated to the analysis of single-molecule experiments can be reduced from days/weeks to minutes. After a thorough description of the functionalities of the software, we also demonstrate the capabilities of the software via the analysis of a previously published dynamic three-color DNA origami structure fluctuating between three states. With the drastic time reduction in data analysis, new types of experiments become realistically possible that complement our currently available palette of methodologies for investigating the nanoworld.

Indexed as

Fluorescence Resonance Energy TransferSingle Molecule ImagingSoftwareData AnalysisKinetics

Identifiers

PMID38384132
PMCPMC11393668

What OpenQuestion holds

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Registered trials

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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.