Evidence map›Paper›PMID 33210213›Full record

ReviewBiophysical reviews2020

Recent advances in point spread function engineering and related computational microscopy approaches: from one viewpoint.

Yoav Shechtman

Abstract readReview
In one paragraph

Review in Biophysical reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  4. Article
  5. 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

1 author.

Yoav ShechtmanDepartment of Biomedical Engineering and Lorry Lokey Interdisciplinary Center for Life Sciences and Engineering, Technion-Israel Institute of Technology, 3200003, Haifa, Israel. yoavsh@bm.technion.ac.il.ORCID https://orcid.org/0000-0001-8498-5203

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This personal hybrid review piece, written in light of my recipience of the UIPAB 2020 young investigator award, contains a mixture of my scientific biography and work so far. This paper is not intended to be a comprehensive review, but only to highlight my contributions to computation-related aspects of super-resolution microscopy, as well as their origins and future directions.

Indexed as

Deep learningPoint-spread function engineeringSingle particle trackingSuper resolution microscopy

Identifiers

PMID33210213
PMCPMC7755951

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.