Evidence map›Paper›PMID 36293163›Full record

ArticleInternational journal of molecular sciences2022

Flow-Seq Evaluation of Translation Driven by a Set of Natural

Ekaterina S Komarova, Anna N Slesarchuk, Maria P Rubtsova, Ilya A Osterman, Alexey E Tupikin, Dmitry V Pyshnyi, Olga A Dontsova, Marsel R Kabilov, Petr V Sergiev

Abstract read
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In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Approaches for Studying Context Specificity of Translation Inhibitor Action.International journal of molecular sciences · 2026
    Review
  2. 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

9 authors.

Ekaterina S KomarovaInstitute of Functional Genomics, Lomonosov Moscow State University, 119992 Moscow, Russia.ORCID 0000-0002-6285-6395
Anna N SlesarchukDepartment of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia.
Maria P RubtsovaDepartment of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia.
Ilya A OstermanCenter for Life Sciences, Skolkovo Institute of Science and Technology, Skolkovo, 143025 Moscow, Russia.
Alexey E TupikinInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia.
Dmitry V PyshnyiInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia.ORCID 0000-0002-2587-3719
Olga A DontsovaDepartment of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia.
Marsel R KabilovInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia.ORCID 0000-0003-2777-0833
Petr V SergievInstitute of Functional Genomics, Lomonosov Moscow State University, 119992 Moscow, Russia.ORCID 0000-0001-8866-1863

Funding

Russian Foundation for Basic Research 17-00-00366Russian Foundation for Basic Research 17-00-00367Russian Science Foundation 21-64-00006
6 · The paper itself

Abstract

Flow-seq is a method that combines fluorescently activated cell sorting and next-generation sequencing to deduce a large amount of data about translation efficiency from a single experiment. Here, we constructed a library of fluorescent protein-based reporters preceded by a set of 648 natural 5'-untranslated regions (5'-UTRs) of

Indexed as

Escherichia coliRibosomes5' Untranslated RegionsGene LibraryProtein Biosynthesis5' Untranslated RegionsFlow-seqribosometranslationtranslation efficiencyuntranslated region

Identifiers

PMID36293163
PMCPMC9604319

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.