Evidence map›Paper›PMID 33014344›Full record

ArticleF1000Research2020

Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX.

Aikaterini Alexaki, Jacob Kames, Gaya K Hettiarachchi, John C Athey, Upendra K Katneni, Ryan C Hunt, Nobuko Hamasaki-Katagiri, David D Holcomb, Michael DiCuccio, Haim Bar and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in F1000Research, 2020. 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
0.2field-weighted citation impact, top 51% of its field
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, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. RiboDoc: A Docker-based package for ribosome profiling analysis.Computational and structural biotechnology journal · 2021
    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

12 authors at 4 institutions in 1 country.

Aikaterini Alexaki *Center for Biologics Evaluation and Research, Food and Drug Administration, USA, Silver Spring, MD, 20993, USA.
Jacob Kames *Center for Biologics Evaluation and Research, Food and Drug Administration, USA, Silver Spring, MD, 20993, USA.
Gaya K HettiarachchiCenter for Biologics Evaluation and Research, Food and Drug Administration, USA, Silver Spring, MD, 20993, USA.
John C AtheyCenter for Biologics Evaluation and Research, Food and Drug Administration, USA, Silver Spring, MD, 20993, USA.
Upendra K KatneniCenter for Biologics Evaluation and Research, Food and Drug Administration, USA, Silver Spring, MD, 20993, USA.
Ryan C HuntCenter for Biologics Evaluation and Research, Food and Drug Administration, USA, Silver Spring, MD, 20993, USA.
Nobuko Hamasaki-KatagiriCenter for Biologics Evaluation and Research, Food and Drug Administration, USA, Silver Spring, MD, 20993, USA.
David D HolcombCenter for Biologics Evaluation and Research, Food and Drug Administration, USA, Silver Spring, MD, 20993, USA.
Michael DiCuccioNational Center of Biotechnology Information, National Institutes of Health, USA, Bethesda, MD, 20892, USA.
Haim BarDepartment of Statistics, University of Connecticut, Storrs, CT, 06269, USA.
Anton A KomarCenter for Gene Regulation in Health and Disease, Cleveland State University, Cleveland, OH, 44115, USA.
Chava Kimchi-SarfatyCenter for Biologics Evaluation and Research, Food and Drug Administration, USA, Silver Spring, MD, 20993, USA.ORCID 0000-0002-9355-8585
Center for Biologics Evaluation and Research · USCleveland State University · USNational Institutes of Health · USUniversity of Connecticut · US

Funding

Safer and more effective FIX therapeutics: impact of codon optimizationR01HL151392 · NHLBI · CLEVELAND STATE UNIVERSITY · PI KOMAR, ANTON A. · 2020 to 2023
$1.5M
Understanding the impact of disease causing mutations in FIXR15HL121779 · NHLBI · CLEVELAND STATE UNIVERSITY · PI KOMAR, ANTON A. · 2014 to 2014
$437k
NHLBI NIH HHS R01 HL151392NHLBI NIH HHS R15 HL121779
6 · The paper itself

Abstract

Ribosome profiling provides the opportunity to evaluate translation kinetics at codon level resolution. Here, we describe ribosome profiling data, generated from two HEK293T cell lines. The ribosome profiling data are composed of Ribo-seq (mRNA sequencing data from ribosome protected fragments) and RNA-seq data (total RNA sequencing). The two HEK293T cell lines each express a version of the

Indexed as

Protein BiosynthesisCodonFactor IXHEK293 CellsHumansRibosomesCodonFactor IXcodon optimizationcodon pair usagecodon usageprotein therapeuticsRibo-seqRibosome profilingRNA-seqtranslation kinetics

Identifiers

PMID33014344
PMCPMC7509596
OpenAlexW3010821287

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.