Evidence map›Paper›PMID 34165723›Full record

ReviewMethods in molecular biology (Clifton, N.J.)2021

Pseudogene Profiling for Cancer Subtype Classification.

Yan Zhang, Deyou Zheng

Abstract readReview
PubMed Publisher
In one paragraph

Review in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 39% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

2 authors at 2 institutions in 1 country.

Yan ZhangDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA. yanzhang.biomed@gmail.com.
Deyou ZhengDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA. deyou.zheng@einsteinmed.org.
Albert Einstein College of Medicine · USThe Ohio State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although long thought of as "gene relics," pseudogenes have recently gained research and medical interests because of their potential impacts on cellular pathways and of their clinical relevance. Studies have profiled pseudogenes at both DNA and RNA levels in cancers. Differences in pseudogene expression (RNA) or occurrence (DNA) help cancer subtype classification, which in turn can contribute to improving treatment selection in precision medicine. Such differences are also associated with clinical outcomes, such as patient survival.Here we review the existing methods on pseudogene profiling and discuss the application scenarios, as well as their relevant issues and challenges.

Indexed as

PseudogenesDatasets as TopicDNA, NeoplasmGene Expression Regulation, NeoplasticHumansMolecular Sequence AnnotationMultigene FamilyNeoplasm ProteinsNeoplasmsPatientsPrognosisRNA, MessengerRNA, NeoplasmDNA, NeoplasmNeoplasm ProteinsRNA, MessengerRNA, NeoplasmCancerDNA and RNA profilingPseudogeneSubtype classification

Identifiers

PMID34165723
OpenAlexW3175031836

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.