Evidence map›Paper›PMID 33651354›Full record

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

Urinary Nucleic Acid in Tumor: Bioinformatics Approaches.

Davide Angeli

Abstract read
PubMed Publisher
In one paragraph

Article 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
0.4field-weighted citation impact, top 40% 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, 1 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

1 author at 1 institution in 1 country.

Davide AngeliUnit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST), Meldola, Italy. davide.angeli@irst.emr.it.
Istituti di Ricovero e Cura a Carattere Scientifico · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Application of next generation sequencing techniques in the field of liquid biopsy, in particular urine, requires specific bioinformatics methods in order to deal with its peculiarity. Many aspects of cancer can be explored starting from nucleic acids, especially from cell-free DNA and circulating tumor DNA in order to characterize cancer. It is possible to detect small mutations, as single nucleotide variants, small insertions and deletions, copy-number alterations, and epigenetic profiles. Due to the low fraction of circulating tumor DNA over the whole cell-free DNA, some methods have been exploited. One of them is the application of unique barcodes to each DNA fragment in order to lower the limit of detection of cancer-related variants. Some bioinformatics workflows and tools are the same of a classic analysis of tumor tissue, but there are some steps in which specific algorithms have to be introduced.

Indexed as

AnimalsBiomarkers, TumorCell-Free Nucleic AcidsDNA Copy Number VariationsDNA MethylationEpigenesis, GeneticGenomicsHigh-Throughput Nucleotide SequencingHumansLiquid BiopsyNeoplasmsBiomarkers, TumorCell-Free Nucleic AcidsBioinformaticsCancercfDNACNVctDNAMethylationSNVUrine

Identifiers

PMID33651354
OpenAlexW3133528478

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.