Evidence map›Paper›PMID 26811605›Full record

ReviewWorld journal of gastroenterology2016

Integration of genome scale data for identifying new players in colorectal cancer.

Viktorija Sokolova, Elisabetta Crippa, Manuela Gariboldi

Open access · hybridAbstract readReview
In one paragraph

Review in World journal of gastroenterology, 2016. 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
1.2field-weighted citation impact, top 21% 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, 5 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

3 authors at 1 institution in 1 country.

Viktorija SokolovaViktorija Sokolova, Elisabetta Crippa, Manuela Gariboldi, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milano, Italy.
Elisabetta CrippaViktorija Sokolova, Elisabetta Crippa, Manuela Gariboldi, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milano, Italy.
Manuela GariboldiViktorija Sokolova, Elisabetta Crippa, Manuela Gariboldi, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milano, Italy.
Fondazione IRCCS Istituto Nazionale dei Tumori · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancers (CRCs) display a wide variety of genomic aberrations that may be either causally linked to their development and progression, or might serve as biomarkers for their presence. Recent advances in rapid high-throughput genetic and genomic analysis have helped to identify a plethora of alterations that can potentially serve as new cancer biomarkers, and thus help to improve CRC diagnosis, prognosis, and treatment. Each distinct data type (copy number variations, gene and microRNAs expression, CpG island methylation) provides an investigator with a different, partially independent, and complementary view of the entire genome. However, elucidation of gene function will require more information than can be provided by analyzing a single type of data. The integration of knowledge obtained from different sources is becoming increasingly essential for obtaining an interdisciplinary view of large amounts of information, and also for cross-validating experimental results. The integration of numerous types of genetic and genomic data derived from public sources, and via the use of ad-hoc bioinformatics tools and statistical methods facilitates the discovery and validation of novel, informative biomarkers. This combinatory approach will also enable researchers to more accurately and comprehensively understand the associations between different biologic pathways, mechanisms, and phenomena, and gain new insights into the etiology of CRC.

Indexed as

Computational BiologySystems IntegrationAnimalsBiomarkers, TumorColorectal NeoplasmsDatabases, GeneticDNA Copy Number VariationsDNA MethylationEpigenesis, GeneticGene DosageGene Expression ProfilingGene Expression Regulation, NeoplasticGenetic Predisposition to DiseaseGenomicsHigh-Throughput Nucleotide SequencingHumansBiomarkers, TumorMicroRNAsRNA, MessengerColorectal cancerCopy number variationsData integrationGene expressionMethylomemiRNA expression

Identifiers

PMID26811605
PMCPMC4716057
OpenAlexW2411915702

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.