Evidence map›Paper›PMID 35230687›Full record

ArticleAdvances in experimental medicine and biology2022

Pathway Analysis for Cancer Research and Precision Oncology Applications.

Alessandro La Ferlita, Salvatore Alaimo, Alfredo Ferro, Alfredo Pulvirenti

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Article in Advances in experimental medicine and biology, 2022. 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
–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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

4 authors.

Alessandro La FerlitaDepartment of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, Italy.
Salvatore AlaimoDepartment of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, Italy.
Alfredo FerroDepartment of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, Italy.
Alfredo PulvirentiDepartment of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, Italy. alfredo.pulvirenti@unict.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the advent of OMICs technologies, several bioinformatics methods have been developed to infer biological knowledge from such data. Pathway analysis methodologies help integrate multi-OMICs data and find altered function in known metabolic and signaling pathways. As widely known, such alterations promote the cancer cells' progression and the maintenance of the malignant state. In this chapter, we provide (i) a comprehensive description of the primary data sources for omics data, cancer "omics" projects, and precision oncology knowledge bases; (ii) a survey of the main biological pathway databases; (iii) and a global view of the principal pathway analysis tools and methodologies, describing their main characteristics and shortcomings highlighting their potential applications in cancer research and precision oncology.

Indexed as

NeoplasmsComputational BiologyGenomicsHumansMedical OncologyPrecision MedicineCancerFunctional Class ScoringMetabolic pathwaysOver-Representation AnalysisPathway analysisPathway databasesPathwaysPathway topology-based analysisPhenotype simulationPrecision oncologySignaling pathways

Identifiers

PMID35230687

What OpenQuestion holds

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Registered trials

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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.