Evidence map›Paper›PMID 34948010›Full record

ReviewInternational journal of molecular sciences2021

Systems Biology Approaches to Decipher the Underlying Molecular Mechanisms of Glioblastoma Multiforme.

Ali Kaynar, Ozlem Altay, Xiangyu Li, Cheng Zhang, Hasan Turkez, Mathias Uhlén, Saeed Shoaie, Adil Mardinoglu

Open access · goldAbstract readReview
In one paragraph

Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

8 citing papers in PubMed, 16 citations in OpenAlex.

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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

8 authors at 3 institutions in 3 countries.

Ali KaynarCentre for Host-Microbiome Interactions, Faculty of Dentistry, Oral and Craniofacial Sciences, King's College London, London SE1 9RT, UK.
Ozlem AltayScience for Life Laboratory, Royal Institute of Technology (KTH), SE-10691 Stockholm, Sweden.
Xiangyu LiScience for Life Laboratory, Royal Institute of Technology (KTH), SE-10691 Stockholm, Sweden.ORCID 0000-0002-8301-9959
Cheng ZhangScience for Life Laboratory, Royal Institute of Technology (KTH), SE-10691 Stockholm, Sweden.ORCID 0000-0002-3721-8586
Hasan TurkezMedical Biology Department, Faculty of Medicine, Atatürk University, Erzurum TR-25240, Turkey.ORCID 0000-0002-7046-8990
Mathias UhlénScience for Life Laboratory, Royal Institute of Technology (KTH), SE-10691 Stockholm, Sweden.
Saeed ShoaieCentre for Host-Microbiome Interactions, Faculty of Dentistry, Oral and Craniofacial Sciences, King's College London, London SE1 9RT, UK.
Adil MardinogluCentre for Host-Microbiome Interactions, Faculty of Dentistry, Oral and Craniofacial Sciences, King's College London, London SE1 9RT, UK.ORCID 0000-0002-4254-6090
Science for Life Laboratory · SEKing's College London · GBAtatürk University · TR

Funding

Knut and Alice Wallenberg Foundation 72210
6 · The paper itself

Abstract

Glioblastoma multiforme (GBM) is one of the most malignant central nervous system tumors, showing a poor prognosis and low survival rate. Therefore, deciphering the underlying molecular mechanisms involved in the progression of the GBM and identifying the key driver genes responsible for the disease progression is crucial for discovering potential diagnostic markers and therapeutic targets. In this context, access to various biological data, development of new methodologies, and generation of biological networks for the integration of multi-omics data are necessary for gaining insights into the appearance and progression of GBM. Systems biology approaches have become indispensable in analyzing heterogeneous high-throughput omics data, extracting essential information, and generating new hypotheses from biomedical data. This review provides current knowledge regarding GBM and discusses the multi-omics data and recent systems analysis in GBM to identify key biological functions and genes. This knowledge can be used to develop efficient diagnostic and treatment strategies and can also be used to achieve personalized medicine for GBM.

Indexed as

Biomarkers, TumorBrain NeoplasmsEarly Detection of CancerGlioblastomaHumansPrognosisSurvival AnalysisSystems BiologyBiomarkers, Tumorgenome-scale metabolic modelsglioblastomamulti-omics datasystems biology

Identifiers

PMID34948010
PMCPMC8706582
OpenAlexW4200043970

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.