Evidence map›Paper›PMID 32967266›Full record

ReviewCancers2020

Applications of Genome-Wide Screening and Systems Biology Approaches in Drug Repositioning.

Elyas Mohammadi, Rui Benfeitas, Hasan Turkez, Jan Boren, Jens Nielsen, Mathias Uhlen, Adil Mardinoglu

Abstract readReview
In one paragraph

Review in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Emerging therapeutics.Journal of translational medicine · 2021
    Article
  9. Article
  10. 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

7 authors.

Elyas MohammadiScience for Life Laboratory, KTH-Royal Institute of Technology, SE-17121 Stockholm, Sweden.
Rui BenfeitasNational Bioinformatics Infrastructure Sweden (NBIS), Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, SE-10691 Stockholm, Sweden.ORCID 0000-0001-7972-0083
Hasan TurkezDepartment of Medical Biology, Faculty of Medicine, Atatürk University, 25240 Erzurum, Turkey.
Jan BorenDepartment of Molecular and Clinical Medicine, University of Gothenburg, The Wallenberg Laboratory, Sahlgrenska University Hospital, SE-41345 Gothenburg, Sweden.ORCID 0000-0003-0786-8091
Jens NielsenDepartment of Biology and Biological Engineering, Chalmers University of Technology, SE-41296 Gothenburg, Sweden.
Mathias UhlenScience for Life Laboratory, KTH-Royal Institute of Technology, SE-17121 Stockholm, Sweden.
Adil MardinogluScience for Life Laboratory, KTH-Royal Institute of Technology, SE-17121 Stockholm, Sweden.

Funding

Knut och Alice Wallenbergs Stiftelse 2019
6 · The paper itself

Abstract

Modern drug discovery through de novo drug discovery entails high financial costs, low success rates, and lengthy trial periods. Drug repositioning presents a suitable approach for overcoming these issues by re-evaluating biological targets and modes of action of approved drugs. Coupling high-throughput technologies with genome-wide essentiality screens, network analysis, genome-scale metabolic modeling, and machine learning techniques enables the proposal of new drug-target signatures and uncovers unanticipated modes of action for available drugs. Here, we discuss the current issues associated with drug repositioning in light of curated high-throughput multi-omic databases, genome-wide screening technologies, and their application in systems biology/medicine approaches.

Indexed as

drug repositioninggenomic screensmachine learningsystems medicinesystems pharmacology

Identifiers

PMID32967266
PMCPMC7563533

What OpenQuestion holds

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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.