Evidence map›Paper›PMID 31638744›Full record

ArticleMolecular informatics2020

An in silico Approach for Integrating Phenotypic and Target-based Approaches in Drug Discovery.

Hiroaki Iwata, Ryosuke Kojima, Yasushi Okuno

Abstract read
In one paragraph

Article in Molecular informatics, 2020. 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
–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

1 citing paper in PubMed.

  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.

Hiroaki IwataGraduate School of Medicine, Kyoto University, 53 Shogoin-kawaharacho, Sakyo-ku Kyoto, 606-8507, Japan.
Ryosuke KojimaGraduate School of Medicine, Kyoto University, 53 Shogoin-kawaharacho, Sakyo-ku Kyoto, 606-8507, Japan.
Yasushi OkunoGraduate School of Medicine, Kyoto University, 53 Shogoin-kawaharacho, Sakyo-ku Kyoto, 606-8507, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phenotypic and target-based approaches are useful methods in drug discovery. The phenotypic approach is an experimental approach for evaluating the phenotypic response. The target-based approach is a rational approach for screening drug candidates targeting a biomolecule that causes diseases. These approaches are widely used for drug discovery. However, two serious problems of target deconvolution and polypharmacology are encountered in these conventional experimental approaches. To overcome these two problems, we developed a new in silico method using a probabilistic framework. This method integrates both the phenotypic and target-based approaches to estimate a relevant network from compound to phenotype. Our method can computationally execute target deconvolution considering polypharmacology and can provide keys for understanding the pathway and mechanism from compound to phenotype, thereby promoting drug discovery.

Indexed as

Computer SimulationDrug DiscoveryPhenotypedrug discoverymachine learningphenotypic approachpolypharmacologytarget-based approachtarget deconvolution

Identifiers

PMID31638744
PMCPMC7050533

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.