Evidence map›Paper›PMID 38213890›Full record

ArticleComputational and structural biotechnology journal2023

Predicting the effects of cultivation condition on gene regulation in

Mun Su Kwon, Joshua Julio Adidjaja, Hyun Uk Kim

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 77% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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.

Mun Su KwonSystems Biology and Medicine Laboratory, Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
Joshua Julio AdidjajaSystems Biology and Medicine Laboratory, Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
Hyun Uk KimSystems Biology and Medicine Laboratory, Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
Korea Advanced Institute of Science and Technology · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell's physiology is affected by cultivation conditions at varying degrees, including carbon sources and inorganic nutrients in growth medium, and the presence or absence of aeration. When examining the effects of cultivation conditions on the cell, the cell's transcriptional response is often examined first among other phenotypes (e.g., proteome and metabolome). In this regard, we developed DeepMGR, a deep learning model that predicts the effects of culture

Indexed as

Cultivation conditionDeep learningEscherichia coliGene regulationTranscriptional response

Identifiers

PMID38213890
PMCPMC10781998
OpenAlexW4365458064

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.