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Record W3071581989 · doi:10.5376/rgg.2020.11.0001

Cloning, Expression and Purification of <i>MGG_14095</i> Gene of <i>Magnaporthe grisea</i>

2020· article· en· W3071581989 on OpenAlexvenueno aff
Shuang Wang, Yongsheng Chen, Fenglan Huang, Guorui Li

Bibliographic record

VenueRice Genomics and Genetics · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolism and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMagnaporthe griseaMagnaportheBiologyGeneIsoelectric pointGeneticsEnzymeOryza sativaBiochemistry

Abstract

fetched live from OpenAlex

Magnaporthe grisea is the most harmful pathogen in the world for rice and the main model organism for elucidating the molecular basis of plant fungal disease interaction. Carrying out relevant research of the growth and development of Magnaporthe grisea has a great significance for the control of Magnaporthe grisea . MGG _ 14095 gene is the pathogenic gene of Magnaporthe grisea . The bioinformatics prediction of MGG_14095 protein showed that the isoelectric point (PI) of MGG_14095 protein was 5.72, and the instability index was 50.99, belonging to the acid unstable protein and the α/β hydrolase superfamily, containing the keratinase conservative domain; having obvious transmembrane structure and signal peptide cutting site, belonging to the secretory protein. In this study, the MGG _ 14095 ( 38 ~ 281 ) gene of Magnaporthe grisea was cloned, and the prokaryotic expression system pETM20- MGG _ 14095 ( 38 ~ 28 ) was constructed. We use the stepwise chromatography to purify MGG_14095 protein, and the high-purity soluble target protein was obtained successfully. The results provided for the analysis of MGG_14095(38~281) protein structure, the exploration of pathogenetic mechanism of Magnaporthe grisea and the control of Magnaporthe grisea Certain theoretical and experimental basis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.221
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueRice Genomics and GeneticsSame topicMicrobial Metabolism and ApplicationsFrench-language works237,207