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pmid:40991071

Selection of tumor invasion-related genes to build a prognostic model and predict immune response and potential drugs for esophageal cancer patients based on WGCNA.

Discover oncology · 2025 doi:10.1007/s12672-025-03095-w

Paper

partial

Experiment

partial

Data

partial

Analysis

absent

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:40991071
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science-record
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2026-11-01T10:25:53Z
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paper object · 10 fields
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title
Selection of tumor invasion-related genes to build a prognostic model and predict immune response and potential drugs for esophageal cancer patients based on WGCNA.
doi
10.1007/s12672-025-03095-w
pmid
40991071
authors
null
journal
Discover oncology
year
2025
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null
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the headline numerical result the paper states for its main finding
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the headline numerical result the paper states for its main finding
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The number a replication must land on, and the sentence it came from.
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the published estimate, its unit and its interval
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The published result cannot be recomputed without the data the paper analysed.
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no owned computational capability is bound to this experiment
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A 10-gene prognostic model consisting of ARMCX2, RGS16, APLN, TRIM28, AKAP4, ZC3H12B, MAD1L1, TWIST1, TMTC2, and TADA2B was created.
minimax_alt
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tumor mutation analysis
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Complete file
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