Search alternatives:
selective algorithm » selection algorithm (Expand Search), detection algorithm (Expand Search), detection algorithms (Expand Search)
mutant selective » potent selective (Expand Search), task selective (Expand Search)
selective algorithm » selection algorithm (Expand Search), detection algorithm (Expand Search), detection algorithms (Expand Search)
mutant selective » potent selective (Expand Search), task selective (Expand Search)
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Overview of CINner’s mathematical model and simulation algorithm.
Published 2025“…<b>(d)</b> Selection model for driver genes. Each driver gene has a selection rate for its wild-type (WT) and mutant (MUT) alleles, which are constant across cells. …”
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Table 3_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.xlsx
Published 2025“…Characterizing the malignant features of EGFR-mutant epithelial cells may facilitate improved stratification and personalized therapeutic strategies.…”
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Table 2_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.xlsx
Published 2025“…Characterizing the malignant features of EGFR-mutant epithelial cells may facilitate improved stratification and personalized therapeutic strategies.…”
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Image 3_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.tif
Published 2025“…Characterizing the malignant features of EGFR-mutant epithelial cells may facilitate improved stratification and personalized therapeutic strategies.…”
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Image 2_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.tif
Published 2025“…Characterizing the malignant features of EGFR-mutant epithelial cells may facilitate improved stratification and personalized therapeutic strategies.…”
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Image 1_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.tif
Published 2025“…Characterizing the malignant features of EGFR-mutant epithelial cells may facilitate improved stratification and personalized therapeutic strategies.…”
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Table 1_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.xlsx
Published 2025“…Characterizing the malignant features of EGFR-mutant epithelial cells may facilitate improved stratification and personalized therapeutic strategies.…”
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Equivalent Mutants Analysed via Deductive Verification
Published 2025“…</p><p dir="ltr">For MathUtils, the benchmark covers only the uninteresting *gcd*, instead we supplied a mutant for *distance*.</p><p dir="ltr">Most of the samples selected above lacked loops. …”
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Enhancing Activity and Stability of Transaminase through Integrated Machine Learning, Rational Design, and Directed Evolution Approaches
Published 2025“…By employing machine learning algorithms with appropriate feature selection, we identified key mutations that enhanced catalytic properties while maintaining the structural stability. …”
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Data Sheet 1_TET2 gene mutation status associated with poor prognosis of transition zone prostate cancer: a retrospective cohort study based on whole exome sequencing and machine l...
Published 2025“…Novel candidate variants relevant to driver gene were selected using rare-variant burden analysis. Kaplan-Meier curves with log-rank testing and Cox regression models were applied to evaluate the prognostic significance of selected mutant driver gene and clinicopathological characteristics in a cohort of 132 patients with TZ PCa. …”