G4SNVHunter workflow for identifying variants that affect G4 formation. حسب Rongxin Zhang (1618159)

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List of aSNPs predicted to disrupt G4 formation propensity. حسب Rongxin Zhang (1618159)

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Overview of archaic SNPs (aSNPs) potentially affecting G4 formation, identified by G4SNVHunter. حسب Rongxin Zhang (1618159)

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Schematic diagram of the G4Hunter scanning principle. حسب Rongxin Zhang (1618159)

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An example of an aSNP affecting G4 formation. حسب Rongxin Zhang (1618159)

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VEP annotation of the aSNPs listed in S1 Table. حسب Rongxin Zhang (1618159)

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2D density plot of maximum G4Hunter scores for G4s whose formation propensity is computationally impaired by aSNPs. حسب Rongxin Zhang (1618159)

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A hypothetical example illustrating the differences between the two assessment modes in G4SNVHunter. حسب Rongxin Zhang (1618159)

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Data Sheet 1_Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model.docx حسب Pan Zhang (206408)

"…Considering the increased detection range of EDARM and the requirements for computational efficiency, this paper presents a 2.5-dimensional (2.5D) finite element method (FEM). By leveraging the symmetry of simulated signals in the spectral domain, the algorithm reduces computation time by 50%, significantly enhancing computational efficiency while preserving accuracy. …"

Computation time as a function of the sample size on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). حسب Tomokaze Shiratori (9635271)

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Computation time as a function of the sample size on the random graph dataset. حسب Tomokaze Shiratori (9635271)

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F1 score of edges selected through cross-validation on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). حسب Tomokaze Shiratori (9635271)

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Examples of ground-truth graph structures with (<i>p</i>, <i>n</i>_≠0) = (10, 10). حسب Tomokaze Shiratori (9635271)

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Number of edges selected through cross-validation on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Number of edges selected through cross-validation on the random graph dataset. حسب Tomokaze Shiratori (9635271)

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Graphs of the regularization terms. حسب Tomokaze Shiratori (9635271)

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F1 score of a given number of selected edges on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Computation time as a function of the number of variables on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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