23 papers · ranked by Valyu relevance
Max Robinson, Heeju Noh, Lance Pflieger, Noa Rappaport
Multi-omic data pose a particular challenge for Weighted Correlation Network Analysis (WCNA or WGCNA) due to (platform- or) batch-specific characteristics, such as resolution, accuracy, dynamic range, and sources of spurious variation. When unaccounted for, these differences can result in a bias toward single-batch…
M Harshvardhan, Pritam Ranjan
Pearson correlation is the default measure of association in most statistical software, yet it is only appropriate for pairs of continuous variables with a linear relationship. When variables are binary, ordinal, or categorical, specialized methods (e.g., point-biserial, polychoric, tetrachoric, and Cramér's~$V$) may…
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Predicting which molecular systems require post-Hartree-Fock treatment remains a fundamental challenge in quantum chemistry. We introduce Fbond, a universal descriptor that quantifies electron correlation strength through the product of HOMO-LUMO gap and maximum single-orbital entanglement entropy. Validation across…
Miroslava Cuperlovic-Culf, Anuradha Surendra, Irina Alecu, Abdullah Mahdi + 2 more
Introduction Data-driven determination is a powerful approach for unbiased investigation of the functional relationships in biomolecular networks. Such networks can be inferred from omics data, where correlation analysis is a commonly used method. However, the correlation values depend strongly on sample variability…
Ze Lin, Bo Li, Jinyao Shen
Pearson's correlation coefficient is commonly used as a single-number summary of association between two responses. In many applications, however, the strength of association is itself heterogeneous and may vary with demographic, biological, experimental, or environmental covariates. The regcorr package implements…
Robert M. Flight, Praneeth S. Bhatt, Hunter N. B. Moseley, Michele Costanzo
Background: Almost all correlation measures currently available are unable to directly handle missing values. Typically, missing values are either ignored completely by removing them or are imputed and used in the calculation of the correlation coefficient. In either case, the correlation value will be impacted based…
Krishna Neupane, Igor Griva, Robert Axtell, William Kennedy + 1 more
Corporate insiders trade for various reasons, often possessing Material Non-Public Information (MNPI). Accurately determining whether a trade was conducted with MNPI is a challenging task due to its complexity. The work presented here focuses on two critical aspects, first, accurately detecting Unlawful Insider Trading…
Jörn Diedrichsen, Xianglong Fu, Mahdiyar Shahbazi, Simon Bonner
Many functional magnetic resonance imaging (fMRI) studies conclude that two conditions engage “overlapping, yet partly distinct” patterns of activation. Yet, there is currently no commonly accepted method for determining the extent of this overlap. While correlations between activation patterns can serve as a measure…
Y. Chen, T.T. Gui, Z. Huang, N.E. Quach + 8 more
Title: S Chemotherapy in breast cancer (BC) can substantially affect mental wellness. Advances in metabolomics enable comprehensive profiling of metabolic changes over time during and after treatment, offering insights into biological mechanisms linking chemotherapy to mental health outcomes. To study the association…
Jiayi Hu, Abdel G. Babiker, Cavan S. Reilly, Jason V. Baker + 1 more
The recent growth of immunoglobulin-based therapies has motivated clinical trials testing primary endpoints both in the overall cohort and in subgroups of patients, such as in patients without specific antibodies at baseline. Multiple testing methods in clinical trials often ignore the natural correlation between test…
Santa Sozzi, Alejandro Luis Callara, Simone Cauzzo, Enzo Pasquale Scilingo + 2 more
Functional connectivity (FC) approaches from resting-state fMRI (rs-fMRI) are amply spread to investigate the cortical organization, yet the brainstem remains relatively underexplored despite its pivotal roles in both physiological and pathological conditions. The highly collinear network, in which the strongly…
Hyun-Soo Zhang, Inkyung Jung, Chung Mo Nam
In dependently censored survival data, the usual assumption of independent censoring or an incorrect specification of the correlation between the event and censoring times can bias marginal survival inference. Likelihood-based estimation of this dependence can be numerically unstable with large variance, and practical…
Xu, Jiayang, Chen, Xintong + 6 more
Correlation coefficient is widely used in biomedical and biological literature, yet its frequent misuse and misinterpretation undermine the credibility and reproducibility of the scientific findings. We systematically reviewed 1326 records of correlation analyses across 310 articles published in Science, Nature, and…
Jalil Nourisa, Antoine Passemiers, Yves Moreau, Daniele Raimondi
Batch correction is essential for integrating datasets and enabling population-level insights into health and disease. Embedding-based approaches are among the most widely used solutions, but here we highlight a critical, overlooked limitation: these methods can distort feature-to-feature (e.g., gene–gene)…
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The rapid growth of worldwide computing power has transformed in silico chemistry into a discipline that is integrated into the daily work of many chemists. Nowadays, researchers find it increasingly straightforward to predict a wide range of molecular properties and chemi- cal processes at reasonable computational…
Koji Kyoda, Hatsumi Okada, Shuichi Onami
Advances in live-cell imaging and image analysis have made it possible to quantitatively measure the spatiotemporal morphological dynamics of biological phenomena at scale. However, a general framework is still lacking for systematically extracting, from the resulting multivariate data, which relationships between…
Joris Mulder, Julius Pfadt, Eric-Jan Wagenmakers
Correlation coefficients play a central role in scientific research to quantify the (linear) association between certain key variables of interest. Currently, hypothesis testing of correlation coefficients, such as whether a correlation equals zero or whether two correlations are equal, is mainly done using classical p…
Gabriel Kennedy, Alejandro Ochoa
In studies of assortative mating, similarity between variables measured in parents is often quantified using correlation. The order of the parents within any given pair can be arbitrary in these applications, but common correlation estimators are not robust to reordering within pairs. These unordered variable pairs are…
Tillman Reuter, Sebastian Seidel, Dominik Seidel
Forest structural complexity is critical for ecosystem functions, yet standardized metrics for its quantification remain elusive. This study compares two LiDAR-derived three-dimensional indices, the box dimension () as a fractal-based measure, and canopy entropy (), an entropy-based metric, to evaluate their…
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End-point binding free energy (BFE) methods, such as molecular mechanics Poisson–Boltzmann surface area (MMPBSA), are widely used to estimate protein–ligand binding affinity due to their favorable balance between accuracy and computational efficiency. Their reliability, however, is often limited by approximations in…
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Quantitative Structure Activity Relationship (QSAR) remains an effective tool for early-stage chemical modelling and virtual screening in drug design. The advancements in this field are led by two core paradigms, 1) descriptor engineering, where complex fixed-length vectors of compounds are generated and conventional…
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Pharmacophores are widely used to describe protein-ligand interactions, and the Grids of Pharmacophore Interaction Fields (GRAIL) method extends this concept by representing binding pockets as interpretable sets of interaction type-specific pharmacophoric maps. In this work, we propose a hybrid framework for binding…
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Background: Batch reactor process optimization has traditionally relied on Analysis of Variance (ANOVA) for factor effect quantification. However, Structural Equation Modeling (SEM) and machine learning (ML) offer complementary mechanistic and predictive capabilities that remain underexplored in chemical engineering…