23 papers · ranked by Valyu relevance
A. Nicholls
The calculation of error bars for quantities of interest in computational chemistry comes in two forms: (1) Determining the confidence of a prediction, for instance of the property of a molecule; (2) Assessing uncertainty in measuring the difference between properties, for instance between performance metrics of two or…
Rôlin Gabriel Rasoanaivo, Morteza Yazdani, Pascale Zaraté, Amirhossein Fateh
'Amirhossein Fateh'] | AHP | : Analytical Hierarchy Process | | --- | --- | | BNN | : Bipolar Neutrosophic Numbers | | BWM | : Best Worst Method | | CoCoFISo | : Combined Compromise For Ideal Solution | | CoCoSo | : Combined Compromise Solution | | CODAS | : COmbinative Distance-based ASsessment | | COPRAS | : COmplex…
Philip J Schluter
measurement method comparison studies Authors: ['Philip J Schluter'] Background Assessing agreement in method comparison studies depends on two fundamentally important components; validity (the between method agreement) and reproducibility (the within method agreement). The Bland-Altman limits of agreement technique is…
Authors not listed
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…
Sijun Zhang, Kimberly Colvin
Single-item assessments have recently become popular in various fields, and researchers have developed methods for estimating the reliability of single-item assessments, some based on factor analysis and correction for attenuation, and others using the double monotonicity model, Guttman’s λ6, or the latent class model.…
Sini Junttila, Johannes Smolander, Laura L Elo
Single-cell RNA-sequencing (scRNA-seq) enables researchers to quantify transcriptomes of thousands of cells simultaneously and study transcriptomic changes between cells. scRNA-seq datasets increasingly include multi-subject, multi-condition experiments to investigate cell-type-specific differential states (DS) between…
Robert M. X. Wu, Zhongwu Zhang, Wanjun Yan, Jianfeng Fan + 13 more
Subjective weighting methods depend on the assessments of decision-makers. The design and determination of weights can be interpreted in terms of value judgments, that methods based on the subjective opinions of individual experts are preferred . Decision-makers compare each criterion with other criteria and determine…
Hao Wang, Carlos Igncio Hernández Castellanos, Tome Eftimov
Assessing the empirical performance of Multi-Objective Evolutionary Algorithms (MOEAs) is vital when we extensively test a set of MOEAs and aim to determine a proper ranking thereof. Multiple performance indicators, e.g., the generational distance and the hypervolume, are frequently applied when reporting the…
Jiyizhe Zhang, Daria Semochkina, Naoto Sugisawa, David Woods + 1 more
Multi-objective Bayesian optimization (MOBO) has shown to be a promising tool for reaction development. However, noise is usually unavoidable during experiments and makes it challenging to find reliable solutions. In this study, we focus on finding a set of optimal reaction conditions using multi-objective Euclidian…
Valdecy Pereira, Márcio Pereira Basílio, Carlos Tarjano
Comprehensive Library of MCDA Methods in Python Authors: ['Valdecy Pereira' 'Márcio Pereira Basílio' 'Carlos Tarjano'] Purpose: Multicriteria decision analysis (MCDA) has become increasingly essential for decision-making in complex environments. In response to this need, the pyDecision library, implemented in Python…
Zhiyuan Wang, Seyed Reza Nabavi, Gade Pandu Rangaiah
Multi-criteria decision making (MCDM) is necessary for choosing one from the available alternatives (or from the Pareto-optimal solutions obtained by multi-objective optimization), where the performance of each alternative is quantified against several criteria (or objectives). This paper presents a comprehensive…
Fengjun Qi, Zhenping Liu, Wenzheng Zhang, Zhenjie Sun + 1 more
'Muhammad Asif'] The evaluation of teacher performance in higher education is a critical component of educational reform, requiring robust and accurate assessment methodologies. Multi-objective regression offers a promising approach to optimizing the construction of performance evaluation index systems. However…
Bianca A. V. Alberton, Thomas E. Nichols, Humberto R. Gamba, Anderson M. Winkler
The multiple testing problem arises not only when there are many voxels or vertices in an image representation of the brain, but also when multiple contrasts of parameter estimates (that is, hypotheses) are tested in the same general linear model. Here we argue that a correction for this multiplicity must be performed…
Tuomas Puoliväli, Satu Palva, J. Matias Palva
Reproducibility of research findings has been recently questioned in many fields of science but the problem of multiple hypothesis testing has received little attention in this context. The elevated false positive rate in multiple testing is well known and solutions to this problem have been extensively studied for…
Hyemin Han, Andrea L. Glenn
In fMRI research, the goal of correcting for multiple comparisons is to identify areas of activity that reflect true effects, and thus would be expected to replicate in future studies. Finding an appropriate balance between trying to minimize false positives (Type I error) while not being too stringent and omitting…
Bérengère Macabeo, Arthur Quenéchdu, Samuel Aballéa, Clément François + 3 more
'Clément François' 'Laurent Boyer' 'Philippe Laramée' 'Dávid Dankó'] Introduction: Health technology assessment (HTA) agencies express a clear preference for randomized controlled trials when assessing the comparative efficacy of two or more treatments. However, an indirect treatment comparison (ITC) is often necessary…
Kobi Felton, Jan Rittig, Alexei Lapkin
In the fine chemicals industry, reaction screening and optimisation are essential to development of new products. However, this screening can be extremely time and labor intensive, especially when intuition is used. Machine learning offers a solution through iterative suggestions of new experiments based on past…
Jelle J. Goeman, Aldo Solari
We revisit simple and powerful methods for multiple pairwise comparisons that can be used in designs with three groups. We argue that the proper choice of method should be determined by the assessment which of the comparisons are considered primary and which are secondary, as determined by subject-matter…
Ludwig A. Hothorn
In bio-medical studies, the p-values of the F-tests in ANOVA are usually interpreted independently as measures of the significance of the associated factors. This ’hidden multiplicity’ effect increases the false positive rate. Therefore, Cramer et al. (2016) proposed the Bonferroni adjustment of the p-values to control…
Bruno Stegani, Emanuele Scalone, Fran Bacic Toplek, Thomas Lohr + 4 more
The computational study of the binding of a ligand to a target protein provides mechanistic insight into the molecular determinants of this process and can improve the success rate of in silico drug design. All-atom molecular dynamics (MD) simulations can be used to evaluate the binding free energy, typically by…
Pablo Quijano Velasco, Kedar Hippalgaonkar, Balamurugan Ramalingam
The discovery of optimal conditions of chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and Design of Experiments where one…
Tommy Clausner, Stefano Gentili
In the present paper we propose a non-parametric statistical test procedure for interval scaled, paired samples data that circumvents the multiple comparison problem (MCP) by relating the data to the rank order of its group averages. Using an auto-regressive procedure, a single test statistic for multiple groups is…
Martin Law, Michael J. Grayling, Adrian Mander
Existing multi-outcome designs focus almost entirely on evaluating whether all outcomes show evidence of efficacy or whether at least one outcome shows evidence of efficacy. While a small number of authors have provided multi-outcome designs that evaluate when a general number of outcomes show promise, these designs…