We describe a theoretical framework for a model-based approach to two-dimensional correlation spectroscopy that is generally applicable to any arbitrary model function. The method is based on the correlation between spectral data and a set of model waveforms with a varying correlation index, the global phase angle Theta. When experimental spectral intensity variations are expressed as sinusoidal, exponential, Lorentzian, or quadratic functions, the proposed approach allows us to estimate the quantitative values of the target parameters in those expressions. In addition, this method enables us to assess the sequential order in a series of bands undergoing non-identical intensity changes in a dynamic data set. We present both simulated and experimentally obtained data that illustrate that the deviations from linearity of the absorption band intensity waveforms are clearly detected and can be quantitatively estimated using quadratic functions.
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http://dx.doi.org/10.1366/000370206778999058 | DOI Listing |
Mol Ecol Resour
January 2025
Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
In populations of small effective size (N), such as those in conservation programmes, companion animals or livestock species, inbreeding control is essential. Homozygosity-by-descent (HBD) segments provide relevant information in that context, as they allow accurate estimation of the inbreeding coefficient, provide locus-specific information and their length is informative about the "age" of inbreeding. Our objective was to evaluate tools for predicting HBD in future offspring based on parental genotypes, a problem equivalent to identifying segments identical-by-descent (IBD) among the four parental chromosomes.
View Article and Find Full Text PDFJ Pharmacokinet Pharmacodyn
January 2025
Clinical Pharmacology Development Area, MSD K.K., Tokyo, Japan.
Model-informed drug development (MIDD) is an approach to improve the efficiency of drug development. To promote awareness and application of MIDD in Japan, the Data Science Expert Committee of the Drug Evaluation Committee in the Japan Pharmaceutical Manufacturers Association established a task force, which surveyed MIDD applications for approved products in Japan. This study aimed to reveal the trends and challenges in the use of MIDD by analyzing the survey results.
View Article and Find Full Text PDFSci Rep
January 2025
Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea.
Model optimization is a problem of great concern and challenge for developing an image classification model. In image classification, selecting the appropriate hyperparameters can substantially boost the model's ability to learn intricate patterns and features from complex image data. Hyperparameter optimization helps to prevent overfitting by finding the right balance between complexity and generalization of a model.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Predicting protein-protein interactions (PPIs) is crucial for advancing drug discovery. Despite the proposal of numerous advanced computational methods, these approaches often suffer from poor usability for biologists and lack generalization. In this study, we designed a deep learning model based on a coattention mechanism that was capable of both PPI and site prediction and used this model as the foundation for PPI-CoAttNet, a user-friendly, multifunctional web server for PPI prediction.
View Article and Find Full Text PDFBiomech Model Mechanobiol
January 2025
CNRS, LaMCoS, UMR5259, INSA Lyon, 69621, Villeurbanne, France.
Predicting the evolution of ascending aortic aneurysm (AscAA) growth is a challenge, complicated by the intricate interplay of aortic geometry, tissue behavior, and blood flow dynamics. We investigate a flow-structural growth and remodeling (FSG) model based on the homogenized constrained mixture theory to simulate realistic AscAA growth evolution. Our approach involves initiating a finite element model with an initial elastin insult, driven by the distribution of Time-Averaged Wall Shear Stress (TAWSS) derived from computational fluid dynamics simulations.
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