Results 141 to 150 of about 38,196 (251)
An Effective Computational Method for Predicting Self-Interacting Proteins Based on VGGNet Convolutional Neural Network and Gray-Level Co-occurrence Matrix. [PDF]
Chu DH, An JY, Nie XM.
europepmc +1 more source
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source
Machine learning prediction model for gray-level co-occurrence matrix features of synchronous liver metastasis in colorectal cancer. [PDF]
Yang KF, Li SJ, Xu J, Zheng YB.
europepmc +1 more source
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah +3 more
wiley +1 more source
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan +3 more
wiley +1 more source
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Quantitative phase maps of single cells recorded in flow cytometry modality feed a hierarchical architecture of machine learning models for the label‐free identification of subtypes of ovarian cancer. The employment of a priori clinical information improves the classification performance, thus emulating the clinical application of liquid biopsy during ...
Daniele Pirone +11 more
wiley +1 more source
Abstract Premise Desert plant assemblages in southern California provide an opportunity to link patterns of community structure with climate‐driven vulnerability in a rapidly changing environment. California sustains an exceptionally diverse flora of approximately 4300 plant species, with 31% identified as endemic.
Hector Zumbado‐Ulate +4 more
wiley +1 more source
Analysis of gear surface morphology based on gray level co-occurrence matrix and fractal dimension. [PDF]
Wei B +5 more
europepmc +1 more source
Phylogenomic insights into the genus Tulipa (Liliaceae): Taxonomy, evolution, and biogeography
Abstract Premise Tulips are one of the best‐known geophytes, but their taxonomy remains convoluted and their evolutionary history poorly understood. Here, we used plastid genomes to identify some issues with current classification, understand the diversification history of the genus, and identify potential species linked to historical cultivation ...
Brett Wilson +17 more
wiley +1 more source

