PURPOSE: The aim of this study was to compare the latest large language models (LLMs) ChatGPT-4o, Google Gemini 1.5 Pro and Microsoft Copilot Pro developed by three different companies, with each other and with a group of ophthalmologists, to reveal ...
In response to the growing complexity of network threats, researchers are increasingly turning to machine learning and deep learning techniques to develop advanced models for malware detection. Many existing methods that utilize Application Programmi...
Spatial transcriptomics technology has revolutionized our understanding of cellular systems by capturing RNA transcript levels in their original spatial context. Single-cell spatial transcriptomics (scST) offers single-cell resolution expression leve...
MOTIVATION: Identifying drug-target interactions (DTIs) is a crucial step in drug repurposing and drug discovery. The significant increase in demand and the expensive nature for experimentally identifying DTIs necessitate computational tools for auto...
Spatially resolved transcriptomics (SRT) simultaneously measure spatial location, histology images, and transcriptional profiles of cells or regions in undissociated tissues. Integrative analysis of multi-modal SRT data holds immense potential for un...
BACKGROUND: RNA-binding proteins (RBPs) play crucial roles in many biological processes, and computationally identifying RNA-RBP interactions provides insights into the biological mechanism of diseases associated with RBPs.
Even with the significant advances of AlphaFold-Multimer (AF-Multimer) and AlphaFold3 (AF3) in protein complex structure prediction, their accuracy is still not comparable with monomer structure prediction. Efficient and effective quality assessment ...
A terminator is a DNA region that ends the transcription process. Currently, multiple computational tools are available for predicting bacterial terminators. However, these methods are specialized for certain bacteria or terminator type (i.e. intrins...
Non-targeted metabolomics holds great promise for advancing precision medicine and biomarker discovery. However, identifying compounds from tandem mass spectra remains a challenging task due to the incomplete nature of spectral reference libraries. A...
Phylogenetic inference aims at reconstructing the tree describing the evolution of a set of sequences descending from a common ancestor. The high computational cost of state-of-the-art maximum likelihood and Bayesian inference methods limits their us...