arXiv subjects

Guanghong Zuo

Publications and source records attributed to Guanghong Zuo.

3 recordsLinked to original sources

arXiv2026

WebCVTree4: A Newly Designed Phylogenetic and Taxonomic Study Platform for Prokaryotes Using Composition Vectors and Whole Genomes

CVTree is an alignment-free methodology for inferring species phylogeny and taxonomy. This method allows for the efficient and accurate resolution of evolutionary relationships among large numbers of species based on whole-genome sequence data. Since 2004, we have been continuously providing CVTree web services. Recently, the server has undergone a significant upgrade, culminating in the release of the WebCVTree4 platform. This upgrade encompasses a comprehensive update of the inbuilt genomic database. Concurrently, the core algorithm has been optimized to support online phylogenetic reconstruction for tens of thousands of species, thereby facilitating the construction of genome-based trees of life. Moreover, we have developed a novel algorithm for comparing phylogenetic trees with established taxonomic systems. This algorithm allows for rapid tree rooting, taxonomic annotation, and topology comparison. Through an interactive web-based visualization tool, users can dynamically adjust tree layouts and export high-quality phylogenetic tree figures. This functionality provides robust support for comparative analysis between CVTree-generated phylogeny and taxonomy. As genome sequencing costs continue to decline, research into microbial evolution and the revision of taxonomic frameworks will increasingly rely on whole-genome data. WebCVTree4 will serve as an efficient web-based platform to support studies in microbial phylogenetics and taxonomy, accessible at https://cvtree.online/.

q-bio.PE↗

arXiv2025

CLTree: A Tool for Annotating, Rooting, and Evaluating Phylogenetic Trees Leveraging Genomic Lineages

Collapse Lineage Tree (CLTree) is a software tool that annotates, roots, and evaluates phylogenetic trees by using lineages. A recursive algorithm was designed to annotate the branches by the common taxonomic lineage of its descendants in a rooted tree. For an unrooted tree, it determines the root that best conforms to the taxonomic system based on the aforementioned lineage annotations. Based on the lineage annotations of notes, CLTree infers the monophyly of taxonomic units and quantifies the concordance between the phylogenetic tree and the taxonomic system base on Shannon entropy. The core algorithm of CLTree is highly efficient with linear complexity, capable of processing phylogenetic trees with 17,955 terminal nodes within one second. We believe that CLTree will serve as a powerful tool for study of evolution and taxonomy.

q-bio.PE↗

arXiv2025

EscalNet: Learn isotropic representation space for biomolecular dynamics based on effective energy

Deep learning has emerged as a powerful framework for analyzing biomolecular dynamics trajectories, enabling efficient representations that capture essential system dynamics and facilitate mechanistic studies. We propose a neural network architecture incorporating Fourier Transform analysis to process trajectory data, achieving dual objectives: eliminating high-frequency noise while preserving biologically critical slow conformational dynamics, and establishing an isotropic representation space through the last hidden layer for enhanced dynamical quantification. Comparative protein simulations demonstrate our approach generates more uniform feature distributions than linear regression methods, evidenced by smoother state similarity matrices and clearer classification boundaries. Moreover, by using saliency score, we identified key structural determinants linked to effective energy landscapes governing system dynamics. We believe that the fusion of neural network features with physical order parameters creates a robust analytical framework for advancing biomolecular trajectory analysis.

q-bio.BM↗