ArticleBMC bioinformatics2023
PhyloSophos: a high-throughput scientific name mapping algorithm augmented with explicit consideration of taxonomic science, and its application on natural product (NP) occurrence database processing.
Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- An Integrated Systems Pharmacology Approach Combining Bioinformatics, Untargeted Metabolomics and Molecular Dynamics to Unveil the Anti-Aging Mechanisms ofBiomolecules · 2025Article
- A Multi-Layered Analytical Pipeline Combining Informatics, UHPLC-MS/MS, Network Pharmacology, and Bioassays for Elucidating the Skin Anti-Aging Activity ofInternational journal of molecular sciences · 2025Article
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Authors and funding
3 authors.
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Abstract
backgroundThe standardization of biological data using unique identifiers is vital for seamless data integration, comprehensive interpretation, and reproducibility of research findings, contributing to advancements in bioinformatics and systems biology. Despite being widely accepted as a universal identifier, scientific names for biological species have inherent limitations, including lack of stability, uniqueness, and convertibility, hindering their effective use as identifiers in databases, particularly in natural product (NP) occurrence databases, posing a substantial obstacle to utilizing this valuable data for large-scale research applications.
resultTo address these challenges and facilitate high-throughput analysis of biological data involving scientific names, we developed PhyloSophos, a Python package that considers the properties of scientific names and taxonomic systems to accurately map name inputs to entries within a chosen reference database. We illustrate the importance of assessing multiple taxonomic databases and considering taxonomic syntax-based pre-processing using NP occurrence databases as an example, with the ultimate goal of integrating heterogeneous information into a single, unified dataset.
conclusionsWe anticipate PhyloSophos to significantly aid in the systematic processing of poorly digitized and curated biological data, such as biodiversity information and ethnopharmacological resources, enabling full-scale bioinformatics analysis using these valuable data resources.
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