Dr. Xinwei Song | Soil Science | Research Excellence Award
Dr. Xinwei Song | Soil Science | post doctor at Zhejiang University | China
Dr. Xinwei Song is a researcher whose work focuses extensively on microbial ecology, arsenic biogeochemistry, and metagenomic tool development, contributing meaningfully to understanding how microbial processes mediate environmental transformations; although ORCID does not provide personal information, educational background, or formal professional positions, Dr. Song’s scholarly record demonstrates strong engagement with interdisciplinary environmental microbiology, particularly mechanisms of microbial arsenic metabolism and the development of computational tools to support these investigations. Dr. Xinwei Song’s research experience can be inferred from authorship in high-impact journals such as Nature Communications and NAR Genomics and Bioinformatics, where publications address complex microbial interactions including rhizosphere-triggered viral lysogeny that drives microbial metabolic reprogramming to enhance arsenic oxidation, as well as the creation of AsgeneDB, a curated orthology-based database for annotating arsenic metabolism genes across metagenomes. These contributions indicate research interests centered on microbial functional genomics, environmental contamination, microbial-virus interactions, and algorithmic or database-driven approaches to metagenome interpretation. While explicit information about research skills is not provided, Dr. Song’s published work clearly demonstrates proficiency in metagenomics, microbial community analysis, environmental biogeochemistry, database curation, and computational annotation pipelines, as well as collaborative, multi-institutional scientific work. Awards and honors are not listed on ORCID, but the presence of publications in prestigious journals suggests strong recognition within the scientific community. In summary, Dr. Xinwei Song emerges as a productive and technically skilled environmental microbiologist whose contributions advance both fundamental understanding and data-driven tools for studying arsenic-related microbial processes, and although formal education and positions are not documented in the provided records, Dr. Song’s publication record reflects a high level of expertise, methodological sophistication, and commitment to advancing microbial biogeochemical research.
Academic Profile: ORCID | Scopus
Featured Publications:
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Song, X., Wang, Y., Wang, Y., Zhao, K., Tong, D., Gao, R., Lv, X., Kong, D., Ruan, Y., Wang, M., et al. (2025). Rhizosphere-triggered viral lysogeny mediates microbial metabolic reprogramming to enhance arsenic oxidation. Nature Communications. https://doi.org/10.1038/s41467-025-58695-5.
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Song, X., Li, Y., Stirling, E., Zhao, K., Wang, B., Zhu, Y., Luo, Y., Xu, J., & Ma, B. (2022). AsgeneDB: A curated orthology arsenic metabolism gene database and computational tool for metagenome annotation. NAR Genomics and Bioinformatics. https://doi.org/10.1093/nargab/lqac080.
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Song, X., Li, Y., Stirling, E., Zhao, K., Wang, B., Zhu, Y., Luo, Y., Xu, J., & Ma, B. (2022). AsgeneDB: A curated orthology arsenic metabolism gene database and computational tool for metagenome annotation. Preprint. https://doi.org/10.22541/au.164975586.65142559/v1.