Virusdb2.0: An Online Crowdsourcing Virus Database for Classification Based on Natural Vector

Abstract:
We have developed a virus database named VirusDB2.0 (http://www.virusdb.online) and an online query system, designed to serve individuals interested in virus prediction. This database stores k-mer natural vectors of virus genomes and the classification information of single-segment/multi-segment virus reference sequences downloaded from the National Center for Biotechnology Information (NCBI). The online query system aims to calculate the k-mer natural vectors and their distances based on submitted genomes, providing an online interface for accessing and using the database for virus prediction. It also includes a backend process that automatically updates the database in real-time to stay synchronized with GenBank. Additionally, we have introduced a crowdsourcing interface that allows users to choose whether to share their data with VirusDB2.0. Genomic data submitted in FASTA format or as sequences will be processed, and the prediction results, along with a RequestID, will be sent via email for easy retrieval. Considering the one-to-one correspondence between sequences and k-mer natural vectors, along with time efficiency and high accuracy, k-mer natural vectors are a significant improvement over natural vectors and alignment methods. This makes VirusDB2.0 a useful database for further research.