agriGO v2.0 is an updated version of the gene ontology (GO) analysis tool specifically designed for the agricultural community. It supports a larger number of species (394) and data types (865), and includes new visualization tools such as SEACOMPARE, direct acyclic graph (DAG), and scatter plots. The platform has been improved for computational efficiency, user-friendliness, and visualization. It provides batch analysis and P-value distribution (PVD) features, which help in analyzing multiple datasets simultaneously. The platform also allows users to compare significant GO terms based on false discovery rates (FDRs) from batch analysis results. The updated agriGO v2.0 is publicly accessible at http://systemsbiology.cau.edu.cn/agriGOv2/. The GO database is updated monthly, and the definitions of terms and their parent-child relationships may change due to the integration of information from different sources. This necessitates the continuous updating of GO annotations and corresponding terms. agriGO has been referenced over 982 times since its launch, with more than 80,000 analysis requests. The platform has been updated to support more species and data types, and to provide more accurate and comprehensive analysis results. The platform includes various analysis tools such as search, singular enrichment analysis (SEA), parametric analysis of gene set enrichment (PAGE), SEACOMPARE, batch SEA, DAG drawer, and scatter plots. The SEA and batch SEA differ in that the latter can process multiple input datasets simultaneously. SEACOMPARE is used to compare significant GO terms based on FDRs from batch SEA results. The PVD displays the distribution of P-values of significant GO terms and helps in identifying real significant terms by comparing them with randomly selected gene lists. The platform also includes new visualization tools such as the DAG and scatter plots, which help in understanding the relationships between GO terms. The DAG is based on the structure of GO and can indicate submitted terms and their inter-relationships. The scatter plots can display significant GO terms after a multi-step filtering process. The semantic similarity measurement method is used to filter similar GO terms and identify core GO terms. The platform has been updated to support more species and data types, and to provide more accurate and comprehensive analysis results. It includes a new species classification system, which categorizes species into plant, animal, and fungi groups. The platform also includes a new analysis framework that allows users to perform various types of analysis, including group species analysis and single species analysis. The platform has been updated to provide more efficient and systematic analyses, and to support the agricultural community in their research.agriGO v2.0 is an updated version of the gene ontology (GO) analysis tool specifically designed for the agricultural community. It supports a larger number of species (394) and data types (865), and includes new visualization tools such as SEACOMPARE, direct acyclic graph (DAG), and scatter plots. The platform has been improved for computational efficiency, user-friendliness, and visualization. It provides batch analysis and P-value distribution (PVD) features, which help in analyzing multiple datasets simultaneously. The platform also allows users to compare significant GO terms based on false discovery rates (FDRs) from batch analysis results. The updated agriGO v2.0 is publicly accessible at http://systemsbiology.cau.edu.cn/agriGOv2/. The GO database is updated monthly, and the definitions of terms and their parent-child relationships may change due to the integration of information from different sources. This necessitates the continuous updating of GO annotations and corresponding terms. agriGO has been referenced over 982 times since its launch, with more than 80,000 analysis requests. The platform has been updated to support more species and data types, and to provide more accurate and comprehensive analysis results. The platform includes various analysis tools such as search, singular enrichment analysis (SEA), parametric analysis of gene set enrichment (PAGE), SEACOMPARE, batch SEA, DAG drawer, and scatter plots. The SEA and batch SEA differ in that the latter can process multiple input datasets simultaneously. SEACOMPARE is used to compare significant GO terms based on FDRs from batch SEA results. The PVD displays the distribution of P-values of significant GO terms and helps in identifying real significant terms by comparing them with randomly selected gene lists. The platform also includes new visualization tools such as the DAG and scatter plots, which help in understanding the relationships between GO terms. The DAG is based on the structure of GO and can indicate submitted terms and their inter-relationships. The scatter plots can display significant GO terms after a multi-step filtering process. The semantic similarity measurement method is used to filter similar GO terms and identify core GO terms. The platform has been updated to support more species and data types, and to provide more accurate and comprehensive analysis results. It includes a new species classification system, which categorizes species into plant, animal, and fungi groups. The platform also includes a new analysis framework that allows users to perform various types of analysis, including group species analysis and single species analysis. The platform has been updated to provide more efficient and systematic analyses, and to support the agricultural community in their research.