Table 2.
Different orchid and bacterial metagenomic databases.
| Data base name | Content | Website | References |
|---|---|---|---|
| OrchidBase 5.0 | Orchidaceae Plant Genome Molecular Database | https://cosbi.ee.ncku.edu.tw/orchidbase5/ | Chen et al. (2022) |
| Main lab for bioinformatics | Analytical, computational tools and database for crop genomics, sequence analysis pipelines and genomic regions and marker controlling traits | https://www.bioinfo.wsu.edu/ | Cao (2023), Xu et al. (2023) |
| Genome Sequence Annotation Server (GenSAS) | GenSAS, online platform for whole genome, structural annotation, functional annotation of eukaryotes and prokaryotes. Genome sequences, repeat masking, gene model prediction, structural features, it integrates JBrowse and Apollo integration for visualization and editing. | https://www.gensas.org/ | Humann et al. (2019) |
| Planteome | Gene profiling, phenotypes in OMICs and developing annotation standards with other genomic databases for plant biology | https://planteome.org/ | Cooper et al. (2023) |
| GENEVESTIGATOR | Transcriptome data mining and comparison platform | https://genevestigator.com/ | Tahmasebi et al. (2021) |
| WoLFPSOT | Computational tools for protein sequencing, structuring, and finding domains for bacteria, fungi, insects, and mammals. | https://www.genscript.com/wolf-psort.html | Zheng et al. (2019) |
| EasyGo | Provide functional annotations for many genes as well as probe sets from expression microarrays. | http://bioinformatics.cau.edu.cn/easygo/ | Fahmideh et al. (2023), Zhao et al. (2023) |
| GOMAP | Annotate plant protein sequences and compile the annotations together to generate an aggregated dataset. | https://bioinformapping.com/gomap/ | Wimalanathan et al. (2021) |
| NGS and sRNA | Next generation sequencing (NGS) database including small RNA sequencing, sequencing of cleaved target RNAs | https://mpss.meyerslab.org/ | Eckardt et al. (2023a), Eckardt et al. (2023b), Li et al. (2023) |
| Microbial genome database (MBGD) | Provide gene function with their expression and species evolution that reveals their pathogenic molecular mechanism and elucidate the evolutionary relationship between bacteria and the internal structure of the genome. | http://mbgd.genome.ad.jp/ | Uchiyama et al. (2019) |
| Global Catalogue of Metagenomics (gcMeta) | Updated monthly, provides 90 tools which can preprocessing, assembly, structure, annotation, metagenome analysis, comparative analysis, and visualization of microbial meta-omics. | https://gcmeta.wdcm.org/ | Shi et al. (2019) |
| High quality Ribosomal RNA Databases (SILVA) | Provides analysis service for rRNA gene (rDNA) amplicon reads obtained from high-through put sequencing (NGS) approaches based on an automatic software pipeline to combine alignment, search and classify as well as reconstruction of trees in a single web application. | https://www.arb-silva.de/ | Glöckner (2019) |
| National Center of Biotechnology information (NCBI) | DNA sequences, Gen bank, data for computational biology and bibliographic data | https://www.ncbi.nlm.nih.gov/ | Renner et al. (2023), Wang et al. (2023) |
| MIMt | Determination and quantification of the taxonomic composition of microbial communities. | https://mimt.bu.biopolis.pt/ | Cabezas et al. (2023) |