1. NCBI (National Center for Biotechnology Information):

   • NCBI provides various databases related to genetic information, including 16S rRNA sequences.
   • You can access the 16S ribosomal RNA sequences from NCBI's Nucleotide database (https://www.ncbi.nlm.nih.gov/nucleotide/).
   • Perform a search using keywords like "16S rRNA" or specific bacterial names to find relevant sequences.
   • You can download sequences individually or in batches using the provided tools.

2. GreenGenes:

   • GreenGenes is a widely used 16S rRNA gene sequence database.
   • You can access it at http://greengenes.secondgenome.com/.
   • GreenGenes provides precompiled databases for various purposes, including classification, alignment, and phylogenetic analysis.

3. SILVA:

   • SILVA (https://www.arb-silva.de/) is another comprehensive database for ribosomal RNA (rRNA) sequences.
   • It covers not only 16S rRNA but also other ribosomal RNA sequences.
   • SILVA provides precompiled databases for various purposes, including taxonomic classification and alignment.

4. Ribosomal Database Project (RDP):

   • RDP (http://rdp.cme.msu.edu/) is a curated database that offers 16S rRNA sequences.
   • It provides tools for sequence analysis and classification.
   • You can download sequences and taxonomy information from their website.

5. QIIME (Quantitative Insights Into Microbial Ecology):

   • QIIME (https://qiime2.org/) is a widely used bioinformatics platform for microbiome analysis.
   • It provides tools for analyzing microbial communities, including processing 16S rRNA sequences.
   • QIIME often includes its own preprocessed 16S rRNA databases that can be used for analysis within the platform.

Before downloading any database, make sure to read the terms of use and citation requirements, as some databases may have specific usage policies. Additionally, consider the compatibility of the database with your analysis pipeline and software tools.

NCBI 16s RNA database location ftp://ftp.ncbi.nih.gov/blast/db/16SMicrobial.tar.gz

Aim of this web site is to facilitate the scientific community to fight against severe pandemic disease COVID-19 caused by SARS-CoV-2. Here, We have collected and organized information related to novel strain of coronavirus, i.e. SARS-CoV-2.and its resulting disease COVID-19 from the literature and other resources from the Internet. We are providing links to appropriate literature. Moreover, we are Bioinformatics Group, based on our knowledge and expertise, we are also proposing potential diagnostics primers, peptide and RNA based vaccine candidates and potential drug molecules. These are predicted candidates, need to be validated by experimental Researchers, who have appropriate infrastructure. It is an integrated multi-omics repository dedicated to current genomic, proteomic, diagnostic and therapeutic knowledge about coronaviruses particularly the recent strain, i.e. SARS-CoV-2 or 2019-nCoV. This web resource will be helpful for the researchers engaged in the development of therapies and drugs for the COVID-19. The information is collected from various available resources.
Cite: Patiyal, Sumeet, et al. “A Web-based Platform on COVID-19 to Maintain Predicted Diagnostic, Drug
and Vaccine Candidates.” Monoclon Antib Immunodiagn Immunother. doi.org/10.1089/mab.2020.0035

Address of the bookmark: https://webs.iiitd.edu.in/raghava/coronavir/

Address of the bookmark: http://scikit-bio.org/

• dbCAN provides the capability of automated and comprehensive CAZyme annotation of a given genome submitted by the user;
• dbCAN provides an explicitly defined signature domain for each and every CAZyme family along with its location in all the relevant full-length CAZyme proteins in all sequenced genomes;
• dbCAN provides the most complete set of metagenomic CAZyme genes published so far and represents the first step towards discovering novel CAZyme catalysts in metagenomes;
• dbCAN provides a subfamily classification of the existing CAZyme families based on sequence similarities;
• dbCAN make all pre-computed data freely available to the public, including sequence alignments, hidden markov models (HMMs) and phylogenies of the signature domain regions in each and every CAZyme family and subfamily.

dbCAN is updated regularly when CAZy database created new families based on latest literature.

Address of the bookmark: http://csbl.bmb.uga.edu/dbCAN/index.php

To get started using Bokeh to make your visualizations, see the User Guide.

To see examples of how you might use Bokeh with your own data, check out the Gallery.

A complete API reference of Bokeh is at Reference Guide.

If you are interested in contributing to Bokeh, or extending the library, see the Developer Guide.

Address of the bookmark: https://bokeh.pydata.org/en/latest/

The programs and the package are free software for academic users. Permission to use, copy, and modify any part of this software for educational, research and non-profit purposes is hereby granted. In this package or Docker image, number of other supported software has been integrated which may be under other licenses, along with any direct or indirect dependencies of the primary software being contained. As for any pre-built image usage, it is the image user's responsibility to ensure that any use of this image complies with any relevant licenses for all software contained within.

All software packages are distributed in the hope that they will be useful but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. If you have any query, please contact at raghava@iiitd.ac.in.

Address of the bookmark: https://hub.docker.com/r/raghavagps/gpsrdocker/

No previous programming knowledge is assumed. By following this tutorial you will learn the fundamental concepts of programming by using scripting languages: variables, types, arrays, cycles, conditional statements, functions, objects, regular expressions, files reading and manipulation et-cetera.

Address of the bookmark: http://www.cellbiol.com/bioinformatics_web_development/introduction/

CSAR-web can serve as a convenient and useful scaffolding tool allowing the users to efficiently and accurately scaffold their draft genomes according to a complete or incomplete reference genome. 

Address of the bookmark: http://genome.cs.nthu.edu.tw/CSAR-web

https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw377

Address of the bookmark: http://amp.pharm.mssm.edu/Enrichr/