Key Features of BLAST:
1. Sequence Comparison: BLAST searches for local alignments between the query sequence and sequences in a database. It identifies regions of similarity, which can help infer functional and evolutionary relationships.

2. Speed and Efficiency: BLAST uses heuristic algorithms, making it faster than exhaustive search methods, suitable for large-scale database searches.

3. Versatility: There are several versions of BLAST for different types of sequence comparisons:
- blastn: Compares a nucleotide query sequence against a nucleotide sequence database.
- blastp: Compares a protein query sequence against a protein sequence database.
- blastx: Compares a nucleotide query sequence translated in all reading frames against a protein sequence database.
- tblastn: Compares a protein query sequence against a nucleotide sequence database translated in all reading frames.
- tblastx: Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.

4. Scoring and E-value: BLAST results are scored based on the quality and length of the alignments. The E-value (expect value) indicates the number of alignments one can expect to find by chance, with lower E-values representing more significant matches.

5. Output Formats: BLAST provides results in various formats, including plain text, HTML, XML, and JSON, making it adaptable for different types of analyses and integrations with other tools.

Applications of BLAST:
- Genomic Research: Identifying genes, understanding genetic diversity, and mapping genome sequences.
- Protein Function Prediction: Inferring the function of unknown proteins by comparing them to known protein sequences.
- Evolutionary Studies: Exploring evolutionary relationships between organisms by comparing their genetic material.
- Medical Research: Identifying pathogens, understanding disease mechanisms, and developing treatments by comparing sequences of interest.

Overall, BLAST is an essential tool in bioinformatics, offering a reliable and efficient way to analyze and interpret biological sequence data.

The Representational State Transfer (REST) sample clients are provided for a number of programming languages. For details of how to use these clients, download the client and run the program without any arguments.

For details see Environment setup for REST Web Services and Examples for Perl REST Web Services Clients pages.

Address of the bookmark: https://www.kegg.jp/blastkoala/

• viewing files and directories;
• editing, copying and renaming files;
• and many other actions.

https://www.farmanager.com/

Basic instruction at

https://conemu.github.io/en/FarManager.html

Plugins at 

https://plugring.farmanager.com/

Address of the bookmark: https://www.farmanager.com/

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code in Rgui:

install.packages("installr") # install 
setInternet2(TRUE)
installr::updateR() # updating R.

Running “updateR()” will detect if there is a new R version available, and if so it will download+install it (etc.). There is also a step by step tutorial (with screenshots) on how to upgrade R on Windows, using the installr package. If you only see the option to upgrade to an older version of R, then change your mirror or try again in a few hours (it usually take around 24 hours for all CRAN mirrors to get the latest version of R).

I try to keep the installr package updated and useful, so if you have any suggestions or remarks on the package – you are invited to open an issue in the github page.

Address of the bookmark: https://github.com/rachelss/SISRS

For the full list of features, improvements and fixes, see the release notes:https://ncbi.nlm.nih.gov/tools/gbench/releasenotes

New Features

• BLAST Tool: added support for local custom BLAST databases
• Graphical Sequence View: added log scaling option for graph tracks
• Generic Table View: new tutorial added

Bug Fixes and Improvements

• Project Tree View: Genomic Collections/Assemblies now show accessions, not just names
• Tree View: layout updated to better accommodate nodes of different sizes
• Table Import Dialog (MacOS): fixed issue with table visibility
• Fixed bug where different molecules IDs in GenBank could resolve to the same sequence
• Graphical Sequence View: fixed issue where sequence track was not shown for some sequences
• Graphical Sequence View: fixed protein coloration methods
• Graphical Sequence View: improved rendering of Markers to better indicate boundaries and produce higher quality PDF images
• Create Gene Model tool: fixed scenario when gene model tool failed with local sequences
• Search View: ORF Finder – fixed incorrect protein lengths
• Fixed bug with not opening project file (.gbp) on a click
• Fixed issues in GVF import
• Fixed BLAST Search tool against NCBI databases not working
• Fixed tblastn (protein BLAST) not working in standalone mode
• Fixed GTF export failure

More at file:///home/urbe/Downloads/diamond_manual.pdf

http://www.nature.com/nmeth/journal/v12/n1/full/nmeth.3176.html

Address of the bookmark: https://github.com/bbuchfink/diamond