gaspersic/freeCodeCamp
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Add "Find out more" links and section on BLAST (#24949)

Browse Source 
Useful links for finding out more on Computational Genomics, and added a section detailing BLAST, a very useful search algorithm and database for bioinformatics.
This commit is contained in:
coolmint204
2019-05-12 11:32:56 -05:00
committed by Randell Dawson
parent d1afa9c2a4
commit 18acffecad
1 changed files with 13 additions and 6 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
guide/english/computational-genomics/index.md
View File

@@ -11,14 +11,21 @@ RNA-Seq is a very common phrase used in Computational Genomics, as it is becomin
Typically, publicly available data is used for Computational Genomics, and often the research made in this field is used by both doctors and corporations to make medical decisions regarding patients and technology.
## Books to read
## BLAST
*Introduction to Computational Genomics* by Matthew W. Hahn
- https://www.amazon.com/Introduction-Computational-Genomics-Studies-Approach/dp/0521671914
- ISBN-13: 978-0521671910
A great starter book for beginners
A very useful tool for bioinformatics, BLAST, the Basic Local Alignment Search Tool, is an important part of the U.S. National Library of Medicine's online database. BLAST has five main search functions:
* Nucleotide BLAST: insert nucleotide sequence and it will search for all the data surrounding it.
* Protein BLAST: same as Nucleotide BLAST, but with Proteins.
* BlastX: insert a translated nucleotide sequence, and it will attempt to search for information on its respective protein.
* tblastn: the reverse process of BlastX.
* BLAST Genomes: look up the genomes of any species available.
You can access it online via the [BLAST website](https://blast.ncbi.nlm.nih.gov/Blast.cgi)
## Additional Resources
- [IBM Research on Computational Genomics](https://researcher.watson.ibm.com/researcher/view_group.php?id=1179)
- [IBM's GitHub Repository](https://github.com/ComputationalGenomics/)
- This blog by astrobiologist [Mike Lee](https://astrobiomike.github.io/) is a good place to start.
- Bioinformatics tools are commonly designed in R and Python. Two such projects are the [Bioconductor](https://www.bioconductor.org/) project (written in R) and the [Biopython](https://biopython.org/) project.