Introductory and learning guideline for computer scientists to Bioinformatics

1. Bioinformatics for
Computer Scientists
aungthurhahein.me
@Atrhein

2. This is...
● Learning guideline for starters
● Resources for starters
● Thoughts from a computer technician who
does not have formal knowledge of
bioinformatics

3. Bioinformaticist….
Bioinformaticist: Generalists, developers/advanced
users of informatics tools that manipulate biological
data.
Bioinformatics analyst: Biologists who conduct
bioinformatics analyses full-time, but don’t develop
software

4. Formal Knowledge
● Data Mining
● Data Analysis
● Machine Learning Algorithms
● Statistics
● Database Programming

5. Informal Knowledge
● Linux
● Bash scripting
● Bioinformatics Pipelining
● Biological data format
● Open source tools
● Bio-Linux

6. Python for bioinformatics
● Easy to learn
● Extensive libraries for statistics &
visualization
● Biopython (biopython.org)
● Python is awesome and beautiful!

7. Why Python?
● You can do ‘almost’ everything with python
● Options: Perl, R, Java, C, C#
● Choose it wisely

8. Python Libraries to learn
● Pandas
● Numpy
● Scipy
● Biopython
● scikit-bio

9. Books

10. Bioinformatics
● To understand & analyze biological data
● DNA & RNA sequence analysis
● Gene & protein differential expression
analysis

11. Data Types
● DNA, RNA
● EST, cDNA
● Protein Sequence
● Pathways

12. Sequence formats
● fasta
● fastq
● EMBL
● Genbank
● etc ...

13. Open source tools
● Evaluation of tools & softwares in essential
● Important to use right tool at right place
● Many open source projects (open source bioinformatics
software)

14. Books

15. Learning Resources
● List of free online bioinformatics courses
(wiki)
● Learn Bioinformatics
● Resources for learning Bioinformatics (reddit)
● An Online Bioinformatics Curriculum (NCBI)