In many cases, the phrases “bioinformatics” and “computational biology” are used interchangeably, particularly in job descriptions or position titles.
Though the two fields are interrelated, bioinformatics and computational biology differ in the kinds of needs they address. (2/)
Bioinformatics is a multidisciplinary field that combines biological knowledge with computer programming and big data.
It is the process by which biological problems posed by the study of biodata are interpreted and analyzed. (3/)
Examples of bioinformatics studies include: analysis of genomics or transcriptomics data, protein function prediction from sequence and structural information (4/
Computational biology, by contrast, is concerned with solutions to issues raised by studies in bioinformatics. It uses computer science, statistic, and mathematics to help solve problems in biology. (5/)
It can also include the development of algorithms, theoretical models, computational simulation, and mathematical models. (6/)
For example, it includes the examination of how proteins interact with each other through the simulation of protein folding, motion, and interaction (7/)
Hope the difference is clear enough... especially for scientists applying for jobs related to Bioinformatics or Computational Biology
Please share with us any further information you have about these fields 😄 (8/)
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(2/n) Introduction to programming for Bioinformatics with Python
Python is fundamental in Bioinformatics analyses. This course will let you learn Python programming for biological data manipulation and scientific research
Top 10 references for learning Bioinformatics 💻🧬
A thread...🧵
(DM me if you are interested in the PDFs)
(1). Developing Bioinformatics Computer Skills
- One of the first comprehensive references for Bioinformatics concepts
- Covers the Unix file system, building tools & databases, introduction to Perl for bioinformatics, data mining, and data visualization. oreilly.com/library/view/d…
(2). Bioinformatics Data Skills
- Covers Unix pipelines, Bash scripts and Makefiles, exploratory data analysis techniques in the R language, common genomics data file formats like FASTA, FASTQ, SAM, and BAM, the Git version control system, oreilly.com/library/view/b…