Sungwon Jeon
Principles of Bioinformatics
Bioprogramming
Human DNA has about 3 billion base pairs in a single cell. It is 2.79 GB text (1 letter is 1 byte). However, when Human DNA is sequenced, it may be sequenced 30X or more DNA (In case of NGS(Next Generation Sequencing)). So Raw sequenced DNA text file is more than 84 GB. Because of large amount of Raw data, it is difficult to analyze Raw data with our hands. That's why we need computer / computer program to analyze NGS data. We are not enough smart to analyze NGS data. To deal with computer program, we should know what program is , what programming is, what computer is.
What is programming?
Today, Computers and Smart phones are widespread. Programs are very required to operate computer. In the past, Program might be for calculation. Each program has it's own purpose, algorithm. To make program ( actually, computer program), we need to know what programming is, what programming language is.
Definition of Programming
Computer programming (often shortened to programming) is a process that leads from an original formulation of a computing problem to executable computer programs. -Wikipedia -
Above is definition of programming from Wikipedia. I think we have to know why we need executable computer program. Effective and re-usable is the most important term for program. Program have to make our work effective and to be re-usable. It's why we develop computer program. To develop computer program, we need to know programming language.
Programming Language
There are many different programming language in the world.
Bioprogramming
Definition of Bioprogramming
Bioprogramming is programming that is focused on processing Biodata such as Genome, Proteome, etc and usally on dealing with text parsing. - Sungwon Jeon-
Essay : What is real?
Genomics
Genomics
Definition of Genomics
Genomics is field of Biology that study Genome ( the complete set of DNA ) by using DNA sequencing methods and Bioinformatics to analyze it. -Sungwon Jeon-
History of Genomics
1. Early Sequencing
2. Complete Genomes
3. Human Genome Project
Analysis
1. Genome Assembly
2. Genome re-sequencing
3. Gene Annotation
Future of Genomics
Comparative Genomics
Relationship with other Omics