Preface
On this course
Implementation of course
Tasks and arrangements
Academic assessment
Features of the course
About the instructor
What can you learn?
Main chapters
1
Introduction
1.1
On data in our life
1.2
What is Bioinformatics
1.3
History of Bioinformatics
1.4
Applications of Bioinformatics
1.5
Bioinformatics in big data era
1.6
Summary and pespective
2
Databases in Biomedicime
2.1
Guiding
2.2
NCBI data resources
2.3
EMBL data resources
2.4
UCSC genome browser
2.5
Other data resources
2.6
Applications of databases
3
Sequence alignment
3.1
Guiding
3.2
The basics of sequence alignment
3.3
Pairwise alignment
3.4
Scoring matrix
3.5
Tools for alignment
3.6
Some cases
3.7
Alignment in R
4
Sequence analysis
4.1
Introduction
4.2
DNA sequence analysis
4.3
Protein sequence analysis
4.4
Comprehensive analysis
4.5
Others
5
Molecular evolution analysis
5.1
Introduction
5.2
Evolution Theory
5.3
Standard molecule selection
5.4
Phylogenetic tree construction
6
Gene expression analysis
6.1
Introduction
6.2
Measurement platforms
6.3
DNA microarray
6.4
DEG analysis
6.5
Clustering analysis
6.6
Classification analysis
7
Gene annotation & enrichment
7.1
Introduction
7.2
Gene function annotation databases
7.3
Gene set enrichment analysis
7.4
Gene function prediction
8
Computer programming
8.1
Big data & data mining
8.2
Common tools in data mining
8.3
R language in biology
8.4
ABC of R language
8.5
Application cases of R
8.6
Summary
Appendix
A
R programming
A.0.1
The coursera on R programming
A.0.2
Learn R on codecademy
A.0.3
Data Science: R Basics
A.0.4
Data Analysis with R
B
Python programming
B.0.1
Data Analysis with R
C
Rstudio course
D
Docker course
DOWNLOAD
Download chapters
Download R code
Download housework
Published with bookdown
Bioinformatics
B
Python programming
Python is a popular programming language.
B.0.1
Data Analysis with R
Lecturer:
Dr
. XX, Duke University
URL:
Python语言最佳实践
MY RED TEXT
