Introduction to R and its applications in bioinformatics, installation of R and RStudio, R environment, variables, constants, data types, operators, and basic R programs. Representation of DNA, RNA, and protein sequences.
Conditional statements (if, if-else), looping statements (for, while), break and next statements. Simple biological programs such as nucleotide counting and GC content calculation.
Vectors, matrices, lists, data frames, factors, string operations, built-in functions, user-defined functions, and handling biological datasets.
Reading and writing text and CSV files, importing biological data, working with FASTA files, and simple sequence analysis.
Introduction to packages like ggplot2 and Bioconductor, basic statistics, graphs, charts, and introduction to clustering and classification Machine Learning algorithms in bioinformatics.
After completion of the course student will be able to:
This subject is on page 9, 10, 11 of the original AKTU PDF.
