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AKTU R Programming for Bioinformatics Lab (BBI553) Syllabus PDF – B.Tech 3rd Year
R Programming for Bioinformatics Lab BBI553
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- Semester 5
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Official AKTU syllabus of R Programming for Bioinformatics Lab (BBI553) for B.Tech 3rd Year – 1 credits, L-T-P 0-0-2. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — R Programming for Bioinformatics Lab
Download PDFBBI553 · 1 credits · L-T-P 0-0-2
Course Outcomes
At the end of the course, the student will be able to:
| CO1 | Write simple R programs using variables, operators, and input/output statements for biological data representation. | K3 |
| CO2 | Implement conditional and looping constructs to solve biological problems such as nucleotide counting and GC content calculation. | K3 |
| CO3 | Create and manipulate data structures (vectors, matrices, lists, data frames) and develop user-defined functions for biological datasets. | K3 |
| CO4 | Perform file handling operations to read/write CSV and FASTA files and conduct basic sequence analysis. | K3 |
| CO5 | Apply statistical methods and visualization techniques (plots, graphs, clustering) to analyze and interpret biological data. | K3 |
List of Experiments
- Write simple R programs using variables, operators, and basic input-output statements.
- Implement programs using conditional statements (if, if-else) for simple biological decision-making problems.
- Write programs using loops (for, while) for repetitive biological calculations.
- Create and manipulate vectors and matrices for storing DNA sequences and biological data.
- Implement programs using lists and data frames for organizing gene or sample information.
- Write user-defined functions for simple biological operations.
- Write a program to count nucleotide frequency (A, T, G, C) in a DNA sequence.
- Write a program to calculate GC content and sequence length of a DNA sequence.
- Read biological data from CSV/text files and perform basic data analysis.
- Read and analyze sequence data from FASTA files.
- Perform basic statistical analysis such as mean, median, standard deviation, and correlation on biological datasets.
- Create graphical representations such as bar plots, histograms, scatter plots, and gene expression plots using R. Note: The instructor may add / delete / modify / tune experiments as required. B. TECH. (BIOINFORMATICS) — SIXTH SEMESTER DETAILED SYLLABUS
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