Master of Science [M.Sc] Bioinformatics: Syllabus
Master of Science [M.Sc] Bioinformatics: Syllabus
The curriculum of the Master of Science [M. Sc] Bioinformatics is vast and capable enough to prepare students to predict the market trends as well as, advises the management for strategizing new ventures.
Semester-Wise Syllabus:
Semester 1:
Subjects | Description |
Introduction to Bioinformatics | Basics of bioinformatics, history, and scope of the field, introduction to biological databases and tools. |
Molecular Biology | Fundamentals of molecular biology, DNA structure and function, gene expression, and regulation. |
Computational Tools | Introduction to programming languages (Python, R), basics of algorithm design, and data structures. |
Biostatistics | Statistical methods for biological data analysis, probability theory, hypothesis testing, and regression. |
Semester 2:
Subjects | Description |
Genomics | Techniques in DNA sequencing, genome organisation, genome annotation, comparative genomics. |
Proteomics | Protein structure and function, techniques in protein analysis, mass spectrometry, protein-protein interactions. |
Database Management | Introduction to relational databases, SQL queries, management of biological databases. |
Data Mining and Machine Learning | Principles of data mining, machine learning algorithms, their applications in bioinformatics. |
Semester 3:
Subjects | Description |
Transcriptomics | Techniques in gene expression analysis, microarrays, RNA sequencing, differential gene expression analysis. |
Structural Bioinformatics | Protein structure prediction, molecular modelling, protein-ligand interactions, structural bioinformatics tools. |
Systems Biology | Mathematical modelling of biological systems, network analysis, computational modelling of biological pathways. |
Semester 4:
Subjects | Description |
Research Project | Independent research under faculty guidance, leading to a thesis or dissertation in a chosen area of bioinformatics. |
Master of Science [M.Sc] Bioinformatics: Recommended Books
Below, we have compiled a list of recommended books that can provide valuable insights:
Book Title | Author(s) | Description |
"Bioinformatics: Sequence and Genome Analysis" | David W. Mount | Provides a comprehensive introduction to bioinformatics, covering algorithms and techniques for sequence and genome analysis. |
"Biological Sequence Analysis" | Richard Durbin, Sean R. Eddy, et al. | Focuses on algorithms and methods for analysing biological sequences, including sequence alignment, gene prediction, and phylogenetics. |
"Introduction to Bioinformatics" | Arthur M. Lesk | Offers an overview of bioinformatics, covering key concepts, databases, algorithms, and applications in genomics and proteomics. |
"Bioinformatics Algorithms: An Active Learning Approach" | Phillip Compeau, Pavel Pevzner | Presents bioinformatics algorithms in a problem-solving framework, with hands-on exercises and interactive features. |
"Practical Bioinformatics" | Michael Agostino | A practical guide to bioinformatics tools and techniques, covering sequence analysis, database searching, and data visualisation. |
"Bioinformatics For Dummies" | Jean-Michel Claverie, Cedric Notredame | An accessible introduction to bioinformatics for beginners, covering basic concepts and practical applications in biological research. |
"Essential Bioinformatics" | Jin Xiong | Covers essential topics in bioinformatics, including sequence alignment, gene prediction, and molecular evolution, with practical examples. |
