Introduction to Computational Biology
Overview of computational biology as a multidisciplinary field.
The role of mathematics, statistics, and computer science in understanding biological systems.
Bioinformatics and Data Analysis
Tools and techniques used in computational biology to analyze biological data.
Sequence analysis (DNA, RNA, protein sequences).
Gene expression data, and genomic data analysis.
Structural bioinformatics and protein modeling.
Algorithms in Computational Biology
The design and application of algorithms to solve biological problems.
Common algorithms used in sequence alignment, genome assembly, and evolutionary biology.
Applications in Genomics and Proteomics
Genomic sequencing, variant detection, and data interpretation.
Proteomics: Protein structure, folding, and function prediction.
Evolutionary genomics: Phylogenetics, comparative genomics.
Computational Tools and Software
Software and programming languages used in computational biology (e.g., Python, R, bioinformatics tools).
Databases like GenBank, PDB, and others in the field.
Machine learning applications in biology for predictive models and big data analysis.

PART I FUNDAMENTALS OF COMPUTING IN BIOSCIENCES Role of Computers in Biosciences Essentials of C Programming Basic Programming Techniques Arrays in C Structures and Unions Pointers Functions Files and Command Line Arguments Role of Programming Languages in Bioinformatics Role of C++ and PERL in Bioinformatics PART II ‘OMICS IN BIOLOGY Introduction to Molecular Biology Cell Introduction to Bioinformatics Genomics Transcriptomics Metabolomics Glossary References Index.