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Syllabus | B.Tech-Computer Science & Engineering | Bioinformatics

  Bioinformatics Learning Schedule
Pre-requisites: Basics of IT 3 0 0 3


This course will provide an overview of bioinformatics, covering a broad selection of the most important techniques used to analyze biological sequence and expression data. Students will acquire a working knowledge of bioinformatics applications through hands-on use of software to ask and answer biological questions. In addition, the course will provide students with an introduction to the theory behind some of the most important algorithms used to analyze sequence data (for example, alignment algorithms and the use of hidden Markov models). Topics covered will include protein and DNA sequence alignments, evolutionary analysis and phylogenetic trees, obtaining protein secondary structure from sequence, and analysis of gene expression including clustering methods.


The objective of this course is to

  1. impart knowledge on basic techniques of Bioinformatics and on analysis of biological data using computational methods
  2. investigating problems in molecular and biology from a computational perspective.


On completion of this course, the students will be able to

  1. extract information from different types of bioinformatics data (gene, protein, disease, etc.), including their biological characteristics and relationships
  2. employ different data representation models and formats used for bioinformatics data representation, including markup languages such as SBML and CellML, and ontologies such as GO ontology
  3. apply the different approaches used for data integration and data management, including data warehouse and wrapper approaches
  4. analyze processed data with the support of analytical and visualization tool
  5. Interact with non-bioinformatics professionals, such as biologists and biomedical researchers, to better understand their bioinformatics needs for improved support and service delivery
  6. design and develop bioinformatics solutions by adapting existing tools, designing new ones or a combination of both.


Unit I: Introduction

Bioinformatics objectives and overviews, Interdisciplinary nature of Bioinformatics, Data integration, Data analysis, Major Bioinformatics databases and tools. Metadata: Summary 40 & reference systems, finding new type of data online. Molecular Biology and Bioinformatics: Systems approach in biology, Central dogma of molecular biology, problems in molecular approach and the bioinformatics approach, overview of the bioinformatics applications.

Unit II: DNA

Basic chemistry of nucleic acids, Structure of DNA, Structure of RNA, DNA Replication, -Transcription, -Translation, Genes- the functional elements in DNA, Analysing DNA, DNA sequencing. Proteins: Amino acids, Protein structure, Secondary, Tertiary and Quaternary structure, Protein folding and function, Nucleic acid-Protein interaction.

Unit III: Applications for bioinformatics

Perl Basics, Perl applications for bioinformatics- Bioperl, Linux Operating System, mounting/ unmounting files, tar, gzip / gunzip, telnet, ftp, developing applications on Linux OS, Understanding and Using Biological Databases, Overview of Java, CORBA, XML, Web deployment concepts.

Unit IV:  Biological data storage techniques

Genome, Genomic sequencing, expressed sequence tags, gene expression, transcription factor binding sites and single nucleotide polymorphism. Computational representations of molecular biological data storage techniques: databases (flat, relational and object oriented), and controlled vocabularies, general data retrieval techniques: indices, Boolean search, fuzzy search and neighboring, application to biological data warehouses.

Unit V: Representation of patterns and relationships in bioinformatics

Macromolecular structures, chemical compounds, generic variability and its connection to clinical data. Representation of patterns and relationships: sequence alignment algorithms, regular expressions, hierarchies and graphical models, Phylogenetic BLAST.


  • Fundamental concepts of Bioinformatics – D E Krane and M L Raymer, Pearson Education.
  • Bioinformatics Methods & applications, Genomics, Proteomics & Drug Discovery – Rastogi, Mendiratta and Rastogi, PHI, New Delhi.


  1. Bioinformatics: with fundamentals of genomics and proteomics – Shubha Gopal, et.al., Mc Graw Hill.
  2. Developing Bio informatics computer skills – O’Reilly, CBS.
  3. Evolutionary Bioinformatics – Forsdyke, Springer.