Instructor: Prof. Boojala VIJAY B. Reddy

This course introduces non-biology science students to the challenging and exciting area of bioinformatics through four major angles. The Basic Biology, Technologies that lead to experimental data growth in biology, Biological Databases, Computational Algorithms and Tools where Computer Science, Math, Statistics, Physics and Chemistry laws are used. The individual topics in the course are structured in such a way that a student with science background will get introduced to the subject. The course will further help them to choose their area of specialization within the Bioinformatics.

What is Bioinformatics?: Introduction and Scope of the Subject

I. Biology primers for non-biology students

Cell Biology: Evolution of the Cell, Prokaryotic & Eukaryotic Cells, Organelles, Cell Division, Viruses, Cell Biology Tools.

Biochemistry: Chemical Elements in Biomolecules, Functional Groups, Covalent & Non-covalent Interactions, Bioenergitics, Water, Macromolecules, Nucleic Acids, Proteins, Carbohydrates & Lipids.

Molecular Biology: Discovery of Hereditary Material, Chromosomes at Meiosis, Inheritance of Dominant and Recessive Genes, Gene Segregation & Linkage, Recombination and Genetic Maps, Genes & Enzymes, Genes & DNA, Transforming Principle, DNA as Genetic Material.

DNA and RNA: Chemical constituents, Discovery of DNA Structure, RNA Structures, DNA replication, Reverse Transcription, Kinds of RNA, RNA Synthesis.

Proteins: Building blocks of proteins, Sequence, Structure: primary, secondary, tertiary and quaternary structures, Function and Evolution.

Central Dogma of Molecular Biology: Transcription, Translation, tRNA & Ribosome structures, Prokaryotic and Eukaryotic Central Dogma and Gene Expression.

II. Technology that lead to data growth in biology

Basic Tools of Gene Exploration: Restriction Nucleases, Recombinant DNA, Gel Electrophoresis, Hybridization, Blotting, Genomic & cDNA Libraries, PCR, Microarray.

Proteome: 2D Gel Electrophoresis, Mass Spectrometry

Protein Structure Determination: X-ray Crystallography, NMR

III. Major Biological databases for mining and analysis

Sequence Databases: Primary and Secondary Databases, International Nucleotide Sequence Database, Collaboration (INSDC), Database Formats.

Information Retrieval: Entrez System, LocusLink, NCBI, Medical Databases, PubMed.

Genome Data Browsers: UCSC, NCBI, Ensemble Etc., and PDB.

Gene and Protein Expression Databases: Microarray, SAGE, Mass Spec Data, 2D-Gel databases.

IV. Major tools used in bioinformatics – Algorithms and Concepts

Gene Prediction: Methods & Programs, ORFs and Repeated Sequences, Prediction in Microbial and Eukaryotic Genes, Promoter Prediction in E. Coli & Eukaryotes, Evaluation of Prediction Methods.

Predicting Functional Regions on DNA/Protein: Prosite, Blocks, Pfam, Interpro.

Sequence Alignment: Mutations and Evolution, PAM & BLOSUM Matrices, Similarity Search, Comparison, Substitution Matrices, Pair-wise Alignments, Dynamic Programming, Gap Penalties, Assessing of Significance.

Database Searching for Similar Sequences: Search with Single Query, FASTA, BLAST, Smith-Waterman, Profiles-based, PSI & PHI-BLAST.

Protein Structural Analyses: Structure Classification (CATH, SCOP), Comparison (Dali, CE, VAST), Structure Prediction, Structure Modeling and Display Tools.

Multiple Sequence Alignments and Phylogenetic Analyses: Progressive Methods, Iterative Alignments, Localized Alignments, Position Specific Scoring. Concept of evolutionary tree, Maximum Parsimony Method, Distance Method.

Bioinformatics Books:

(in order of preference)

Bioinformatics and Functional Genomics.

By Jonathan Pevsner

Bioinformatics: Sequence and Genome Analysis, Second Edition

By David Mount, University of Arizona, Tucson

Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, 3rd Edition.

By Andreas D. Baxevanis (Editor), B. F. Francis Ouellette (Editor).

Fundamental Concepts of Bioinformatics.

By Dan E. Krane, Michael L. Raymer

Introduction to Bioinformatics

By Arthur M. Lesk

Topics in Bioinformatics

(A Future advanced course)

Perl to Facilitate Biological Data Analysis: