note introduces the principles and algorithms from statistics, machine learning,
and pattern recognition to address exciting biological problems such as gene
discovery, gene function prediction, gene expression regulation, diagnosis of
cancers, etc. This course note will take a case-study approach to current topics
This note explains the
following topics: What is bioinformatics, Molecular biology primer, Biological
words, Sequence assembly, Sequence alignment, Fast sequence alignment using
FASTA and BLAST, Genome rearrangements, Motif finding, Phylogenetic trees and
Gene expression analysis.
This book is intended to serve both
as a textbook for short bioinformatics courses and as a base for a self teaching
endeavor. It is divided in two parts: A. Bioinformatics Techniques and B. Case
Studies. Each chapter of the first part addresses a specific problem in
bioinformatics and consists of a theoretical part and of a detailed tutorial
with practical applications of that theory using software freely available on
This note describes the computational challenges in
structural biology and explains the computational methods for analysing and
predicting macromolecular conformations and interactions and gives practice in
programming techniques for structural bioinformatics.
This note explains the basic bioinformatics concepts via a closed lab
exercise and a programming project. Also discusses the implementation of these
activities and some of the results/lessons we learned.