Elements of BioInformatics

Martin Saturka

Syllabus, text, version 0.3

Abstract: We present varoius topics of bioinformatics in this course. We start with backrounds of the topics in relevant areas of classical mathematical and natural sciences. We outline main ideas of bioinformatics fields, we describe relevant methods, and we present some practical examples.


Table of Contents


1  Presentation

Bioinformatics is an interdisciplinary field that deals with huge amount of biological data. It takes concern in data acquisition, store and analysis. Main tasks of bioinformatics are understanding biological data and using them to solve problems in biology and medicine. Bioinformatics uses mathematical and computational methods to extract information from biological data. Current biology produce huge amount of data. Understanding them is the stepping stone for their effective usage.

We introduce main parts of bioinformatics. We start with physical and informatical background of biology. We give introduction into computer sciences and statistics. We outline high data throughput experimental methods in biology. We explain algorithms based on logic, informatics and statistics for pattern recognition, data mining, storing and accessing. We present software tools for and practical examples of bioinformatics. We outline general connections of biology and computer science.

The path from data to information to knowledge is the red thread of bioinformatics. Many new areas arise in interfaces between biology and informatics. They comprise, inter alia, genomics, expressomics, proteomics, and metabolomics. We try to approach them so that it is possible to use software tools to understand their experimental data.


2  Topics

Main fields and principles of bioinformatics. Physical and informatic aspects of biology. Guidance into computer science. Basics of biological data acquisition experiments. Biological data processing methods. Statistical, logical, informatic algorithms for pattern recognition. Data and knowledge storing and accessing. Examples of bioinformatics utilization. Software support for bioinformatics. Outline of computational biology.


3  Lecture index

This course consists of twelve lectures that are listed below. They are given short outlines below.
  1. Introduction: biology, physics
  2. Computer science basics
  3. Genes: sequencing
  4. Sequences: searching
  5. Gene expression: profiling
  6. Expression profiles: statistics
  7. Expression profiles: intriguing
  8. 3D structures: acquisition
  9. Structure types & databases
  10. Ontology, examples
  11. Software support
  12. Biology and computations

4  Course survey

1) Introduction: biology, physics
Outline of basics on biological systems and functions at fundamental levels. Their settlement in natural and mathematical sciences.  
2) Computer science basics
Theoretical background of descriptions based on deterministic and stochastic models. Computation hardness, practical examples.  
3) Genes: sequencing
Description of chromosomes and genes. Methods of gene sequencing. Assembly of sequence fragments. Search for genes.  
4) Sequences: searching
Biological utilization of sequence matching. Alignments and pattern discovery. Direct and abstract methods. Evaluations.  
5) Gene expression: profiling
Current and prospective methods of gene profiling. Data acquisition. Data standardization. Linear approximations of data.  
6) Expression profiles: statistics
Statistics approaches. Situations with known qualititive characteristics. Polylinear approximations. General dimension reduction.  
7) Expression profiles: intriguing
Data mining technics. Intuition leading to applied mathematical logic. Ideas and theory with exploitation of the methods in biology.  
8) 3D structures: acquisition
Experimental and computational methods of structure determinantion for proteins and nucleic acids. Function prediction.  
9) Structure types & databases
Online databases. Classification families of biomacromolecules. Search and retrieval engines with web interface.  
10) Ontology, examples
Annotation of genes, their products and functions. System biology, evolution, hierarchy. Utilize in medical practice.  
11) Software support
Free and open source software available for bioinformatics. Structural text handling. Computational statistics packages.  
12) Biology and computations
Areas of computations in biology. Modeling technics. Laboratory information management. Computing with biosystems.  

This document was translated from LATEX by HEVEA.