introduction to bioinfromatics.pptx

Bioinformatics
What is bioinformatics? Application of techniques from computer
science to problems from biology.
Computer Science
Bioinformatics
Biology
Why is it interesting?  Important problems.
 Massive quantities of data.
 Desperate need for efficient solutions.
 Success is rewarded.

HISTORY OF BIOINFORMATICS
• Bioinformatics is an interdisciplinary field that develops methods and
software tools for understanding biological data.
• Bioinformatics combines computer science, statistics, mathematics,
and engineering to analyze and interpret biological data.
• Bioinformatics has been used for in silico analyses of biological
queries using mathematical and statistical techniques.
• Bioinformatics derives knowledge from computer analysis of
biological data. These can consist of the information stored in the
genetic code, but also experimental results from various sources,
patient statistics, and scientific literature.
• Research in bioinformatics includes method development for storage,
retrieval, and analysis of the data.

• Bioinformatics: Research, development, or application of computational tools and
approaches for expanding the use of biological, medical, behavioral or health data,
including those to acquire, store, organize, archive, analyze, or visualize such data.
• Computational Biology: Computational biology uses mathematical and
computational approaches to address theoretical and experimental questions in
biology.
• Classical" bioinformatics: "The mathematical, statistical and computing methods
that aim to solve biological problems using DNA and amino acid sequences and
related information.” "

Concept of bioinformatics
• Bioinformatics is the application of information technology to store, organize and
analyze the vast amount of biological data.
• The stored data is available in the form of sequences and structures of proteins and
nucleic acids.
• The biological information of nucleic acid is available as sequences while the data
of proteins is available as sequences and structures.
• Sequences are represented in single dimension where as the structure contains the
three dimensional data of sequences.

• Bioinformatics is a field in which biology,mathematics,statistics,CS and IT are
merged into a single discipline to process biological data.
• The term bioinformatics was invented by Paulien Hogeweg and Ben Hesper in
1970.

Aim of Bioinformatics
• The first aim of bioinformatics is to store the biological data organized
in form of a database. For example: GenBank for nucleotide and
protein sequence information, Protein Data Bank for 3D
macromolecular structures, etc.
• The second aim is to develop tools and resources that aid in the
analysis of data. For example: BLAST to find out similar
nucleotide/amino-acid sequences, ClustalW to align two or more
nucleotide/amino-acid sequences, Primer3 to design primers probes
for PCR techniques, etc.
• The third and the most important aim of bioinformatics is to exploit
these computational tools to analyze the biological data interpret the
results in a biologically meaningful manner.

Goals
• 1. Normal biological processes
• 2. Malfunctions in these processes which lead to diseases
• 3. Approaches to improving drug discovery

Contd..
• To study how normal cellular activities are altered in different disease
states, the biological data must be combined to form a comprehensive
picture of these activities.
• Therefore, the field of bioinformatics has evolved such that the most
pressing task now involves the analysis and interpretation of various
types of data.
• This includes nucleotide and amino acid sequences, protein domains,
and protein structures. The actual process of analyzing and interpreting
data is referred to as computational biology.

• Important sub-disciplines within bioinformatics and computational
biology include:
• Development and implementation of computer programs that enable
efficient access to, use and management of, various types of
information
• Development of new algorithms (mathematical formulas) and
statistical measures that assess relationships among members of large
data sets

• The primary goal of bioinformatics is to increase the understanding of
biological processes.
• Major research efforts in the field include sequence alignment, gene
finding, genome assembly, drug design, drug discovery, protein
structure alignment, protein structure prediction, prediction of gene
expression and protein–protein interactions, genome-wide association
studies, the modeling of evolution and cell division/mitosis.

• Common activities in bioinformatics include mapping and analyzing DNA and
protein sequences, aligning DNA and protein sequences to compare them, and
creating and viewing 3-D models of protein structures.
• Bioinformatics encompasses the use of tools and techniques from three separate
disciplines;
1 molecular biology (the source of the data to be analyzed)
2 computer science (supplies the hardware for running analysis and the
networks to communicate the results)
3 Data analysis algorithms which strictly define bioinformatics.

Applications
• Bioinformatics joins mathematics, statistics, and computer science and
information technology to solve complex biological problems.
• These problems are usually at the molecular level which cannot be solved by other
means
• Various bioinformatics application can be categorized under following groups:
 Sequence Analysis
 Structure Analysis
 Function Analysis

• Sequence Analysis: All the applications that analyzes various types of sequence
information and can compare between similar types of information is grouped
under Sequence Analysis.
• Function Analysis: These applications analyze the function engraved within the
sequences and helps predict the functional interaction between various proteins or
genes. Also expressional analysis of various genes is a prime topic for research
these days.
• Structure Analysis: When it comes to the realm of RNA and Proteins, its
structure plays a vital role in the interaction with any other thing.
• Structural Bioinformatics with is devoted to predict the structure and possible
roles of these structures of Proteins or RNA

Why Bioinformatics is necessary?
• The need for bioinformatics has arisen from the recent explosion of the publicly
available genomic information such as resulting from the Human Genome Project.
• Gain a better understanding of gene analysis, taxonomy and evolution
• To work efficiently on the rational drug designs and reduce the time taken for the
development of drug manually.

Goals of Bioinformatics
• To uncover the wealth of biological information hidden in the mass of sequence,
structure, literature and biological data.
• It is being used now and in the foreseeable future in the areas of molecular
medicine.
• It has environment benefits in identifying waste and cleanup bacteria.
• In agriculture, it can be used to produce high yield ,low maintenance crops.

Application of Bioinformatics in various Fields
18
1. Molecular medicine
2. Personalised medicine
3. Preventative medicine
4. Gene therapy
5. Drug development
6. Microbial genome applications
7. Waste cleanup
8. Climate change Studies
9. Alternative energy sources
10. Biotechnology
11. Antibiotic resistance
12. Forensic analysis of microbes
13. Bio-weapon creation
14. Evolutionary studies
15. Crop improvement
16. Insect resistance
17. Improve nutritional quality
18. Development of Drought resistance varieties
19. Vetinary Science

Where Bioinformatics ?
• In experimental molecular biology
• In Genetics and genomics
• In generating biological data
• Analysis of gene and protein expression
• Comparison of genomic data
• In simulation & modeling of DNA,RNA & Protein

Why are these Important?
• Data is submitted directly to biological databases for indexing, organization, and
data optimization.
• They help researchers find relevant biological data by making it available in a
format that is readable on a computer.
• All biological information is readily accessible through data mining tools that
save time and resources.
• Biological databases can be broadly classified as sequence and structure databases.
• Structure databases are for protein structures, while sequence databases are for
nucleic acid and protein sequences.

Life Form
 Phenotype = genotype + environment + life history + epigenetics
 Your genotype is your DNA sequence, both nuclear and mitochondrial. The
genotype is inherited from your parents.
 Your phenotype is the collection of your observable traits, other than your
genotype. These include macroscopic properties such as height, weight,
and eye and hair colour; and microscopic ones such as whether you suffer
from sickle-cell anaemia
 Your life history includes the integrated total of your experiences, and the
physical and psychological environment within which you developed.
 At the interface between the genome and life experience are epigenetic
factors

8.1 Identifying DNA as the Genetic Material
KEY CONCEPT
DNA was identified as the genetic material through a
series of experiments.

Griffith finds a ‘transforming principle.’
• Griffith experimented with the bacteria that cause
pneumonia.
• He used two forms: the S form (deadly) and the R form (not
deadly).
• A transforming material passed from dead S bacteria to live
R bacteria, making them deadly.

Avery identified DNA as the transforming principle.
• Avery isolated and purified Griffith’s transforming
principle.
• Avery performed three tests on the transforming
principle.
– Qualitative tests showed DNA was present.
– Chemical tests showed
the chemical makeup
matched that of DNA.
– Enzyme tests showed
only DNA-degrading
enzymes stopped
transformation.

Hershey and Chase confirm that DNA is the genetic
material.
• Hershey and Chase studied viruses that infect bacteria, or
bacteriophages.
• Tagged DNA was found inside the bacteria; tagged
proteins were not.
– They tagged viral DNA
with radioactive
phosphorus.
– They tagged viral
proteins with radioactive
sulfur.

Contd..
• When bacteriophages, which are composed of DNA and protein, infect
bacteria, their DNA enters the host bacterial cell, but most of their protein
does not.
• Hershey and Chase and subsequent discoveries all served to prove that DNA
is the hereditary material.

KEY CONCEPT
DNA structure is the same in all organisms.

DNA is composed of four types of nucleotides.
• DNA is made up of a long chain of nucleotides.
• Each nucleotide has three parts.
– a phosphate group
– a deoxyribose sugar
– a nitrogen-containing base
phosphate group
deoxyribose (sugar)
nitrogen-containing
base

• The nitrogen containing bases are the only difference in
the four nucleotides.

Watson and Crick determined the three-dimensional
structure of DNA by building models.
• They realized that DNA is
a double helix that is
made up of a sugar-
phosphate backbone on
the outside with bases on
the inside.

• Watson and Crick’s discovery built on the work of Rosalind
Franklin and Erwin Chargaff.
– Franklin’s x-ray images suggested that DNA was a
double helix of even width.
– Chargaff’s rules stated that A=T and C=G.

T
A
C
G
Nucleotides always pair in the same way.
• The base-pairing rules show
how nucleotides always pair
up in DNA.
• Because a pyrimidine
(single ring) pairs with a
purine (double ring), the
helix has a uniform width.
– A pairs with T
– C pairs with G

• The backbone is connected by covalent bonds.
hydrogen bond covalent bond
• The bases are connected by hydrogen bonds.

KEY CONCEPT
DNA replication copies the genetic information of a
cell.

introduction to bioinfromatics.pptx

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