Bioinformatics - University of Mysore

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Oct 2, 2013 (4 years and 1 month ago)

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Overview of Bioinformatics

BY

DR.C. AMRUTHAVALLI

HOD OF BIOINFORMATICS

CIST

UNIVERSITY OF MYSORE



Bioinformatics is the field of science in which molecular
biology, statistics, computer science, and information
technology merge into a single discipline.



Bioinformatics is the science of managing and analyzing
molecular biology data using advanced computing
techniques.



Bioinformatics is the computer
-
assisted data
management discipline that helps us:



Gather, store, analyze, integrate biological and genetic
information (data), and represent this information
efficiently.



Bioinformatics is the electronic infrastructure of
molecular biology




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Software of Bioinformatics


There are many different bioinformatics tools available over the
Internet free of charge to whomever wishes to use them.


There are also many commercial software packages used in
bioinformatics by researchers who can afford it.


The number of software products is growing constantly, so that it is
impossible to list, as software developers working in the life sciences
(or life scientists with software development talents), are constantly
updating and producing useful new applications.


Development and implementation of tools that enable efficient access
and management of different types of information, such as various
databases, integrated mapping information



Bioinformatics is associated typically with massive databases of
gene and protein sequence and structure/function information
databases.


New sequences, new structures or protein/gene function that are
discovered are searched, (compared) against what is already
known, (gathered), and deposited into the databases.


(These searches are done by remote computer access using
various bioinformatics tools.)


Analysis and interpretation of various types of biological data
including: nucleotide and amino acid sequences, protein domains,
and protein structures.


Development of new algorithms and statistics with which to
assess biological information, such as relationships among
members of large data sets.



What type of information do we deal with in
bioinformatics?


DNA


(Genome)

RNA


(Transciptome)

Protein (Proteome)


Sequence

Structure

Evolution

Pathways

Interactions

Mutations


DNA


Simple Sequence Analysis

Database searching

Pairwise analysis


Regulatory Regions


Gene Finding


Whole Genome Annotations


Comparative Genomics (Analyses between Species
and Strains )

RNA


Splice Variants


Tissue specific expression


Structure


Single gene analysis (various cloning
techniques)


Experimental data involving thousands of
genes simultaneously


DNA Chips, MicroArray, and Expression
Array Analyses


Protein


Proteome of an Organism


2D gels


Mass Spec


2D Structure


3D Structure


Sequence Analysis Software


• What is the information contained in a biological sequence?

• How can we analyze it to gain knowledge?

• Does it contain any functional clues
?

Biological problems that computers can help with:


I cloned a gene
-

is it a known gene?

Does the sequence match? Is the sequence any good?

Does it look like anything else in the database?

Which family does it belong to?

How can I find more family members?

I have an orphan receptor, how can I find its ligand?

The gene Iím interested in was found in another

organism, but not mine. How can I look for it?

I have linkage to a specific region on chromosome x,

how do I find genes in that region?



The Potential of Bioinformatics


The potential of Bioinformatics in the identification of useful genes
leading to the development of new gene products, drug discovery
and drug development has led to a paradigm shift in biology and
biotechnology
-
these fields are becoming more & more
computationally intensive. The new paradigm, now emerging, is
that all the genes will be known "in the sense of being resident in
database available electronically", and the starting point of
biological investigation will be theoretical and a scientist will begin
with a theoretical conjecture and only then turning to experiment to
follow or test the hypothesis. With a much deep understanding of
the biological processes at the molecular level, the Bioinformatics
scientist have developed new techniques to analyse genes on an
industrial scale resulting in a new area of science known as
'Genomics'.


Bioinformatics
-

Industry Overview


The Bioinformatics industry has grown to keep up with the
information explosion, growing at 25
-
50% a year. In 2000,
the US market Research company Oscar Gruss estimated
that the value of the Bioinformatics industry would touch
$5 billion. Now it s demand for individuals capable of
doing bioinformatics is soaring. Industry's demand for
scientists with skills in Bioinformatics far exceeds the
supply of qualified specialists in the field, Seems likely that
this figure will be reached within the coming year.
Therefore, companies are developing methods of spotting
potential Bioinformatics experts and then training them on
the job.

Assigning fold and function utilizing similarity to
experimentally

characterized proteins:



Sequence similarity
:
BLAST and others



Beyond sequence
similarity: matching
sequences and shapes
(
threading
)


Aims of Bioinformatics:


The aims of bioinformatics are basically three
-
fold. They are


Organization of data in such a way that it allows researchers to
access existing information & to submit new entries as they are
produced. While data
-
creation is an essential task, the information
stored in these databases is useless unless analyzed. Thus the
purpose of bioinformatics extends well beyond mere volume control.



To develop tools and resources that help in the analysis of data. For
example, having sequenced a particular protein, it is with previously
characterized sequences. This requires more than just a
straightforward database search. As such, programs such as FASTA
and PSI
-
BLAST much consider what constitutes a biologically
significant resemblance. Development of such resources extensive
knowledge of computational theory, as well as a thorough
understanding of biology.



Use of these tools to analyze the individual systems in detail, and
frequently compared them with few that are related.


Analysis activity in Bioinformatics




Development of methods to predict the
structure and/or function of newly discovered
proteins and structural RNA sequences.



Clustering protein sequences into families of
related sequences and the development of
protein models.



Aligning similar proteins and generating
phylogenetic trees to examine evolutionary
relationships


Sub
-
disciplines within bioinformatics


There are three important sub
-
disciplines within
bioinformatics involving computational biology:

The development of new algorithms and statistics
with which to assess relationships among
members of large data sets


The analysis and interpretation of various types of
data including nucleotide and amino acid
sequences, protein domains, and protein
structures and


The development and implementation of tools
that enable efficient access and management of
different types of information


Medical applications:



Understand life processes in healthy and disease states.



Genetic Disease (SNPs)



Pharmaceutical and Biotech Industry



To find (develop) new and better drugs.



Gene
-
based or Structure
-
based Drug Design



Agricultural applications



Disease, Drought Resistant Plants



Higher Yield Crops

Careers in Bioinformatics


Genomics:

• Genome sequencing of


Bacteria, viruses


Animals


Plants

• Comparative genomics

• Annotation and Mapping

• Gene Discovery


Functional Genomics (Gene Expression and Regulation):

• Control Regions



Switches



Circuits



Bypass



Feedback loops

• Environmental Effects

• Diseased States

• Chemical Consequences

Careers in Bioinformatics


Pharmacogenomics:

• SNPs



Regional, ethnic variations



Inheritance patterns



Radiological/ecological modifications

• Therapeutic target recognition

• Correlation of drug and expression effects

• Pathway Effects

Proteomics:

• Protein Profiling



Alternate splice variants



Orphan genes



Cryptic introns

• Gene Therapy


Careers in Bioinformatics

Structural Genomics:

• Experimental Protein structures



Apo
state



Holo
state



Structural modifications

• Membrane Proteins

• Homology Modelling

• Comparative Modelling


Drug and Vaccine Design:

• Screening Natural Products


Plants,


Fungi



Bacteria

• Chemicals


In silico
modifications of ligands

• Vaccine design and delivery


Conclusion


With the confluence of biology and computer science, the computer
applications of molecular biology are drawing a greater attention among
the life science researchers and scientists these days. As it becomes
imperative for biologists to seek the help of information technology
professionals to accomplish the ever growing computational
requirements of a host of exciting and needy biological problems, the
synergy between modern biology and computer science is to blossum
in the days to come. Thus the research scope for all the mathematical
techniques and algorithms coupled with software programming
languages, software development and deployment tools are to get a
real boost. In addition, information technologies such as databases,
middleware, graphical user interface(GUI) design, distributed object
computing, storage area networks (SAN), data compression, network
and communication and remote management are all set to play a very
critical role in taking forward the goals for which the
Bioinformatics

field came into existence.

The genomics revolution has transformed the
landscape of drug discovery. DNA and protein
sequences are yielding a host of new therapeutic
targets and an enormous amount of associated
information. The challenges in the genomics arena
are to securely and reliably manage and analyze
huge quantities of sequence and associated data,
and to extract useful information from that data

Detailed study of the three dimensional molecular
structure of DNA, proteins, and other biological
compounds can be critical to understanding their
function and to designing therapeutics to control
their effects. Modeling, simulation, and other
computational techniques to predict and analyze
this structure are essential components in today's
discovery research

Significance of protein folding
problem

O
2




V
L
S
E
G
E
W
Q
L
V
L
V
.
.
.

Sequence

structure

function

folds into a 3D



to perform a