2. CONTENTS
• Introduction
• Goals of Bioinformatics
• Field of Bioinformatics
• Bioinformatics Data
• Applications of Bioinformatics
• Bioinformatics & Molecular Medicine
• Tools in Bioinformatics
3. INTRODUCTION
• 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 information carrier).
• The biological information of nucleic acids 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.
4. INTTRODUCTION
• Bioinformatics is a field in which biology, mathematics, statistics, CS and IT
are merged into a single discipline to process biological data.
• Complex machines are used to read in biological data at a much faster rate
than before.
• The term “Bioinformatics” was invented by Paulien Hogeweg and Ben Hesper
in 1970.
• The need for bioinformatics has arisen from the recent explosion of publicly
available genomic information, such as resulting from the Human Genome
Project.
• Gain a better understanding of gene analysis, taxonomy, & evolution.
• To work efficiently on the rational drug designs and reduce the time taken for
the development of drug manually.
5. 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 environmental benefits in identifying waste and clean up
bacteria.
• In agriculture, it can be used to produce high yield, low maintenance
crops.
6. FIELD OF BIOINFORMATICS
• Molecular Medicine
• Gene Therapy
• Drug Development
• Microbial genome applications
• Crop Improvement
• Forensic Analysis of Microbes
• Biotechnology
• Evolutionary Studies
• Bio-Weapon Creation
7. BIOINFORMATICS DATA
Bioinformatics deals with any type of data that is of interest to biologists
• DNA and protein sequences
• Gene expression (microarray)
• Raw data collected from field or laboratory experiment –
Images, virtual models, Software
• Articles from literature and databases of citations
Each type of data can exist in many incompatible computer formats
The analysis of DNA sequence data has come to dominate the field of
bioinformatics, but the term can be applied to any type of biological data that
can be recorded as numbers or images and handled by computers
8. APPLICATIONS OF 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
9. APPLICATIONS
Prediction of Protein Structure:-
• It is easy to determine the primary structure of proteins in the form of
amino acids which are present on the DNA molecule but it is difficult
to determine the secondary, tertiary or quaternary structures of
proteins. Tools of bioinformatics can be used to determine the
complex protein structures.
Genome Annotation:-
• In genome annotation, genomes are marked to know the regulatory
sequences and protein coding. It is a very important part of the human
genome project as it determines the regulatory sequences.
10. APPLICATIONS
Comparative Genomics:-
• Comparative genomics is the branch of bioinformatics which determines the
genomic structure and function relation between different biological species.
For this purpose, intergenomic maps are constructed which enable the
scientists to trace the processes of evolution that occur in genomes of
different species.
Health and Drug discovery:-
• The tools of bioinformatics are also helpful in drug discovery, diagnosis and
disease management. Complete sequencing of human genes has enabled the
scientists to make medicines and drugs which can target more than 500
genes.
11. APPLICATIONS
Preventative medicine:-
• Gene identification by sequence inspection and prediction of splice
sites allows mutations to be corrected easily. This is much used in the
analysis of mutations that cause cancer.
Gene therapy:-
• Mutations are easily detected and quantified through next-generation
sequencing technology in a heterogeneous sample thus a cost
effective precision medicine, “right drug at right dose to the right
patient at the right time” can be administered.
12. BIOINFORMATICS & MOLECULAR
MEDICINE
• Early detection of genetic predispositions to diseases
• Improved diagnosis of disease
• Pharmacogenomics
o Customized drugs
o Individualized drugs selection
o Better methods for determining drug doses for individuals
o Appropriate doses determination
• Gene therapy and control systems for drugs
13. TOOLS IN BIOINFORMATICS
• Storage
Databases
o Building, Querying, Complex data
o Annotations, Citations
• Standards
• Interoperability
• Knowledge Management
o Classification, Vocabularies, Ontologies
• Communications
• Process Workflow
14. TOOLS IN BIOINFORMATICS
• Discovery and Analyses
Text String Comparison
• Text search, Statistical analysis
Finding Patterns
• AI / Machine Learning, Clustering, Data mining
Geometric
• Robotics, Graphics (Surfaces, Volumes),
Comparison and 3D Matching (Vision, Recognition)
Physical Simulation
• Newtonian Mechanics, Electrostatics, Numerical Algorithms, Simulation
15. TOOLS IN BIOINFORMATICS
BLAST
• Basic Local Alignment Search Tool.
• It is an algorithm for comparing biological sequences information, such
as amino acid sequence of different proteins or the nucleotides of DNA
sequences.
• BLAST is used to identify library sequences that resembles the query
sequences.
16. CONCLUSION
• As we can see that Technological advances have had both positive &
negative impacts on our daily lives.
• Bioinformatics is just biology using computers & mathematics.
• Bioinformatics has become an important part of many areas of biology.
In experimental molecular biology, bioinformatics techniques such as
image & signal processing allow extraction of useful results from large
amounts of raw data. In the field of genetics & genomics.
