Hi, I am Jesmin, studying MCSE. I think this file will help you if you want to know the basic information about Bioinformatics and the use of BLAST tool. The BLAST tool is the tool that matches the sequences of DNA,RNA and proteins.

1. Bioinformatics Introduction & Use of
Blast Tool
Prepared By Jesmin Zaman

2. BIOINFORMATICS:
Bioinformatics is an interdisciplinary field that develops methods and software tools
for understanding biological data, in particular when the data sets are large and
complex. As an interdisciplinary field of science, bioinformatics combines biology,
computer science, information engineering, mathematics and statistics to analyze and
interpret the biological data.

3. HISTORY:
• Historically, the term bioinformatics did not mean what it means today. Paulien
Hogeweg and Ben Hesper coined it in 1970 to refer to the study of information
processes in biotic systems.
• A pioneer in the field was Margaret Oakley Dayhoff. She compiled one of the first
protein sequence databases, initially published as books and pioneered methods of
sequence alignment and molecular evolution.
Margaret O. Dayhoff

4. MAJOR RESEARCH AREAS OF BIOINFORMATICS:
Sequence Analysis: In bioinformatics, sequence analysis is the process of subjecting a
DNA, RNA or peptide sequence to any of a wide range of analytical methods to
understand its features, function, structure, or evolution.
Genome Analysis: Personal genomics or consumer genetics is the branch of genomics
concerned with the sequencing, analysis and interpretation of the genome of an
individual.
Computational evolutionary biology: Computational biology has assisted the field of
evolutionary biology in many capacities. This includes:
 Using DNA data to reconstruct the tree of life with computational phylogenetics
 Fitting population genetics models (either forward time or backward time) to DNA data
to make inferences about demographic or selective history
 Building population genetics models of evolutionary systems from first principles in order
to predict what is likely to evolve.

5. MAJOR RESEARCH AREAS OF BIOINFORMATICS:
Literature Analysis: The theorical analysis about bioinformatics is the literature
analysis.
Analysis of Gene expression: Gene expression is the process by which information
from a gene is used in the synthesis of a functional gene product that enables it
to produce end products, protein or non-coding RNA, and ultimately affect a
phenotype, as the final effect.
Analysis of Regulation: Regulation is the management of complex systems according
to a set of rules and trends.
 in biology, gene regulation and metabolic regulation allow living organisms to adapt
to their environment and maintain homeostasis.

6. MAJOR RESEARCH AREAS OF BIOINFORMATICS:
Analysis of protein expression: Protein expression may refer to:
 Gene expression, the processes that convert the information of DNA genes into a
functional copies of mRNA in living cells
 Protein production, the method of generating some quantity of a specific protein in
biotechnology
Analysis of mutation in cancer: In biology, a mutation is an alteration in the
nucleotide sequence of the genome of an organism, virus, or extrachromosomal
DNA.
Comparative Genomics: Comparative genomics is a field of biological research in
which the genomic features of different organisms are compared.

7. MAJOR RESEARCH AREAS OF BIOINFORMATICS:
Hi-throughput Image Analysis: Computational technologies are used to accelerate or fully
automate the processing, quantification and analysis of large amounts of high-information-content
biomedical imagery. Modern image analysis systems augment an observer's ability to make
measurements from a large or complex set of images, by improving accuracy, objectivity, or speed.
A fully developed analysis system may completely replace the observer. Although these systems are
not unique to biomedical imagery, biomedical imaging is becoming more important for both diagnostics
and research. Some examples are:
 high-throughput and high-fidelity quantification and sub-cellular localization (high-content screening,
cytohistopathology, Bioimage informatics)
 morphometrics
 clinical image analysis and visualization
 determining the real-time air-flow patterns in breathing lungs of living animals
 quantifying occlusion size in real-time imagery from the development of and recovery during arterial
injury
 making behavioral observations from extended video recordings of laboratory animals
 infrared measurements for metabolic activity determination
 inferring clone overlaps in DNA mapping, e.g. the Sulston score.

8. GOALS OR APPLICATIONS OF BIOINFORMATICS:
• 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 also 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, management and
use of, various types of information.
 Development of new algorithms (mathematical formulas) and statistical measures that assess relationships
among members of large data sets. For example, there are methods to locate a gene within a sequence,
to predict protein structure and/or function, and to cluster protein sequences into families of related
sequences.
• The primary goal of bioinformatics is to increase the understanding of biological processes. What sets it
apart from other approaches, however, is its focus on developing and applying computationally intensive
techniques to achieve this goal. Examples include: pattern recognition, data mining, machine learning
algorithms, and visualization. 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.
• Often, such identification is made with the aim of better understanding the genetic basis of disease,
unique adaptations, desirable properties (esp. in agricultural species), or differences between populations. In a
less formal way, bioinformatics also tries to understand the organizational principles within nucleic acid and
protein sequences, called proteomics.
• 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.

9. DATABASES:
Databases are essential for bioinformatics research and applications. Many databases
exist, covering various information types: for example, DNA and protein sequences,
molecular structures, phenotypes and biodiversity. Databases may contain empirical data
(obtained directly from experiments), predicted data (obtained from analysis), or, most
commonly, both. They may be specific to a particular organism, pathway or molecule of
interest. Alternatively, they can incorporate data compiled from multiple other databases.
These databases vary in their format, access mechanism, and whether they are public or
not.
Some of the most commonly used databases are listed below.
 Used in biological sequence analysis: Genbank, UniProt
 Used in structure analysis: Protein Data Bank (PDB)
 Used in finding Protein Families and Motif Finding: InterPro, Pfam
 Used for Next Generation Sequencing: Sequence Read Archive
 Used in Network Analysis: Metabolic Pathway Databases (KEGG, BioCyc), Interaction
Analysis Databases, Functional Networks
 Used in design of synthetic genetic circuits: GenoCAD.

10. SOFTWARE AND TOOLS OF 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.
Use of the Blast Tool Step By Step
1
1
.
2

11. USE OF THE BLAST TOOL STEP BY STEP:
3.
4.
5.

12. USE OF THE BLAST TOOL STEP BY STEP:
6
7

13. USE OF THE BLAST TOOL STEP BY STEP:
8 9 10

14. USE OF THE BLAST TOOL STEP BY STEP:
11
12
13

15. USE OF THE BLAST TOOL STEP BY STEP:
1
4
15
16
17

16. USE OF THE BLAST TOOL STEP BY STEP:
18
19
20
21

17. USE OF THE BLAST TOOL STEP BY STEP:
22
23

18. USE OF THE BLAST TOOL STEP BY STEP:
24 25
26

19. USE OF THE BLAST TOOL STEP BY STEP:
27

20. USE OF THE BLAST TOOL STEP BY STEP:
28
29

21. USE OF THE BLAST TOOL STEP BY STEP:
30
31

22. THANK YOU