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‫‪BIOINFORMATICS‬‬
‫مدرس ‪:‬جناب آقای دکتر توحید خواه‬
‫تنظیم ‪ :‬رضا صفری(‪)85233515‬‬
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DEFINITION
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Any use of computer to handle biological information.
(Tk ATTWOD,…,intrud to bioinf.99) ‫با این تعریف موضوعاتی چون‬
med imaging-image analysis-AI ‫و‬neural network ‫جزو‬
.‫بیوانفورماتیک هستند‬
‫ در عمل این اصطالح به معنی استفاده از کامپیوتر جهت تعیین محتویات‬
.)computational molecular biology( ‫مولکولی عناصر زنده‬
 Fredj Takaya –Institute Pasteur:
 The mathematical ,statistical & computing methods that
aim to solve biological problems using DNA and amino
acid sequences and related information.
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Definition…
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.‫ وارد منابع گردید‬91 ‫اصطالح بیوانفورماتیک نسبتا جدید واز سال‬
‫و توسعه الگوریتم ها و‬database ‫ حرکتهایی در زمینه ساخت‬60 ‫در دهه‬
‫ انجام شد که‬sequence analysis ‫کشف بیولوژیکی با کمک‬
.‫ گفته میشد‬molecular evolution
: bioinformatics ‫عناصر تشکیل دهنده‬
Biology
Computerscience(computational biology)
Mathematics(biomathematics)
Informatics
Statistics
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Bioinformatics vs computational biology.
Bioinformatics is concerned with the information.
Comp.biology is concerned with the hypothesis.
Bioinformatics is also often specified as an applied
subfield of the more general discipline of
biomedical informatics.
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bioinformatics
medical
informatics
Tool-users
public health
informatics
Tool-makers
algorithms
databases
infrastructure
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‫?‪Why does bioinformatics appear‬‬
‫‪ ‬انجام تحقیقات در آزمایشگاه وقت گیر و هزینه بر‬
‫‪ ‬رشد انفجاری داده های بیولوژیکی طی چند دهه‬
‫‪ ‬حجم دادها هر ‪ 15‬ماه دو برابر می شود‪.‬‬
‫‪ ‬حجم دادها در یک آزمایشگاه ژنتیک روزانه ‪ 100‬گیگا بایت است‪.‬‬
‫‪ ‬داده های حجیم نیاز به وجود ‪ database‬های کامپیوتری تا ذخیره –دسته‬
‫بندی وایندکس گذاری شده و ابزارهایی بوجود آید تا این داده ها قابل دسترسی‬
‫آسان و آنالیز باشند‪.‬‬
‫‪ ‬در ابتدای انقالب ژنی توجه ویژه معطوف به تولید و حفظ داده ها بمنظور‬
‫ذخیره اطالعات بیو لوژیکی (توالی اسید آمینه و نوکلئوتیدها)‪.‬‬
‫‪ ‬پسشرفت های قابل مالحظه در تکنولوژی کامپیوتر‪:‬‬
‫(‪)CPU,disk storage,internet‬‬
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Sequences (millions)
Base pairs of DNA (billions)
Growth of GenBank
Updated 8-12-04:
>40b base pairs
1982
1986
1990
1994
Year
1998
2002
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Central dogma of molecular biology
DNA
genome
RNA
transcriptome
protein
proteome
Central dogma of bioinformatics and genomics
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Aims of Bioinformatics
1.Biological database:
A large ,organized body of persistent data , usually
associated with computerized software designed to
update,query,and retrieve components of the data
stored within the system.
Simple database:simple file,some records,same sets of
informations.
Additional requrements: easy access
a method for extractingonly needed
information to answer a specific
qeustion.
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There are three major public DNA databases
EMBL
Housed
at EBI
European
Bioinformatics
Institute
GenBank
DDBJ
Housed
at NCBI
National
Center for
Biotechnology
Information
Housed
in Japan
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List of URL
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NCBI
(natioal center for biotechnology information)
www.ncbi.nlm.nih.gov
 Entrez: a unique search and retrieval system
access to many databases
for exam: Entrez protein DB crosslink to Entrez
Taxonomy DB(finding tax. Inf for the species from
which a prot seq was derived.
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Entrez integrates…
• the scientific literature;
• DNA and protein sequence databases;
• 3D protein structure data;
• population study data sets;
• assemblies of complete genomes
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Entrez is a search and retrieval system
that integrates NCBI databases
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Four ways to access DNA and
protein sequences
[1] Entrez Gene with RefSeq
[2] UniGene
[3] European Bioinformatics Institute (EBI)
and Ensembl (separate from NCBI)
[4] ExPASy Sequence Retrieval System
(separate from NCBI)
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2.Data Analysis:
The information in these DBs is useless until analysed .
Bioinf. Tools can be used to obtain seq. of genes or proteins.
Seq canbe analysed in many ways:
Assembling:
Mapping:
Compare:a comparison of genes within a species or between diff.spp.
can show similarities between protein function or relation
between spp.(use to construct phylogenic trees)
Phylogenetics: understanding the relatioships between diff. kinds of life
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Analysis of:
Gene expression:
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(measuring mRNA level by EST,SAGE,..tech)
noise-prone (developing statistical tools to separate signal
from noise).applies in tumor cells.
Identification of genes that are expressed differentialy in a
affected cell provide a basis for explaining the cause of
illness and highlights potential drug targets.
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Analysis of:
Regulation: complex events starting with
extracellular signal such as a hormone and
leading to increase or decrease in the activity of
one or more proteins.
bioinformatics tech.have been applied to explore
various steps in this process.
Protein expression: protein microarrays,HT MS
Mutations in cancer:point mutation,detction
methods measure several hundred thousand
sites throughout the genom,generate tetrabyte
of data per experiment.
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Prediction of protein structure :
Amino acid seq.(primary structure) can be determined from
the seq of gene that codes for it.
Prediction of secondary,tertiary ,….. Protein structures.
Using of homology to predict gene function:
similar function with similar seq.
Which part of prot. Is important in structure formation&
Interaction with other prot.
Homology modeling
Hemoglobin & leghemoglobin(same structure &functiondiff. a.a)
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Comparative Genomics:
Establishment of the correspondence between
gene(orthology analysis) or other genomic
features.
Gene(pointmutation),
chromosom(duplication,lateraltransfer,inversion,delet….),
whole genome (hybridization,polypeptidasion,…)
RAPID SPECIATION
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3.Evolutionary Biology:
The study of the origin & descent of spp.and their change over time.
New insight to molecular basis of disease.
Investigating the function of homologs of a disease gene.
Homology:two genes sharing a common evolut.history.
Finding evolut.relationships between diff.forms of life.
Closely related orgnisms have similar seq.
Protein Family:proteins that show a significant seq.
Protein Folds:distinct protein building block.
Reconstruct the evolut. Rlationship between two species.
Estimate time of divergence.
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Bioinformatics&evolutionary biology
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Trace the evolution of a large number of organism by
measuring changing in their DNA
Compare entire genomes and the prediction of important
factors
Build complex computational models of populations to
predict the outcome of the system overtime
Track and share information on an increasingly large
number of spp.
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Measuring Biodiversity of an Ecosystem:
Total genomic complement of a particular environment,from
all of the spp. Present.
Collect the spp.names,descriptions,genetic information,status
and size of population,habitant needs,…..
Genetic health of a breeding pool(agriculture)
Endangered population(in silico)
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4.Modeling biological systems:
Computer simulations of cellular subsystems to analyze &
visualize the complex connection of cellular processes.
Artificial life(virtual evolution)attemps to understand
evolutionary processes via comp. simulation of simple
(artificial) life forms.
Protein-protein docking: protein structure by XRC&NMR
Predict p-p interaction only by these 3D shapes.
The most straightforward application of the database is
to predict the function of uncharacterised protein
through their homology to characterised proteins.
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Protein Modeling:
DNA seq encode proteins with specific functions.
In the absence of a protein structure ,by using protein or molecular
modeling researchers try to predict 3D structure.
By using Templates predict
Target
Helpful in proposing and testing biological hypothesis.
Starting point to confirm a structure through XRC & NMR
Increasingly important tool for scientists working to understand normal
and disease-related process in living organisms.
Changig of undesired action of an enzyme.
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5.Genom Mapping:
Serve a scaffold for orienting seq. information.
Past: Manually mapping the genomic region
time-consuming and painstaking process.
Now: by new tec. A number of high quality genom-wide
maps are available.
comp.maps
gene hunting: faster,cheaper,more
practical
By these advances,researcher‘s burden has shifted from
mapping a genom to navigate a vast number of web
sites and DBs
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6.Map Viewer:
A tool for visualizing whole genome or single chromosomes.
Whole genom view:display a schematic for all of an organism‘s
chromosomes.
Map view: show one or more detailed maps for a single ch.
Using Map viewer ,researchers can find answers to question
such as:
Where does a particular gene exist within an organism`s genome?
Which gene are located on a particular chromosome& in what order?
What is the corresponding seq. data for a gene that exist in a particular
chromosome region?
What is the distance between two gene/
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An important aspects of complete genom is distinguish
between coding & non-coding region.
The biggest excitement : availability of complete genom
seq. for diff. organism.
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>100,000 species are represented in GenBank
all species
128,a941
viruses
6,137
bacteria
31,262
archaea
2,100
eukaryota
87,147
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Human Genome project
The greatest achievment of bioinformatics methods.
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A typical scenario
Post-natal genotyping
Assess susceptibility or immunity
From specific disease&pathogens
Early detection of illness
Unique combination of vaccines
Minimising healthcare costs
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Rapid progress of bioinformatics
Advances in the diagnosis,treatment,and
prevention of many genetic disease
Bioinformatics has transformed the biology from
purely lab-based science to an information
science
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