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BIOINFORMATICS. مدرس :جناب آقای دکتر توحید خواه تنظیم : رضا صفری(85233515). DEFINITION. Any use of computer to handle biological information. (Tk ATTWOD,…,intrud to bioinf.99) با این تعریف موضوعاتی چون med imaging-image analysis-AI و neural network جزو بیوانفورماتیک هستند.
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BIOINFORMATICS مدرس :جناب آقای دکتر توحید خواه تنظیم : رضا صفری(85233515)
DEFINITION • Any use of computer to handle biological information. (Tk ATTWOD,…,intrud to bioinf.99)با این تعریف موضوعاتی چون med imaging-image analysis-AIو neural network جزو بیوانفورماتیک هستند. • در عمل این اصطلاح به معنی استفاده از کامپیوتر جهت تعیین محتویات مولکولی عناصر زنده (computational molecular biology). • Fredj Takaya –Institute Pasteur: • The mathematical ,statistical & computing methods that aim to solve biological problems using DNA and amino acid sequences and related information.
Definition… • اصطلاح بیوانفورماتیک نسبتا جدید واز سال 91 وارد منابع گردید. • در دهه 60 حرکتهایی در زمینه ساخت databaseو توسعه الگوریتم ها و کشف بیولوژیکی با کمک sequence analysis انجام شد که molecular evolution گفته میشد. • عناصر تشکیل دهنده bioinformatics : • Biology • Computerscience(computational biology) • Mathematics(biomathematics) • Informatics • Statistics
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.
bioinformatics medical informatics public health informatics algorithms databases infrastructure Tool-users Tool-makers
Why does bioinformatics appear? • انجام تحقیقات در آزمایشگاه وقت گیر و هزینه بر • رشد انفجاری داده های بیولوژیکی طی چند دهه • حجم دادها هر 15 ماه دو برابر می شود. • حجم دادها در یک آزمایشگاه ژنتیک روزانه 100 گیگا بایت است. • داده های حجیم نیاز به وجود database های کامپیوتری تا ذخیره –دسته بندی وایندکس گذاری شده و ابزارهایی بوجود آید تا این داده ها قابل دسترسی آسان و آنالیز باشند. • در ابتدای انقلاب ژنی توجه ویژه معطوف به تولید و حفظ داده ها بمنظور ذخیره اطلاعات بیو لوژیکی (توالی اسید آمینه و نوکلئوتیدها). • پسشرفت های قابل ملاحظه در تکنولوژی کامپیوتر: (CPU,disk storage,internet)
Growth of GenBank Base pairs of DNA (billions) Sequences (millions) 1982 1986 1990 1994 1998 2002 Updated 8-12-04: >40b base pairs Year
genome transcriptome proteome Central dogma of bioinformatics and genomics Central dogma of molecular biology DNA RNA protein
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.
There are three major public DNA databases EMBL GenBank DDBJ Housed at EBI European Bioinformatics Institute Housed at NCBI National Center for Biotechnology Information Housed in Japan
NCBI (natioal center for biotechnologyinformation)www.ncbi.nlm.nih.gov • Entrez: a unique search and retrievalsystem 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.
Entrez integrates… • the scientific literature; • DNA and protein sequence databases; • 3D protein structure data; • population study data sets; • assemblies of complete genomes
Entrez is a search and retrieval system that integrates NCBI databases
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) Page 27
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
Analysis of: Gene expression: • (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.
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 incancer:point mutation,detction methods measure several hundred thousand sites throughout the genom,generate tetrabyte of data per experiment.
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 &function-diff. a.a)
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
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.
Bioinformatics&evolutionary biology • 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.
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)
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.
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.
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
6.Map Viewer: A tool for visualizing whole genome or single chromosomes. Whole genomview: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/
An important aspects of complete genom is distinguish between coding & non-coding region. • The biggest excitement : availability of complete genom seq. for diff. organism.
>100,000 species are represented in GenBank all species 128,a941 viruses 6,137 bacteria 31,262 archaea 2,100 eukaryota 87,147
Human Genome project The greatest achievment of bioinformatics methods.
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
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