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M. Alroy Mascrenghe MBCS, MIEEE, MIT

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Presentation on theme: "M. Alroy Mascrenghe MBCS, MIEEE, MIT "— Presentation transcript:

1 How Bioinformatics can change your life Basic Concepts of Bioinformatics
M. Alroy Mascrenghe MBCS, MIEEE, MIT A lecture given for the BCS Wolerhampton Branch at the University of Wolverhampton

2 TOC Introduction Basic concepts in Molecular biology
Bioinformatics techniques Areas in bioinformatics Applications Related Computer Technology Conference in Glasgow Acknowledgements Reference M.Alroy Mascrenghe

3 Introduction…… M.Alroy Mascrenghe

4 2000 A Major event happened that was to change the course of human history It was a joint British and American effort nothing to do with IRAQ! It was a race – who will complete first Race Test – not whether they have taken drugs but whether they can produce them! Human genome was sequenced M.Alroy Mascrenghe

5 A Situ…somewhere in the near future
A virus –not ‘I love you’ virus- creates an epidemic Geneticists and bioinformaticians role on their sleeves Genetic material of the virus is compared with the existing base of known genetic material of other viruses As the characteristics of the other viruses are known From genetic material computer programs will derive the proteins necessary for the survival of the virus When the protein (sequence and structure) is known then medicines can be designed M.Alroy Mascrenghe

6 What is The marriage between computer science and molecular biology
The algorithm and techniques of computer science are being used to solve the problems faced by molecular biologists ‘Information technology applied to the management and analysis of biological data’ Storage and Analysis are two of the important functions – bioinformaticians build tools for each M.Alroy Mascrenghe

7 Chemistry Biology Computer Science Statistics Bioinformatics
M.Alroy Mascrenghe

8 What is.. This is the age of the Information Technology
However storing info is nothing new Information to the volume of Britannica Encyclopedia is stored in each of our cells ‘Bioinformatics tries to determine what info is biologically important’ M.Alroy Mascrenghe

9 Basics of Molecular Biology…. M.Alroy Mascrenghe

10 DNA & Genes DNA is where the genetic information is stored
Blonde hair and blue eyes are inherited by this Gene - The basic unit of heredity There are genes for characteristics i.e. a gene for blond hair etc Genes contain the information as a sequence of nucleotides Genes are abstract concepts – like longitude and latitudes in the sense that you cannot see them separately Genes are made up of nucleotides M.Alroy Mascrenghe

11 M.Alroy Mascrenghe

12 Nucleotide (nt) Each nt I made up of
Sugar Phospate group Base The base it (nt) contains makes the only difference between one nt and the other There are 4 different bases G(uanine),A(denine),T(hymine),C(ytosine) The information is in the order of nucleotide and the order is the info Genes can be many thousands of nt long The complete set of genetic instructions is called genomes M.Alroy Mascrenghe

13 Chromosomes DNA strings make chromosomes Analogy Letters - nt
Sentences – genes Individual volumes of Britannica encyclopedia – chromosomes All voles together - Genome M.Alroy Mascrenghe

14 Double Helix The DNA is a double helix
Each strand has complementary information Each particular base in one strand is bonded with another particular base in the next strand G - C A - T For example - AATGC one strand TTACG other strand M.Alroy Mascrenghe

15 Proteins Proteins are very important biological feature
Amino Acids make up the proteins 20 different amino acids are there The function of a protein is dependant on the order of the amino acids M.Alroy Mascrenghe

16 Proteins… The information required to make aa is stored in DNA
DNA sequence determines amino acid sequence Amino Acid sequence determines protein structure Protein structure determines protein function A Substance called RNA is used to carry the Info stored in the DNA that in turn is used to make proteins Storage - DNA Information Transfer – RNA RNA is the message boy! M.Alroy Mascrenghe

17 Central dogma DNA transcription RNA Translation Protein
RNA Polymerase Ribosomes M.Alroy Mascrenghe

18 M.Alroy Mascrenghe

19 Proteins….. Since there are 20 amino acids to translate one nt cannot correspond to one aa, neither can it correspond as twos So in triplet codes – codon – protein information is carried The codons that do not correspond to a protein are stop codons – UAA, UAG, UGA (RNA has U instead of T) Some codons are used as start codons - AUG as well as to code methionine M.Alroy Mascrenghe

20 Protein Structure Shows a wide variety as opposed to the DNA whose structure is uniform X-ray crystallography or Nuclear Magnetic Resonance (NMR) is used to figure out the structure Structure is related to the function or rather structure determines the function Although proteins are created as a linear structure of aa chain they fold into 3 d structure. If you stretch them and leave them they will go back to this structure – this is the native structure of a protein Only in the native structure the proteins functions well Even after the translation is over protein goes through some changes to its structure M.Alroy Mascrenghe

21 Gene Expression Gene Expression – the process of Transcripting a DNA and translating a RNA to make protein Where do the genes begin in a chromosome? How does the RNA identify the beginning of a gene to make a protein A single nt cannot be taken to point out the beginning of a gene as they occur frequently But a particular combination of a nucleotide can be Promoter sequences – the order of nt which mark the beginning of a gene M.Alroy Mascrenghe

22 Bioinformatics Techniques…..
M.Alroy Mascrenghe

23 Prediction and Pattern Recognition
The two main areas of bioinformatics are Pattern recognition ‘A particular sequence or structure has been seen before’ and that a particular characteristic can be associated with it Prediction From a sequence (what we know) we can predict the structure and function (what we don’t know) M.Alroy Mascrenghe

24 Dot plots…. Simple way of evaluating similarity between two sequences
In a graph one sequence is on one side the next on the other side Where there are matches between the two sequences the graph is marked M.Alroy Mascrenghe

25 M.Alroy Mascrenghe

26 Alignments A match for similarity between the characters of two or more sequences Eg. TTACTATA TAGATA There are so many ways to align the above two sequences 1. 2. 3. So which one do we choose and on what basis? Solution is to Provide a match score and mismatch score M.Alroy Mascrenghe

27 Gaps Introduce gaps and a penalty score for gaps
TTACTATA T_A_GATA In gap scores a single indel which is two characters long is preferred to two indels which are each one character long However not all gaps are bad TTGCAATCT CAA How do we align? ---CAA--- These gaps are not biologically significant Semi Global Alignments M.Alroy Mascrenghe

28 Scoring Matrix For DNA/protein sequence alignment we create a matrix
If A and A score is 1 If A and T score is -5 If A and C score is -1 M.Alroy Mascrenghe

29 Dynamic Programming As the length of the query sequences increase and the difference of length between the two sequence also increases –more gaps has to be inserted in various places We cannot perform an exhaustive search Combinatorial explosion occurs – too much combinations to search for Dynamic programming is a way of using heuristics to search in the most promising path M.Alroy Mascrenghe

30 Databases Sequence info is stored in databases
So that they can be manipulated easily The db (next slide) are located at diff places They exchange info on a daily basis so that they are up-to-date and are in sync Primary db – sequence data M.Alroy Mascrenghe

31 Major Primary DB Nucleic Acid Protein EMBL (Europe) PIR -
Protein Information Resource GenBank (USA) MIPS DDBJ (Japan) SWISS-PROT University of Geneva, now with EBI TrEMBL A supplement to SWISS-PROT NRL-3D

32 Composite DB As there are many db which one to search? Some are good in some aspects and weak in others? Composite db is the answer – which has several db for its base data Search on these db is indexed and streamlined so that the same stored sequence is not searched twice in different db M.Alroy Mascrenghe

33 Composite DB OWL has these as their primary db
SWISS PROT (top priority) PIR GenBank NRL-3D M.Alroy Mascrenghe

34 Secondary db Store secondary structure info or results of searches of the primary db Compo DB Primary Source PROSITE SWISS-PROT PRINTS OWL M.Alroy Mascrenghe

35 Database Searches We have sequenced and identified genes. So we know what they do The sequences are stored in databases So if we find a new gene in the human genome we compare it with the already found genes which are stored in the databases. Since there are large number of databases we cannot do sequence alignment for each and every sequence So heuristics must be used again. M.Alroy Mascrenghe

36 Areas in Bioinformatics…
M.Alroy Mascrenghe

37 Genomics Because of the multicellular structure, each cell type does gene expression in a different way –although each cell has the same content as far as the genetic i.e. All the information for a liver cell to be a liver cell is also present on nose cell, so gene expression is the only thing that differentiates M.Alroy Mascrenghe

38 Genomics - Finding Genes
Gene in sequence data – needle in a haystack However as the needle is different from the haystack genes are not diff from the rest of the sequence data Is whole array of nt we try to find and border mark a set o nt as a gene This is one of the challenges of bioinformatics Neural networks and dynamic programming are being employed M.Alroy Mascrenghe

39 Organism Genome Size (Mb) Gene Number Web Site Yeast 13.5 6,241
bp * 1,000,000 Gene Number Web Site Yeast 13.5 6,241 Fruit Flies 180 13,601 Homo Sapiens 3,000 45,000

40 Proteomics Proteome is the sum total of an organisms proteins
More difficult than genomics Simple chemical makeup complex Can duplicate can’t We are entering into the ‘post genome era’ Meaning much has been done with the Genes – not that it’s a over M.Alroy Mascrenghe

41 Proteomics….. The relationship between the RNA and the protein it codes are usually very different After translation proteins do change So aa sequence do not tell anything about the post translation changes Proteins are not active until they are combined into a larger complex or moved to a relevant location inside or outside the cell So aa only hint in these things Also proteins must be handled more carefully in labs as they tend to change when in touch with an inappropriate material M.Alroy Mascrenghe

42 Protein Structure Prediction
Is one of the biggest challenges of bioinformatics and esp. biochemistry No algorithm is there now to consistently predict the structure of proteins M.Alroy Mascrenghe

43 Structure Prediction methods
Comparative Modeling Target proteins structure is compared with related proteins Proteins with similar sequences are searched for structures M.Alroy Mascrenghe

44 Phylogenetics The taxonomical system reflects evolutionary relationships Phylogenetics trees are things which reflect the evolutionary relationship thru a picture/graph Rooted trees where there is only one ancestor Un rooted trees just showing the relationship Phylogenetic tree reconstruction algorithms are also an area of research M.Alroy Mascrenghe

45 Applications…. M.Alroy Mascrenghe

46 Medical Implications BioWeapons (??) Pharmacogenomics
Not all drugs work on all patients, some good drugs cause death in some patients So by doing a gene analysis before the treatment the offensive drugs can be avoided Also drugs which cause death to most can be used on a minority to whose genes that drug is well suited – volunteers wanted! Customized treatment Gene Therapy Replace or supply the defective or missing gene E.g: Insulin and Factor VIII or Haemophilia BioWeapons (??) M.Alroy Mascrenghe

47 Diagnosis of Disease Diagnosis of disease
Identification of genes which cause the disease will help detect disease at early stage e.g. Huntington disease - Symptoms – uncontrollable dance like movements, mental disturbance, personality changes and intellectual impairment Death in years The gene responsible for the disease has been identified Contains excessively repeated sections of CAG So once analyzed the couple can be counseled M.Alroy Mascrenghe

48 Drug Design Can go up to 15yrs and $700million
One of the goals of bioinformatics is to reduce the time and cost involved with it. The process Discovery Computational methods can improves this Testing M.Alroy Mascrenghe

49 Discovery Target identification
Identifying the molecule on which the germs relies for its survival Then we develop another molecule i.e. drug which will bind to the target So the germ will not be able to interact with the target. Proteins are the most common targets M.Alroy Mascrenghe

50 Discovery… For example HIV produces HIV protease which is a protein and which in turn eat other proteins This HIV protease has an active site where it binds to other molecules So HIV drug will go and bind with that active site Easily said than done! M.Alroy Mascrenghe

51 Discovery… Lead compounds are the molecules that go and bind to the target protein’s active site Traditionally this has been a trial and error method Now this is being moved into the realm of computers M.Alroy Mascrenghe

52 Related Computer Technology………….
M.Alroy Mascrenghe

53 PERL Perl is commonly used for bioinformatics calculations as its ability to manipulate character symbols The default CGI language It started out as a scripting language but has become a fully fledged language IT has everything now, even web service support M.Alroy Mascrenghe

54 The place of XML & Web Services
Various markup languages are being created – Gene Markup language etc to represent sequence/gene data Web Services – program to program interaction, making the web application centric as opposed to human centric So this has to platform language independent Protocols like SOAP help in this regard In bioinformatics various databases are being used, different platforms, languages etc So web services helps achieve platform independence and program interaction Since sequence data bases are in various formats, platforms SOAP also helps in this regards M.Alroy Mascrenghe

55 The place of GRID GRID - new kid on the block
Using many computers to fulfill a single computational tasks Bioinformatics is the ideal platform as it has to deal with a large amount of data in alignment and searches E-science initiative in the UK ORACLE 10g – the worlds first GRID database M.Alroy Mascrenghe

56 Data bases and Mining Lot of the sequence databases are available publicly As there is a DB involved various data mining techniques are used to pull the data out As there is a lot of literature – articles etc – on this area a data mining on the literature – not on the sequence data has also become a PhD topic for many M.Alroy Mascrenghe

57 European Molecular Biology Network (EMBnet)
A central system for sharing, training and centralizing up to date bio info Some of the EMBnet sites are: SQENET UCL EBI – European Bioinformatics Institute M.Alroy Mascrenghe

58 References Prof David Gilbert’s Site
Dan E. Krane and Michael L. Raymer Basic Concepts of Bioinformatics Arthur M Lesk Intro to Bioinformatics T.K. Attwood & D. J. Parry-Smith The genetic Revolution Dr Patrick Dixon Prof David Gilbert’s Site M.Alroy Mascrenghe

59 Thank You! M.Alroy Mascrenghe


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