1. Introduction to Bioinformatics 236523/234525
Lecturer: Prof. Yael Mandel-Gutfreund
Teaching Assistance:
Shai Ben-Elazar
Idit kosti
Course web site :

2. What is Bioinformatics?

3. Course Objectives To introduce the bioinfomatics discipline
To make the students familiar with the major biological questions which can be addressed by bioinformatics tools
To introduce the major tools used for sequence and structure analysis and explain in general how they work (limitation etc..)

4. Course Structure and Requirements
Class Structure
2 hours Lecture
1 hour tutorial
2. Home work
Homework assignments will be given every second week
The homework will be done in pairs.
5/5 homework assignments will be submitted
2. A final project will be conducted in pairs
* Project will be presented as a poster –poster day 14.3

5. Grading
20 % Homework assignments
80 % final project

6. Literature list
Gibas, C., Jambeck, P. Developing Bioinformatics Computer Skills. O'Reilly, 2001.
Lesk, A. M. Introduction to Bioinformatics. Oxford University Press, 2002.
Mount, D.W. Bioinformatics: Sequence and Genome Analysis. 2nd ed.,Cold Spring Harbor Laboratory Press, 2004.
Advanced Reading
Jones N.C & Pevzner P.A. An introduction to Bioinformatics algorithms MIT Press, 2004

7. What is Bioinformatics?

8. What is Bioinformatics?
“The field of science in which biology, computer science, and information technology merge to form a single discipline”
Ultimate goal: to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned.

9. Central Paradigm in Molecular Biology
Gene (DNA)
mRNA
Protein
21ST centaury
Genome
Transcriptome
Proteome

10. Watson and Crick DNA model
From DNA to Genome
Watson and Crick DNA model
1955
1960
1965
1970
1975
1980
1985

11. First human genome draft
1990
First genome
Hemophilus Influenzae
1995
Yeast genome
First human genome draft
2000

12. Complete Genomes 2010 2005 Total 1379 294 Eukaryotes 133 39
Bacteria
Archaea

13. 1,000 Genomes Project: Expanding the Map of Human Genetics
Researchers hope the effort will speed up the discovery of many diseases's genetic roots

14. To understand the living cell
25000 genomes… What’s Next ?
The “post-genomics” era
Systems
Biology
Annotation
Comparative
genomics
Functional
genomics
Main Goal:
To understand the living cell

15. To…Understanding living cells
From … genomes
To…Understanding living cells

16. Annotation CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG
CGTGCAAATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA
CTTTGTTACGCGTTTTTGTCATGGCTTTGGTCCCGCTTTGTTC
AGAATGCTTTTAATAAGCGGGGTTACCGGTTTGGTTAGCGAGA
AGAGCCAGTAAAAGACGCAGTGACGGAGATGTCTGATG CAA
TAT GGA CAA TTG GTT TCT TCT CTG AAT
TGAAAAACGTA

17. Annotation Identify the genes within a given sequence of DNA
Identify the sites
Which regulate the gene
Annotation
Predict the function

18. How do we identify a gene in a genome?
A gene is characterized by several features (promoter, ORF…)
some are easier and some harder to detect…

19. promoter TF binding site Transcription Start Site
Ribosome binding Site
ORF=Open Reading Frame
CDS=Coding Sequence
Transcription
Start Site
CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG
CGTGCAAATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA
CTTTGTTACGCGTTTTTGTCATGGCTTTGGTCCCGCTTTGTTC
AGAATGCTTTTAATAAGCGGGGTTACCGGTTTGGTTAGCGAGA
AGAGCCAGTAAAAGACGCAGTGACGGAGATGTCTGATG CAA
TAT GGA CAA TTG GTT TCT TCT CTG AAT
TGAAAAACGTA

20. Using Bioinformatics approaches for Gene hunting
Relative easy in simple organisms (e.g. bacteria)
VERY HARD for higher organism (e.g. humans)

21. Comparative
genomics

22. Perhaps not surprising!!!
How humans
are chimps?
Comparison between the full drafts of the human and chimp genomes
revealed that they differ only by 1.23%

23. So where are we different ??
Human ATAGCGGGGGGATGCGGGCCCTATACCC
Chimp ATAGGGGGGATGCGGGCCCTATACCC
Mouse ATAGCGGGATGCGGCGCTATACCA
Human ATAGCGGGGGGATGCGGGCCCTATACCC
Chimp ATAGGGG--GGATGCGGGCCCTATACCC
Mouse ATAGCG---GGATGCGGCGC-TATACC-A

24. And where are we similar ???
VERY SIMAILAR
Conserved between many organisms
VERY
DIFFERENT

25. Functional
genomics

26. TO BE IS NOT ENOUGH
In any time point a gene can be functional or not

27. From the gene expression pattern we can lean:
What does the gene do ?
When is it needed?
What other genes or proteins interact with it?
…..
What's wrong??

28. Systems
Biology

29. Biological networks
Jeong et al. Nature 411, (2001)

30. What can we learn from a network?
יחסים בין חברים
למי יש מעגל חברים דומה לשלי (הרבה קשתות) או מעגל חברתי שונה משלי (מעט קשתות)

31. What can we learn from Biological Networks
What can we learn about this protein
Is the protein essential for the organism ?
Is it a good drug targets?

32. What of all this will we learn in the course?
The course will concentrate on the bioinformatics
tools and databases which are used to :
Annotate genes,
Compare genes and genomes
Infer the function of the genes and proteins
Analyze the interactions between genes and proteins
ETC….

33. Biological Databases
The different types of data are collected in database
Sequence databases
Structural databases
Databases of Experimental Results
All databases are connected

34. Sequence databases Gene database Genome database
Disease related mutation database
………….

35. UCSC Genome Browser http://genome.ucsc.edu/
Genome Browsers
Easy “walk” through the genome
UCSC Genome Browser

36. Disease related database

37. Sickle Cell Anemia
Due to 1 swapping an A for a T, causing inserted amino acid to be valine instead of glutamine in hemoglobin
Image source:

38. Healthy Individual
>gi| |ref|NM_ | Homo sapiens hemoglobin, beta (HBB), mRNA
ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA
GGAGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC
AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG
CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC
TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT
CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA
CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA
CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT
GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC
>gi| |ref|NP_ | beta globin [Homo sapiens]
MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG
AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN
ALAHKYH

39. Diseased Individual
>gi| |ref|NM_ | Homo sapiens hemoglobin, beta (HBB), mRNA
ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA
GGTGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC
AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG
CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC
TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT
CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA
CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA
CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT
GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC
>gi| |ref|NP_ | beta globin [Homo sapiens]
MVHLTPVEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG
AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN
ALAHKYH

40. Structure Databases
3-dimensional structures of proteins, nucleic acids, molecular complexes etc
3-d data is available due to techniques such as NMR and X-Ray crystallography

42. Databases of Experimental Results
Data such as experimental microarray images- gene expression data
Proteomic data- protein expression data
Metabolic pathways, protein-protein interaction data, regulatory networks
ETC………….

43. PubMed Literature Databases http://www.ncbi.nlm.nih.gov/pubmed/
Service of the National Library of Medicine

44. Putting it all Together
Each Database contains specific information
Like other biological systems also these databases are interrelated

45. PROTEIN DISEASE ASSEMBLED GENOMES GENOMIC DATA ESTs GENES SNPs
PIR
SWISS-PROT
DISEASE
LocusLink
OMIM
OMIA
ASSEMBLED GENOMES
GoldenPath
WormBase
TIGR
MOTIFS
BLOCKS
Pfam
Prosite
GENOMIC DATA
GenBank
DDBJ
EMBL
ESTs
dbEST
unigene
GENES
RefSeq
AllGenes
GDB
SNPs
dbSNP
GENE EXPRESSION
Stanford MGDB
NetAffx
ArrayExpress
PATHWAY
KEGG
COG
STRUCTURE
PDB
MMDB
SCOP
LITERATURE
PubMed