Slides for bioinformatics

2. FBW 29-09-2011 Wim Van Criekinge

4. What is Bioinformatics ? Application of information technology to the storage, management and analysis of biological information (Facilitated by the use of computers) Sequence analysis? Molecular modeling (HTX) ? Phylogeny/evolution? Ecology and population studies? Medical informatics? Image Analysis ? Statistics ? AI ? Sterkstroom of zwakstroom ?

5. Promises of genomics and bioinformatics Medicine (Pharma) Genome analysis allows the targeting of genetic diseases The effect of a disease or of a therapeutic on RNA and protein levels can be elucidated Knowledge of protein structure facilitates drug design Understanding of genomic variation allows the tailoring of medical treatment to the individual’s genetic make-up The same techniques can be applied to crop (Agro) and livestock improvement (Animal Health)

6. Bioinformatics: What’s in a name ? Begin 1990’s “Bio-informatics”: Computing Power Genbank (Log) Time (years)

7. Bioinformatics: What’s in a name ? Begin 1990’s “Bio-informatics”: convergence of explosive growth in biotechnology, paralled by the explosive growth in information technology Not new: > 30 years that people use “computers” in biology In silico biology, database biology, ...

8. Time (years)

9. Happy Birthday …

10. PCR + dye termination Suddenly, a flash of insight caused him to pull the car off the road and stop. He awakened his friend dozing in the passenger seat and excitedly explained to her that he had hit upon a solution - not to his original problem, but to one of even greater significance. Kary Mullis had just conceived of a simple method for producing virtually unlimited copies of a specific DNA sequence in a test tube - the polymerase chain reaction (PCR)

11. Math Theoretical Biology Computer Science (Molecular) Biology Informatics Computational Biology Bioinformatics, a scientific discipline … Bioinformatics

12. Math Algorithm Development Theoretical Biology Computer Science AI, Image Analysis structure prediction (HTX) NP Datamining Interface Design Expert Annotation Sequence Analysis (Molecular) Biology Informatics Computational Biology Bioinformatics, a scientific discipline … Bioinformatics

13. Math Algorithm Development Theoretical Biology Computer Science AI, Image Analysis structure prediction (HTX) NP Datamining Interface Design Expert Annotation Sequence Analysis (Molecular) Biology Informatics Computational Biology Bioinformatics, a scientific discipline … Bioinformatics Discovery Informatics – Computational Genomics

14. Doel van de cursus Meer dan een inleiding tot ... het is de bedoeling van de cursus een onderliggend inzicht te verschaffen achter de verschillende technieken. Naast het gebruik van recepten, wat terug te vinden is in delen van de syllabus laat een inzicht in de werking van databanken en de achterliggende algoritmen toe om wisselende interfaces op nieuwe problemen toe te passen.

15. Inhoud Lessen: Bioinformatica don 29-09-2011: 1* Bioinformatics (practicum 8.30-11.00) don 06-10-2011: 2* Biological Databases (practicum 9.00-11.30) don 20-10-2011: 3 Sequence Similarity (Scoring Matrices) don 27-10-2011: 4 Sequence Alignments don 10-11-2011: 5 Database Searching Fasta/Blast don 17-11-2011: 6 Phylogenetics don 24-11-2011: 7 Protein Structure don 01-12-2011: 8 Gene Prediction, Gene Ontologies & HMM don 08-12-2011: 9 ncRNA, Chip Data Analysis, AI don 15-12-2011: 10 Bio- & Cheminformatics in Drug Discovery (inhaalweek) Opgelet: Geen les op don 13-10-2010 en don 3-11-2010

16. Examen Theorie Deel rond een zelf te kiezen publicatie die in verband staat met de cursus Bv Bioinformatics of Computational Biology Drie inzichtsvragen over de cursus (inclusief  !!) Practicum (“open-book”) Viertal oefeningen die meestal het schrijven van een programma veronderstellen Puntenverdeling 50/50

18. Timelin: Magaret Dayhoff …

19. Nexus > FAQ > Bioinformatics Milestones

20. http://www.sciencemag.org/cgi/content/full/291/5507/1195 Printed version in cursus

21. nature the Human genome Setting the stage …

25. Genome Meters Genomes Online Database (GOLD 1.0) http://geta.life.uiuc.edu/~nikos/genomes.html http://www.ebi.ac.uk/research/cgg/genomes.html NCBI http://www.ncbi.nlm.nih.gov/PMGifs/Genomes/bact.html INFOBIOGEN http://www.infobiogen.fr/doc/data/complete_genome.html

26. Genome Size E. coli = 4.2 x 106 Yeast = 18 x 106 Arabidopsis = 80 x 106 C.elegans = 100 x 106 Drosophila = 180 x 106 Human/Rat/Mouse = 3000 x 106 Lily = 300 000 x 106 With ... : 99.9 % To primates: 99% DOGS: Database Of Genome Sizes

28. Biological Research Adapted from John McPherson, OICR

29. And this is just the beginning …. Next Generation Sequencing is here

30. Basics of the “old” technology Clone the DNA. Generate a ladder of labeled (colored) molecules that are different by 1 nucleotide. Separate mixture on some matrix. Detect fluorochrome by laser. Interpret peaks as string of DNA. Strings are 500 to 1,000 letters long 1 machine generates 57,000 nucleotides/run Assemble all strings into a genome.

31. Basics of the “new” technology Get DNA. Attach it to something. Extend and amplify signal with some color scheme. Detect fluorochrome by microscopy. Interpret series of spots as short strings of DNA. Strings are 30-300 letters long Multiple images are interpreted as 0.4 to 1.2 GB/run (1,200,000,000 letters/day). Map or align strings to one or many genome.

32. Next Generation Technologies 454 Emulsion PCR Polymerase Natural Nucleotides 20-100Mb for 5-15k 1% error rate Homopolymers

38. One additional insight ...

39. Read Length is Not As Important For Resequencing Jay Shendure

40. Two Short Read Techologies Illumina GA ABI SOLID

41. Technology Overview: Solexa/Illumina Sequencing

47. ABI Solid Dressman 2003

48. ABI SOLID

49. ABI SOLID

53. Paired End Reads are Important! Known Distance Read 1 Read 2 Repetitive DNA Unique DNA Paired read maps uniquely Single read maps to multiple positions

54. Single Molecule Sequencing Adapted from: Barak Cohen, Washington University, Bio5488 http://tinyurl.com/6zttuq http://tinyurl.com/6k26nh Microscope slide * * * Single DNA molecule Super-cooled TIRF microscope primer dNTP-Cy3 * Helicos Biosciences Corp.

55. IntroducingNXT GNT DXSNextGenerationDiagnostics 18th september 2009 Wim Van Criekinge

56. develop in shortest time frame best assay for most relevant clinical application

59. Dedicated Team & Network

60. Operational: Location

61. Professionalized

62. DXS

63. Content engine

64. Product 1 established

65. Pipeline for n+1

66. NXT

67. Workflow management

68. Bioinformatics

70. Complete genomics

71. Complete genomics

72. Pacific Biosciences: A Third Generation Sequencing Technology Eid et al 2008

73. Pacific Biosciences: A Third Generation Sequencing Technology

74. Nanopore Sequencing

75. NCBI (educational resources)

76. Weblems What ? Web-based problemes (over de huidige les en/of voorbereiding op volgende les) When ? Einde van elke les How ? Oplossingen online via screencasts Practicum Voorbedereiding op het practicum examen ... Niet alle problemen vereisen noodzakelijk programmacode ...

77. Weblems W1.1: To which phyla do the following species belong (a) starfish (b) ginko tree (c) scorpion W1.2: What are the common names for the following species (a) Orycterophus afer (b) Beta vulagaris (c) macrocystis pyrifera W1.3: What species has the smallest known genome ? And is genome size related to number of genes ? W1.4: What are the 5 latest genomes published ? How complete is “coverage” ? W1.5: For approximately 10% of europeans, the painkiller codeine is ineffective because the patients lack the enzyme that converts codeine into the active molecule, morphine. What is the most common mutation that causes this condition ?