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Applying AI to Human Genome

Learn about the basics of DNA, collecting data, and the human genome project. Explore the power of Perl for data extraction and manipulation. Dive into applying AI for exon identification and splice junctions. Join us on this educational journey!

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Applying AI to Human Genome

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  1. Applying AI to Human Genome Part 1 : Collecting data Prof. M. Embrechts Robert Bress Bram Heyns

  2. Overview • Basics of DNA • Collecting the data • Collection : my application • Perl • Goal

  3. Basics of DNA • DNA = polymer of 4 molecules : bases or nucleotides • A = Adenine , C = Cytosine , G = Guanine , T = Thymine • Replication ( copying ) and translation ( reading ) => double helix : AT , GC ( copying ) • 3 letter combination = codon • RNA : U = Uracil in place of T => Transcribing • Protein = polymer composed of 20 amino acids ( reading ) => more complex structure than DNA

  4. Transition DNA RNA Protein

  5. Intron – Exon - Splicejunction • exon 200 characters  intron thousands • 30,000 genes identified out of possible 100,000 • Identification gene patent

  6. Summary • Human : 23 chromosomes • Chromosomes thousands of genes • Gene info : exons , comments : introns • Exons and introns codons • Codon bases

  7. Datacollection • Human Genome Project • NCBI website : http//www.ncbi.nlm.nih.gov • Entrez-Nucleotide.htm • NCBI Sequence Viewer.htm

  8. Datacollection • Human Genome Project • NCBI website : http//www.ncbi.nlm.nih.gov • Entrez-Nucleotide.htm • NCBI Sequence Viewer.htm

  9. Datacollection : my application

  10. Datacollection : my application

  11. Perl Practical Extraction and Report Language POD – files -> web Portability Free – CPAN modules String manipilation Extremely powerfull regex-engine Glue language designed for short and simple tasks, not equal to lack of power or “serious” features Tutorial : http://www.netcat.co.uk/rob/perl/win32perltut.html

  12. Regular Expression – Pattern Matching • Practical Extraction and Report Language • Scan through data and extract useful information • m/PATTERN/ s/PATTERN/REPLACEMENT/ • 1 line Perl = 100 lines C or Java • Complex, but easy

  13. Regex examples • /[KCZ]arl^sa/ • /<I>/(.*?)<\/I>/i • $1,$2,… • i , g , c , … • . , * , + , ? • /([0-9a-zA-Z])+/ or /([\w])+/ • s/us[^a-z]/them/g or s/us\W/them/g • /([acc|act][ttt|ttc|att])/ • TIMTOWTDT

  14. Part 2 : Applying AI • Our choice : evolutionary computing • First part : identify exon part • Second part : identify splicejunctions • Third part : combine previous parts • Hope to reach +90% accuracy

  15. Questions ?

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