1. Biomedical Informatics Michael D. Kane, Ph.D.

2. The Cell is a Living Machine

3. DNA is Information Storage

4. “Zipped Files” Decompression “Executable Files”

5. DNA is Double Stranded – One strand is the “coding strand” and the other strand is there to stabilize the DNA sequence when not in use. Double-stranded DNA is very durable in our environment.

6. CAGGACCATGGAACTCAGCGTCCTCCTCTTCCTTGCACTCCTCACAGGACTCTTGCTACT CCTGGTTCAGCGCCACCCTAACACCCATGACCGCCTCCCACCAGGGCCCCGCCCTCTG CCCCTTTTGGGAAACCTTCTGCAGATGGATAGAAGAGGCCTACTCAAATCCTTTCTGAG GTTCCGAGAGAAATATGGGGACGTCTTCACGGTACACCTGGGACCGAGGCCCGTGGTC ATGCTGTGTGGAGTAGAGGCCATACGGGAGGCCCTTGTGGACAAGGCTGAGGCCTTCT CTGGCCGGGGAAAAATCGCCATGGTCGACCCATTCTTCCGGGGATATGGTGTGATCTTT GCCAATGGAAACCGCTGGAAGGTGCTTCGGCGATTCTCTGTGACCACTATGAGGGACTT CGGGATGGGAAAGCGGAGTGTGGAGGAGCGGATTCAGGAGGAGGCTCAGTGTCTGAT AGAGGAGCTTCGGAAATCCAAGGGGGCCCTCATGGACCCCACCTTCCTCTTCCAGTCC ATTACCGCCAACATCATCTGCTCCATCGTCTTTGGAAAACGATTCCACTACCAAGATCAA GAGTTCCTGAAGATGCTGAACTTGTTCTACCAGACTTTTTCACTCATCAGCTCTGTATTCG GCCAGCTGTTTGAGCTCTTCTCTGGCTTCTTGAAATACTTTCCTGGGGCACACAGGCAA GTTTACAAAAACCTGCAGGAAATCAATGCTTACATTGGCCACAGTGTGGAGAAGCACCG TGAAACCCTGGACCCCAGCGCCCCCAAGGACCTCATCGACACCTACCTGCTCCACATG GAAAAAGAGAAATCCAACGCACACAGTGAATTCAGCCACCAGAACCTCAACCTCAACA CGCTCTCGCTCTTCTTTGCTGGCACTGAGACCACCAGCACCACTCTCCGCTACGGCTTC CTGCTCATGCTCAAATACCCTCATGTTGCAGAGAGAGTCTACAGGGAGATTGAACAGGT GATTGGCCCACATCGCCCTCCAGAGCTTCATGACCGAGCCAAAATGCCATACACAGAGG CAGTCATCTATGAGATTCAGAGATTTTCCGACCTTCTCCCCATGGGTGTGCCCCACATTG TCACCCAACACACCAGCTTCCGAGGGTACATCATCCCCAAGGACACAGAAGTATTTCTC ATCCTGAGCACTGCTCTCCATGACCCACACTA

7. THEREDCAT_HSDKLSD_WASNOTHOTBUT_WKKNASDN KSAOJ.ASDNALKS_WASWET_ASDFLKSDOFIJEIJKNAW DFN_ANDMAD_WERN.JSNDFJN_YETSAD_MNSFDGPOIJ D_BUTTHEFOX_SDKMFIDSJIR.JER_GOTWET_JSN.DFOI AMNJNER_ANDATEHIM.

8. Start with a thin 2 x 4 lego block… Add a 2 x 2 lego block… Add a 2 x 3 lego block… Add a 2 x 4 lego block…

10. What are the comparative genome sizes of humans and other organisms being studied? organismestimated size estimated gene number average gene density chromo -some number Homo sapiens (human) 2900 million bases~30,0001 gene per 100,000 bases46 Rattus norvegicus (rat) 2750 million bases~30,0001 gene per 100,000 bases42 Mus musculus (mouse) 2500 million bases~30,0001 gene per 100,000 bases40 Drosophila melanogaster (fruit fly) 180 million bases13,6001 gene per 9,000 bases8 Arabidopsis thaliana (plant) 125 million bases25,5001 gene per 4000 bases5 Caenorhabditis elegans (roundworm) 97 million bases19,1001 gene per 5000 bases6 Saccharomyces cerevisiae (yeast) 12 million bases63001 gene per 2000 bases16 Escherichia coli (bacteria) 4.7 million bases32001 gene per 1400 bases1 H. influenzae (bacteria) 1.8 million bases17001 gene per 1000 bases1 Genome size does not correlate with evolutionary status, nor is the number of genes proportionate with genome size.

11. >gi|1924939|emb|X98411.1|HSMYOSIE Homo sapiens partial mRNA for myosin-IF CAGGAGAAGCTGACCAGCCGCAAGATGGACAGCCGCTGGGGCGGGCGCAGCGAGTCCATCAATGTGACCC TCAACGTGGAGCAGGCAGCCTACACCCGTGATGCCCTGGCCAAGGGGCTCTATGCCCGCCTCTTCGACTT CCTCGTGGAGGCCATCAACCGTGCTATGCAGAAACCCCAGGAAGAGTACAGCATCGGTGTGCTGGACATT TACGGCTTCGAGATCTTCCAGAAAAATGGCTTCGAGCAGTTTTGCATCAACTTCGTCAATGAGAAGCTGC AGCAAATCTTTATCGAACTTACCCTGAAGGCCGAGCAGGAGGAGTATGTGCAGGAAGGCATCCGCTGGAC TCCAATCCAGTACTTCAACAACAAGGTCGTCTGTGACCTCATCGAAAACAAGCTGAGCCCCCCAGGCATC ATGAGCGTCTTGGACGACGTGTGCGCCACCATGCACGCCACGGGCGGGGGAGCAGACCAGACACTGCTGC AGAAGCTGCAGGCGGCTGTGGGGACCCACGAGCATTTCAACAGCTGGAGCGCCGGCTTCGTCATCCACCA CTACGCTGGCAAGGTCTCCTACGACGTCAGCGGCTTCTGCGAGAGGAACCGAGACGTTCTCTTCTCCGAC CTCATAGAGCTGATGCAGTCCAGTGACCAGGCCTTCCTCCGGATGCTCTTCCCCGAGAAGCTGGATGGAG ACAAGAAGGGGCGCCCCAGCACCGCCGGCTCCAAGATCAAGAAACAAGCCAACGACCTGGTGGCCACACT GATGAGGTGCACACCCCACTACATCCGCTGCATCAAACCCAACGAGACCAAGCACGCCCGAGACTGGGAG GAGAACAGAGTCCAGCACCAGGTGGAATACCTGGGCCTGAAGGAAAACATCAGGGTGCGCAGAGCCGGCT TCGCCTACCGCCGCCAGTTCGCCAAATTCCTGCAGAGGTATGCCATTCTGACCCCCGAGACGTGGCCGCG GTGGCGTGGGGACGAACGCCAGGGCGTCCAGCACCTGCTTCGGGCGGTCAACATGGAGCCCGACCAGTAC CAGATGGGGAGCACCAAGGTCTTTGTCAAGAACCCAGAGTCGCTTTTCCTCCTGGAGGAGGTGCGAGAGC GAAAGTTCGATGGCTTTGCCCGAACCATCCAGAAGGCCTGGCGGCGCCACGTGGCTGTCCGGAAGTACGA GGAGATGCGGGAGGAAGCTTCCAACATCCTGCTGAACAAGAAGGAGCGGAGGCGCAACAGCATCAATCGG AACTTCGTCGGGGACTACCTGGGGCTGGAGGAGCGGCCCGAGCTGCGTCAGTTCCTGGGCAAGAAGGAGC GGGTGGACTTCGCCGATTCGGTCACCAAGTACGACCGCCGCTTCAAGCCCATCAAGCGGGACTTGATCCT GACGCCCAAGTGTGTGTATGTGATTGGGCGAGAGAAGATGAAGAAGGGACCTGAGAAAGGTCCAGTGTGT GAAATCTTGAAGAAGAAATTGGACATCCAGGCTCTGCGGGGGGTCTCCCTCAGCACGCGACAGGACGACT TCTTCATCCTCCAAGAGGATGCCGCCGACAGCTTCCTGGAGAGCGTCTTCAAGACCGAGTTTGTCAGCCT TCTGTGCAAGCGCTTCGAGGAGGCGACGCGGAGGCCCCTGCCCCTCACCTTCAGCGACACACTACAGTTT CGGGTGAAGAAGGAGGGCTGGGGCGGTGGCGGCACCCGCAGCGTCACCTTCTCCCGCGGCTTCGGCGACT TGGCAGTGCTCAAGGTTGGCGGTCGGACCCTCACGGTCAGCGTGGGCGATGGGCTGCCCAAGAACTCCAA GCCTACCGGAAAGGGATTGGCCAAGGGTAAACCTCGGAGGTCGTCCCAAGCCCCTACCCGGGCGGCCCCT GGCGCCCCCCAAGGCATGGATCGAAATGGGGCCCCCCTCTGCCCACAGGGGGGGGCCCCCTGCCCCCTGG AGAAATTCATTTGGCCCAGGGGGCACCCACAGGCCTCCCCGGCCCTCCGTCCACATCCCTGGGATGCCAG CAGACGACCCCGGGCACGTCCGCCCTCAGAGCACAACACAGAATTCCTCAACGTGCCTGACCAGGGGATG GCCGGCATGCAGAGGAAGCGCAGCGTGGGGCAACGGCCAGTGCCTGTGGGCCGACCCAAGCCCCAGCCTC GGACACATGGTCCCAGGTGCCGGGCCCTATACCAGTACGTGGGCCAAGATGTGGACGAGCTGAGCTTCAA CGTGAACGAGGTCATTGAGATCCTCATGGAAGATCCCTCGGGCTGGTGGAAGGGCCGGCTTCACGGCCAG GAGGGCCTTTTCCCAGGAAACTACGTGGAGAAGATCTGAGCTGGGCCCTGGGATACTGCCTTCTCTTTCG CCCGCCTATCTGCCTGCCGGCCTGGTGGGGAGCCAGGCCCTGCCAATGAAAGCCTCGTTTACCTGGGCTG CAATAGCCTAAAAGTCCAATCCTTTGGCCTCCAGTCCTTGCCCAGGCCCTGGGTCACCAGGTCACTGGTG CAGCCCCCGCCCCTGGGCCCTGGTTTTCCTCCAACATCACACCTGCTGCCCATTGTCCAAAACTGTGTGT GTCAAAGGGGACTAACAGCAGAATTTACCTCCCAACTGCCATGTGATTAAGAAATGGGTCTTGAGTCCTG TGCTGTTGGCAAAGTTCCAGGCACAGTTGGGGAGGGGGGGCCGGAATCCGC FASTA File Format

12. >gi|1924939|emb|X98411.1|HSMYOSIE Homo sapiens partial mRNA for myosin-IF CAGGAGAAGCTGACCAGCCGCAAGATGGACAGCCGCTGGGGCGGGCGCAGCGAGTCCATCAATGTGACCC TCAACGTGGAGCAGGCAGCCTACACCCGTGATGCCCTGGCCAAGGGGCTCTATGCCCGCCTCTTCGACTT CCTCGTGGAGGCCATCAACCGTGCTATGCAGAAACCCCAGGAAGAGTACAGCATCGGTGTGCTGGACATT TACGGCTTCGAGATCTTCCAGAAAAATGGCTTCGAGCAGTTTTGCATCAACTTCGTCAATGAGAAGCTGC AGCAAATCTTTATCGAACTTACCCTGAAGGCCGAGCAGGAGGAGTATGTGCAGGAAGGCATCCGCTGGAC TCCAATCCAGTACTTCAACAACAAGGTCGTCTGTGACCTCATCGAAAACAAGCTGAGCCCCCCAGGCATC ATGAGCGTCTTGGACGACGTGTGCGCCACCATGCACGCCACGGGCGGGGGAGCAGACCAGACACTGCTGC AGAAGCTGCAGGCGGCTGTGGGGACCCACGAGCATTTCAACAGCTGGAGCGCCGGCTTCGTCATCCACCA CTACGCTGGCAAGGTCTCCTACGACGTCAGCGGCTTCTGCGAGAGGAACCGAGACGTTCTCTTCTCCGAC CTCATAGAGCTGATGCAGTCCAGTGACCAGGCCTTCCTCCGGATGCTCTTCCCCGAGAAGCTGGATGGAG ACAAGAAGGGGCGCCCCAGCACCGCCGGCTCCAAGATCAAGAAACAAGCCAACGACCTGGTGGCCACACT GATGAGGTGCACACCCCACTACATCCGCTGCATCAAACCCAACGAGACCAAGCACGCCCGAGACTGGGAG GAGAACAGAGTCCAGCACCAGGTGGAATACCTGGGCCTGAAGGAAAACATCAGGGTGCGCAGAGCCGGCT TCGCCTACCGCCGCCAGTTCGCCAAATTCCTGCAGAGGTATGCCATTCTGACCCCCGAGACGTGGCCGCG GTGGCGTGGGGACGAACGCCAGGGCGTCCAGCACCTGCTTCGGGCGGTCAACATGGAGCCCGACCAGTAC CAGATGGGGAGCACCAAGGTCTTTGTCAAGAACCCAGAGTCGCTTTTCCTCCTGGAGGAGGTGCGAGAGC GAAAGTTCGATGGCTTTGCCCGAACCATCCAGAAGGCCTGGCGGCGCCACGTGGCTGTCCGGAAGTACGA GGAGATGCGGGAGGAAGCTTCCAACATCCTGCTGAACAAGAAGGAGCGGAGGCGCAACAGCATCAATCGG AACTTCGTCGGGGACTACCTGGGGCTGGAGGAGCGGCCCGAGCTGCGTCAGTTCCTGGGCAAGAAGGAGC GGGTGGACTTCGCCGATTCGGTCACCAAGTACGACCGCCGCTTCAAGCCCATCAAGCGGGACTTGATCCT GACGCCCAAGTGTGTGTATGTGATTGGGCGAGAGAAGATGAAGAAGGGACCTGAGAAAGGTCCAGTGTGT GAAATCTTGAAGAAGAAATTGGACATCCAGGCTCTGCGGGGGGTCTCCCTCAGCACGCGACAGGACGACT TCTTCATCCTCCAAGAGGATGCCGCCGACAGCTTCCTGGAGAGCGTCTTCAAGACCGAGTTTGTCAGCCT TCTGTGCAAGCGCTTCGAGGAGGCGACGCGGAGGCCCCTGCCCCTCACCTTCAGCGACACACTACAGTTT CGGGTGAAGAAGGAGGGCTGGGGCGGTGGCGGCACCCGCAGCGTCACCTTCTCCCGCGGCTTCGGCGACT TGGCAGTGCTCAAGGTTGGCGGTCGGACCCTCACGGTCAGCGTGGGCGATGGGCTGCCCAAGAACTCCAA GCCTACCGGAAAGGGATTGGCCAAGGGTAAACCTCGGAGGTCGTCCCAAGCCCCTACCCGGGCGGCCCCT GGCGCCCCCCAAGGCATGGATCGAAATGGGGCCCCCCTCTGCCCACAGGGGGGGGCCCCCTGCCCCCTGG AGAAATTCATTTGGCCCAGGGGGCACCCACAGGCCTCCCCGGCCCTCCGTCCACATCCCTGGGATGCCAG CAGACGACCCCGGGCACGTCCGCCCTCAGAGCACAACACAGAATTCCTCAACGTGCCTGACCAGGGGATG GCCGGCATGCAGAGGAAGCGCAGCGTGGGGCAACGGCCAGTGCCTGTGGGCCGACCCAAGCCCCAGCCTC GGACACATGGTCCCAGGTGCCGGGCCCTATACCAGTACGTGGGCCAAGATGTGGACGAGCTGAGCTTCAA CGTGAACGAGGTCATTGAGATCCTCATGGAAGATCCCTCGGGCTGGTGGAAGGGCCGGCTTCACGGCCAG GAGGGCCTTTTCCCAGGAAACTACGTGGAGAAGATCTGAGCTGGGCCCTGGGATACTGCCTTCTCTTTCG CCCGCCTATCTGCCTGCCGGCCTGGTGGGGAGCCAGGCCCTGCCAATGAAAGCCTCGTTTACCTGGGCTG CAATAGCCTAAAAGTCCAATCCTTTGGCCTCCAGTCCTTGCCCAGGCCCTGGGTCACCAGGTCACTGGTG CAGCCCCCGCCCCTGGGCCCTGGTTTTCCTCCAACATCACACCTGCTGCCCATTGTCCAAAACTGTGTGT GTCAAAGGGGACTAACAGCAGAATTTACCTCCCAACTGCCATGTGATTAAGAAATGGGTCTTGAGTCCTG TGCTGTTGGCAAAGTTCCAGGCACAGTTGGGGAGGGGGGGCCGGAATCCGC FASTA File Format

13. FASTA File Format…(note: U = T) >gi|1234|my name from genetic code in DNA ATGATTTGTCACGCTGAGCTC-AAAGCT AACGAGTAA >gi|1234|my name translated into protein MICHAEL-KANE* A  alanine P  proline B  aspartateQ  glutamine C  cystine R  arginine D  aspartate S  serine E  glutamate T  threonine F  phenylalanine U  selenocysteine G  glycine V  valine H  histidine W  tryptophan I  isoleucine Y  tyrosine K  lysine Z  glutamine L  leucine X  any M  methionine “*”  translation stop N  asparagine “-”  gap of indeterminate length

14. Where do we get DNA sequence information? DNA Sequencing Methods -conversion of biological/bioanalytical data into sequence information There are automated, high-throughput sequencing centers that COMPLETELY automate (robotics and information systems) DNA sequencing, preliminary identification and publishing.

15. A G C T 5’-AAACCAGGCCGATAAGGTACTACACGAAAAAAA-3’ dATP dCTP dTTP dGTP + ddATP 32 ddCTP 32 ddTTP 32 ddGTP 32 TTTGGTCCGGCTATTCCATGATGTGCTTTTTTT TTGGTCCGGCTATTCCATGATGTGCTTTTTTT TGGTCCGGCTATTCCATGATGTGCTTTTTTT GGTCCGGCTATTCCATGATGTGCTTTTTTT GTCCGGCTATTCCATGATGTGCTTTTTTT TCCGGCTATTCCATGATGTGCTTTTTTT CCGGCTATTCCATGATGTGCTTTTTTT CGGCTATTCCATGATGTGCTTTTTTT GGCTATTCCATGATGTGCTTTTTTT GCTATTCCATGATGTGCTTTTTTT CTATTCCATGATGTGCTTTTTTT TATTCCATGATGTGCTTTTTTT ATTCCATGATGTGCTTTTTTT Step 1. Extend complementary sequence using “free” nucleotides with limiting amounts of radioactive “terminating” nucleotides. Step 2. Run product out on a electrophoresis gel. Step 3. Place gel against radiographic film, develop. TTTTTTT AAACCAGGCCGATAAGGTACTACACGAAAAA | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | DNA Sequencing (old method)

16. http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/D/DNAsequencing.html DNA Sequencing new method)