biomedical informatics michael d. kane, ph.d.. the cell is a living machine
Post on 21-Dec-2015
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TRANSCRIPT
Biomedical Informatics
Michael D. Kane, Ph.D.
The Cell is a Living Machine
DNA is Information Storage
“Zipped Files”
Decompression
“Executable Files”
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.
CAGGACCATGGAACTCAGCGTCCTCCTCTTCCTTGCACTCCTCACAGGACTCTTGCTACTCCTGGTTCAGCGCCACCCTAACACCCATGACCGCCTCCCACCAGGGCCCCGCCCTCTGCCCCTTTTGGGAAACCTTCTGCAGATGGATAGAAGAGGCCTACTCAAATCCTTTCTGAGGTTCCGAGAGAAATATGGGGACGTCTTCACGGTACACCTGGGACCGAGGCCCGTGGTCATGCTGTGTGGAGTAGAGGCCATACGGGAGGCCCTTGTGGACAAGGCTGAGGCCTTCTCTGGCCGGGGAAAAATCGCCATGGTCGACCCATTCTTCCGGGGATATGGTGTGATCTTTGCCAATGGAAACCGCTGGAAGGTGCTTCGGCGATTCTCTGTGACCACTATGAGGGACTTCGGGATGGGAAAGCGGAGTGTGGAGGAGCGGATTCAGGAGGAGGCTCAGTGTCTGATAGAGGAGCTTCGGAAATCCAAGGGGGCCCTCATGGACCCCACCTTCCTCTTCCAGTCCATTACCGCCAACATCATCTGCTCCATCGTCTTTGGAAAACGATTCCACTACCAAGATCAAGAGTTCCTGAAGATGCTGAACTTGTTCTACCAGACTTTTTCACTCATCAGCTCTGTATTCGGCCAGCTGTTTGAGCTCTTCTCTGGCTTCTTGAAATACTTTCCTGGGGCACACAGGCAAGTTTACAAAAACCTGCAGGAAATCAATGCTTACATTGGCCACAGTGTGGAGAAGCACCGTGAAACCCTGGACCCCAGCGCCCCCAAGGACCTCATCGACACCTACCTGCTCCACATGGAAAAAGAGAAATCCAACGCACACAGTGAATTCAGCCACCAGAACCTCAACCTCAACACGCTCTCGCTCTTCTTTGCTGGCACTGAGACCACCAGCACCACTCTCCGCTACGGCTTCCTGCTCATGCTCAAATACCCTCATGTTGCAGAGAGAGTCTACAGGGAGATTGAACAGGTGATTGGCCCACATCGCCCTCCAGAGCTTCATGACCGAGCCAAAATGCCATACACAGAGGCAGTCATCTATGAGATTCAGAGATTTTCCGACCTTCTCCCCATGGGTGTGCCCCACATTGTCACCCAACACACCAGCTTCCGAGGGTACATCATCCCCAAGGACACAGAAGTATTTCTCATCCTGAGCACTGCTCTCCATGACCCACACTA
THEREDCAT_HSDKLSD_WASNOTHOTBUT_WKKNASDNKSAOJ.ASDNALKS_WASWET_ASDFLKSDOFIJEIJKNAWDFN_ANDMAD_WERN.JSNDFJN_YETSAD_MNSFDGPOIJD_BUTTHEFOX_SDKMFIDSJIR.JER_GOTWET_JSN.DFOIAMNJNER_ANDATEHIM.
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…
What are the comparative genome sizes of humans and other organisms being studied?
organism estimated sizeestimated
gene number
average gene densitychromo-some
number
Homo sapiens(human)
2900 million bases ~30,000 1 gene per 100,000 bases 46
Rattus norvegicus(rat)
2750 million bases ~30,000 1 gene per 100,000 bases 42
Mus musculus (mouse)
2500 million bases ~30,000 1 gene per 100,000 bases 40
Drosophila melanogaster(fruit fly)
180 million bases 13,600 1 gene per 9,000 bases 8
Arabidopsis thaliana(plant)
125 million bases 25,500 1 gene per 4000 bases 5
Caenorhabditis elegans(roundworm)
97 million bases 19,100 1 gene per 5000 bases 6
Saccharomyces cerevisiae(yeast)
12 million bases 6300 1 gene per 2000 bases 16
Escherichia coli(bacteria)
4.7 million bases 3200 1 gene per 1400 bases 1
H. influenzae (bacteria)
1.8 million bases 1700 1 gene per 1000 bases 1
Genome size does not correlate with evolutionary status, nor is the number of genes proportionate with genome size.
>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
FASTAFileFormat
>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
FASTAFileFormat
FASTA File Format…(note: U = T)
>gi|1234|my name from genetic code in DNAATGATTTGTCACGCTGAGCTC-AAAGCTAACGAGTAA
>gi|1234|my name translated into proteinMICHAEL-KANE*
A alanine P prolineB aspartate Q glutamineC cystine R arginineD aspartate S serineE glutamate T threonineF phenylalanine U selenocysteineG glycine V valineH histidine W tryptophanI isoleucine Y tyrosineK lysine Z glutamineL leucine X anyM methionine “*” translation stopN asparagine “-” gap of indeterminate
length
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.
A G C T
5’-AAACCAGGCCGATAAGGTACTACACGAAAAAAA-3’
dATPdCTPdTTPdGTP
+ddATP32
ddCTP32
ddTTP32
ddGTP32 TTTGGTCCGGCTATTCCATGATGTGCTTTTTTTTTGGTCCGGCTATTCCATGATGTGCTTTTTTT
TGGTCCGGCTATTCCATGATGTGCTTTTTTTGGTCCGGCTATTCCATGATGTGCTTTTTTT
GTCCGGCTATTCCATGATGTGCTTTTTTTTCCGGCTATTCCATGATGTGCTTTTTTT
CCGGCTATTCCATGATGTGCTTTTTTTCGGCTATTCCATGATGTGCTTTTTTT
GGCTATTCCATGATGTGCTTTTTTTGCTATTCCATGATGTGCTTTTTTT
CTATTCCATGATGTGCTTTTTTTTATTCCATGATGTGCTTTTTTT
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)
http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/D/DNAsequencing.html
DNA Sequencing new method)