2. Pattern Recognition and Gene Finding
Welcome to Advanced Molecular Genetics, Bioinformatics, and Computational Genomics
Pattern Recognition and Gene Finding

9. Pattern Recognition and Gene Finding
Welcome to Advanced Molecular Genetics, Bioinformatics, and Computational Genomics
Pattern Recognition and Gene Finding
(Through software tools)
An alternative

10. Lives of the Scientist

11. World’s Greatest Explorer

14. World’s Greatest Musicologist
Expect = 4e-98

15. World’s Greatest Microbiologist

16. 3337901 TACACCAGAT ATTGATGTCG TTTTGATGGA TGTAATGATG CCAGAAATGG
ACGGTTACGA AACAACAAGC TTAATCCGCC AAAACGAGCA ATTTAAATCT
TTGCCGATTA TTGCACTGAC AGCTAAAGCC ATGCAAGGCG ATCGCGAGAA
GTGTATTGAA GCGGGTGCAT CAGACTACAT CACCAAACCC GTAGATACTG
AACAACTGCT TTCACTCTTG CGTGTTTGGC TATACCGTTA ATTGGGGCAG
GGGGCAGGGA GCCGTTGCAA CTATTTCAAC CCTAATAGGG ATTTTGATGA
ATTGCAATTC CTCCTTCCTC TGGCTCTGCC ACCGTTCAGC AACTTGGTTT
CAATCCCTGA TAGGGATTTT GATGAATTGC AATATATTAT TTCACAACTG
GTAAAAACGC TAAAGGTTTA GTTTCAATCC CTGATAGGGA TTTTGATGAA
TTGCAATGTT AAACTGGTCT GCTTTGCCGA TACCCAAATA TTGCTAGGTT
TCAATCCCTG ATAGGGATTT TGATGAATTG CAATGAAATC AGAAACATCT
TTGATTTTTT TGACCATGTT TCAATCCCTG ATAGGGATTT TGATGAATTG
CAATTTTTTG GGGAAGAGGT AATCTGAAAC AGAATTTAGT ATTTGTTTCA
ATCCCTGATA GGGATTTTGA TGAATTGCAA TGTTGTTACT TAATCCGTCA
AATAGTCCCA TTAGATGTTT CAATCCCTGA TAGGGATTTT GATGAATTGC
AATTTTGTGT TACTTGAATT ACTTTGTTGT AATATGCTGG TTTCAATCCC
TGATAGGGAT TTTGATGAAT TGCAATCAGC AACGTATGCT GTGGGATGCT
GGATATGCAC GTTTCAATCC CTGATAGGGA TTTTGATGAA TTGCAATTTG
CATATCTCCA TCCAACTGTA TTCAGCTGAA AAGTTTCAAT CCCTGATAGG
GATTTTGATG AATTGCAATC TTCGGCATAA CCATTCTTCC ACCTCCAGTA

17. AATAAAGCTTTACAAACCAAACTCTGGCTTCAATTGTGTAACCCAAGCTTTGATTCTTTCCTCTGTTAAATCGGATTGATTATCTTCATCAAGGGCAAGACCTACAAATTTACCATCACGAACAGCTTTAGACTCACTGAATTCATAACCTTCTGTAGGCCAATAGCCAACTGTTTCACCACCATTTTCTGAAATTTTTTCCTCTAGAATACCGAGGGCATCTTGAAATGTATCAGGATAACCAACCTGGTCTCCAGGAGCAAAATAAGCAACTTTTTTGCCGATGAAGTCAATGTTATCTAACTCATCATAAAAATTTTCCCAATCACTTTGCAATTCTCCAACATTCCAGGTAGGACAACCAACAACGATATAATCGTAGTTATTGAAATCACTTGGTTCAGCTTGTGAAATATCATATAAAGTTACAACACTATCACCACCAAACTCCTTCTGAATTATTTCTGATTCAGTTTGGGTATTGCCTGTTTGAGTACCAAAAAATAAACCAATATTAGACATTTTTACTCCTTTTATGTATTTGCAAAATTATTTCAATTAAAATATTTAGTAATAATTAATTGTTAGCTAGCTAATAATTAAATTTTTATTACAATCATTGTAAAAGGCATTGAAAAAGTAAATAAAAATTTTTATTCTACGTTATTTCAAAAATATTTACTTACATATACTTAACCTTTATAGTGATGTAATATACTCTAATTCCTATTTTACTTATAAATACCATCTCAGCTTAATGTAACGAATTTTTCTGTTTATCTTTAAATACAAAAAATTCAACAAAACTACAGAAAATTAATCTTAATAACACAAAACAAGTATCAATCTGTAATACAACTAAGCTTAAATAAATTAATAGAAAGCTTCATCTATCTAATAGGTTGAGAATAGTTTATGTCTAATGACATAAATTCATTCGTGTTGATTTCATTTGGGTATATTCATCTGATTTAGGATTTACTCCATTAAGTTTGTACTCATCAATGCCCGCCTGTTGGTATCCACAATTCTCATACAGTGCGCGAGCAAAGTAATCAATCGTTCGTCGCCATATCTAACTTTGAGTCAAACAAACCAGTTGGATTACCAACCCTCAACTAATCGCTTCTTTAAGGCGAGCGATCGCACATTTAACTGTTGGTTGTCACAAGAGAACTAATACTACAGCAGTATATTTAACAACTAAGGGTGGTTCAACTTTCGCTGCGACTCCTCCAACGCGCTGAAATACACAGGACTGATGCGATCGCAAACTCTTTGACTAAATTCCATACATTATCATGACCATCTCCCAAACAAACAAGTGGGTTAACCAGATGCTGACTATTAACATCCCCTGAGTTCGGAGTTGTAGGTCTATTTGACTGGTTCAAAGCGATGATGGAACGGCTTTGTTGCATGAATTAAAAAAAGACACACCATCACCTACTTCTAGGATAGACACATCAAACGTCCCACCGCCTAAGTCAAATACCAAGATAATTTCGTTAGTTTTCTTGTCAAGTCCGTAAGCGAGGGCCGCCGCCGTGGGCTAGTTGATAATTCGCAGAACTTTAATCCCGGCAATTCTACTGGCATCTTTGGTAGCCTGCCGTTGAGAGTCATTGAAATAGGCAGGGGTGGTAATTACCGCTTGCCTCACTGGTTCCCCCAGATATGTGCTGGCATCATCTATCAGCTTGCGGACTACCTCATACCATTTCACGAAAAACCTGATACACATGTAAACTCTGAAACCCTTGCTGTATCAAAGTTTTGTAATTACGAATTACGAATTACGAATTGATATCAGCCGAGATTTCTTCGGGTGAAAATTCCTTGTTCAGAGCGGGACAGTGTAGCTTGACATTGCCATTACTGTCACGTACCACTTTGTAAGTAACTTGTTTTGCCTCTTGCGTAACTTCATCATACCTGCGCCCGATGAACCGCTTCACAGAATAAAAAGTGTTTTCTGGGTTCATTACACCCTGGCGCTT
AATAAAGCTTTACAAACCAAACTCTGGCTTCAATTGTGTAACCCAAGCTTTGATTCTTTCCTCTGTTAAATCGGATTGATTATCTTCATCAAGGGCAAGACCTACAAATTTACCATCACGAACAGCTTTAGACTCACTGAATTCATAACCTTCTGTAGGCCAATAGCCAACTGTTTCACCACCATTTTCTGAAATTTTTTCCTCTAGAATACCGAGGGCATCTTGAAATGTATCAGGATAACCAACCTGGTCTCCAGGAGCAAAATAAGCAACTTTTTTGCCGATGAAGTCAATGTTATCTAACTCATCATAAAAATTTTCCCAATCACTTTGCAATTCTCCAACATTCCAGGTAGGACAACCAACAACGATATAATCGTAGTTATTGAAATCACTTGGTTCAGCTTGTGAAATATCATATAAAGTTACAACACTATCACCACCAAACTCCTTCTGAATTATTTCTGATTCAGTTTGGGTATTGCCTGTTTGAGTACCAAAAAATAAACCAATATTAGACATTTTTACTCCTTTTATGTATTTGCAAAATTATTTCAATTAAAATATTTAGTAATAATTAATTGTTAGCTAGCTAATAATTAAATTTTTATTACAATCATTGTAAAAGGCATTGAAAAAGTAAATAAAAATTTTTATTCTACGTTATTTCAAAAATATTTACTTACATATACTTAACCTTTATAGTGATGTAATATACTCTAATTCCTATTTTACTTATAAATACCATCTCAGCTTAATGTAACGAATTTTTCTGTTTATCTTTAAATACAAAAAATTCAACAAAACTACAGAAAATTAATCTTAATAACACAAAACAAGTATCAATCTGTAATACAACTAAGCTTAAATAAATTAATAGAAAGCTTCATCTATCTAATAGGTTGAGAATAGTTTATGTCTAATGACATAAATTCATTCGTGTTGATTTCATTTGGGTATATTCATCTGATTTAGGATTTACTCCATTAAGTTTGTACTCATCAATGCCCGCCTGTTGGTATCCACAATTCTCATACAGTGCGCGAGCAAAGTAATCAATCGTTCGTCGCCATATCTAACTTTGAGTCAAACAAACCAGTTGGATTACCAACCCTCAACTAATCGCTTCTTTAAGGCGAGCGATCGCACATTTAACTGTTGGTTGTCACAAGAGAACTAATACTACAGCAGTATATTTAACAACTAAGGGTGGTTCAACTTTCGCTGCGACTCCTCCAACGCGCTGAAATACACAGGACTGATGCGATCGCAAACTCTTTGACTAAATTCCATACATTATCATGACCATCTCCCAAACAAACAAGTGGGTTAACCAGATGCTGACTATTAACATCCCCTGAGTTCGGAGTTGTAGGTCTATTTGACTGGTTCAAAGCGATGATGGAACGGCTTTGTTGCATGAATTAAAAAAAGACACACCATCACCTACTTCTAGGATAGACACATCAAACGTCCCACCGCCTAAGTCAAATACCAAGATAATTTCGTTAGTTTTCTTGTCAAGTCCGTAAGCGAGGGCCGCCGCCGTGGGCTAGTTGATAATTCGCAGAACTTTAATCCCGGCAATTCTACTGGCATCTTTGGTAGCCTGCCGTTGAGAGTCATTGAAATAGGCAGGGGTGGTAATTACCGCTTGCCTCACTGGTTCCCCCAGATATGTGCTGGCATCATCTATCAGCTTGCGGACTACCTCATACCATTTCACGAAAAACCTGATACACATGTAAACTCTGAAACCCTTGCTGTATCAAAGTTTTGTAATTACGAATTACGAATTACGAATTGATATCAGCCGAGATTTCTTCGGGTGAAAATTCCTTGTTCAGAGCGGGACAGTGTAGCTTGACATTGCCATTACTGTCACGTACCACTTTGTAAGTAACTTGTTTTGCCTCTTGCGTAACTTCATCATACCTGCGCCCGATGAACCGCTTCACAGAATAAAAAGTGTTTTCTGGGTTCATTACACCCTGGCGCTT
AATAAAGCTTTACAAACCAAACTCTGGCTTCAATTGTGTAACCCAAGCTTTGATTCTTTCCTCTGTTAAATCGGATTGATTATCTTCATCAAGGGCAAGACCTACAAATTTACCATCACGAACAGCTTTAGACTCACTGAATTCATAACCTTCTGTAGGCCAATAGCCAACTGTTTCACCACCATTTTCTGAAATTTTTTCCTCTAGAATACCGAGGGCATCTTGAAATGTATCAGGATAACCAACCTGGTCTCCAGGAGCAAAATAAGCAACTTTTTTGCCGATGAAGTCAATGTTATCTAACTCATCATAAAAATTTTCCCAATCACTTTGCAATTCTCCAACATTCCAGGTAGGACAACCAACAACGATATAATCGTAGTTATTGAAATCACTTGGTTCAGCTTGTGAAATATCATATAAAGTTACAACACTATCACCACCAAACTCCTTCTGAATTATTTCTGATTCAGTTTGGGTATTGCCTGTTTGAGTACCAAAAAATAAACCAATATTAGACATTTTTACTCCTTTTATGTATTTGCAAAATTATTTCAATTAAAATATTTAGTAATAATTAATTGTTAGCTAGCTAATAATTAAATTTTTATTACAATCATTGTAAAAGGCATTGAAAAAGTAAATAAAAATTTTTATTCTACGTTATTTCAAAAATATTTACTTACATATACTTAACCTTTATAGTGATGTAATATACTCTAATTCCTATTTTACTTATAAATACCATCTCAGCTTAATGTAACGAATTTTTCTGTTTATCTTTAAATACAAAAAATTCAACAAAACTACAGAAAATTAATCTTAATAACACAAAACAAGTATCAATCTGTAATACAACTAAGCTTAAATAAATTAATAGAAAGCTTCATCTATCTAATAGGTTGAGAATAGTTTATGTCTAATGACATAAATTCATTCGTGTTGATTTCATTTGGGTATATTCATCTGATTTAGGATTTACTCCATTAAGTTTGTACTCATCAATGCCCGCCTGTTGGTATCCACAATTCTCATACAGTGCGCGAGCAAAGTAATCAATCGTTCGTCGCCATATCTAACTTTGAGTCAAACAAACCAGTTGGATTACCAACCCTCAACTAATCGCTTCTTTAAGGCGAGCGATCGCACATTTAACTGTTGGTTGTCACAAGAGAACTAATACTACAGCAGTATATTTAACAACTAAGGGTGGTTCAACTTTCGCTGCGACTCCTCCAACGCGCTGAAATACACAGGACTGATGCGATCGCAAACTCTTTGACTAAATTCCATACATTATCATGACCATCTCCCAAACAAACAAGTGGGTTAACCAGATGCTGACTATTAACATCCCCTGAGTTCGGAGTTGTAGGTCTATTTGACTGGTTCAAAGCGATGATGGAACGGCTTTGTTGCATGAATTAAAAAAAGACACACCATCACCTACTTCTAGGATAGACACATCAAACGTCCCACCGCCTAAGTCAAATACCAAGATAATTTCGTTAGTTTTCTTGTCAAGTCCGTAAGCGAGGGCCGCCGCCGTGGGCTAGTTGATAATTCGCAGAACTTTAATCCCGGCAATTCTACTGGCATCTTTGGTAGCCTGCCGTTGAGAGTCATTGAAATAGGCAGGGGTGGTAATTACCGCTTGCCTCACTGGTTCCCCCAGATATGTGCTGGCATCATCTATCAGCTTGCGGACTACCTCATACCATTTCACGAAAAACCTGATACACATGTAAACTCTGAAACCCTTGCTGTATCAAAGTTTTGTAATTACGAATTACGAATTACGAATTGATATCAGCCGAGATTTCTTCGGGTGAAAATTCCTTGTTCAGAGCGGGACAGTGTAGCTTGACATTGCCATTACTGTCACGTACCACTTTGTAAGTAACTTGTTTTGCCTCTTGCGTAACTTCATCATACCTGCGCCCGATGAACCGCTTCACAGAATAAAAAGTGTTTTCTGGGTTCATTACACCCTGGCGCTT

18. Blast Globin Expect = 4e-98 TCTACTTATA TTCAATCCAC AGGGCTACAC
AAGAGTCTGT TGAATGAACA CATACATGGT
TTCTGTCTGC TCTGACCTCT GGCAGCTTTC TGGATTTCGG AACTCTAGCC TGCCCCACTC GAACCTTAGT GACTTCTGCT ATACCAAAGT CTCCGTAAAC CTCTAACATG ATGTCAGCAA TGAATAAACT TTGTTAAAGG TACAAATGAA
AAGAGTTTAA AGTTAAAAAC GAATTGCAGT AAACCTGTAT GGTTACATGA ACTGCCTAAA TTATATATTT TAAGAAATTA ATTGCAATTA CCCCAGCTGT CATTAAAAAG AGGCAAATAC GACAGCACTG ACCCTCAAGA AGGCACCGGC GCTGAAATTC CGCTGAGAGC AGAGTGGTAC CCCTGCACCA GGTCTTTCCT GTGGGCACTG ATGAATGACT GAACGAACGA TTGAATGAAA
Expect = 4e-98

21. Working Together Towards Discovery
Surprise!
Working Together Towards Discovery

24. Surprise!

25. AATAAAGCTTTACAAACCAAACTCTGGCTTCAATTGTGTAACCCAAGCTTTGATTCTTTCCTCTGTTAAATCGGATTGATTATCTTCATCAAGGGCAAGACCTACAAATTTACCATCACGAACAGCTTTAGACTCACTGAATTCATAACCTTCTGTAGGCCAATAGCCAACTGTTTCACCACCATTTTCTGAAATTTTTTCCTCTAGAATACCGAGGGCATCTTGAAATGTATCAGGATAACCAACCTGGTCTCCAGGAGCAAAATAAGCAACTTTTTTGCCGATGAAGTCAATGTTATCTAACTCATCATAAAAATTTTCCCAATCACTTTGCAATTCTCCAACATTCCAGGTAGGACAACCAACAACGATATAATCGTAGTTATTGAAATCACTTGGTTCAGCTTGTGAAATATCATATAAAGTTACAACACTATCACCACCAAACTCCTTCTGAATTATTTCTGATTCAGTTTGGGTATTGCCTGTTTGAGTACCAAAAAATAAACCAATATTAGACATTTTTACTCCTTTTATGTATTTGCAAAATTATTTCAATTAAAATATTTAGTAATAATTAATTGTTAGCTAGCTAATAATTAAATTTTTATTACAATCATTGTAAAAGGCATTGAAAAAGTAAATAAAAATTTTTATTCTACGTTATTTCAAAAATATTTACTTACATATACTTAACCTTTATAGTGATGTAATATACTCTAATTCCTATTTTACTTATAAATACCATCTCAGCTTAATGTAACGAATTTTTCTGTTTATCTTTAAATACAAAAAATTCAACAAAACTACAGAAAATTAATCTTAATAACACAAAACAAGTATCAATCTGTAATACAACTAAGCTTAAATAAATTAATAGAAAGCTTCATCTATCTAATAGGTTGAGAATAGTTTATGTCTAATGACATAAATTCATTCGTGTTGATTTCATTTGGGTATATTCATCTGATTTAGGATTTACTCCATTAAGTTTGTACTCATCAATGCCCGCCTGTTGGTATCCACAATTCTCATACAGTGCGCGAGCAAAGTAATCAATCGTTCGTCGCCATATCTAACTTTGAGTCAAACAAACCAGTTGGATTACCAACCCTCAACTAATCGCTTCTTTAAGGCGAGCGATCGCACATTTAACTGTTGGTTGTCACAAGAGAACTAATACTACAGCAGTATATTTAACAACTAAGGGTGGTTCAACTTTCGCTGCGACTCCTCCAACGCGCTGAAATACACAGGACTGATGCGATCGCAAACTCTTTGACTAAATTCCATACATTATCATGACCATCTCCCAAACAAACAAGTGGGTTAACCAGATGCTGACTATTAACATCCCCTGAGTTCGGAGTTGTAGGTCTATTTGACTGGTTCAAAGCGATGATGGAACGGCTTTGTTGCATGAATTAAAAAAAGACACACCATCACCTACTTCTAGGATAGACACATCAAACGTCCCACCGCCTAAGTCAAATACCAAGATAATTTCGTTAGTTTTCTTGTCAAGTCCGTAAGCGAGGGCCGCCGCCGTGGGCTAGTTGATAATTCGCAGAACTTTAATCCCGGCAATTCTACTGGCATCTTTGGTAGCCTGCCGTTGAGAGTCATTGAAATAGGCAGGGGTGGTAATTACCGCTTGCCTCACTGGTTCCCCCAGATATGTGCTGGCATCATCTATCAGCTTGCGGACTACCTCATACCATTTCACGAAAAACCTGATACACATGTAAACTCTGAAACCCTTGCTGTATCAAAGTTTTGTAATTACGAATTACGAATTACGAATTGATATCAGCCGAGATTTCTTCGGGTGAAAATTCCTTGTTCAGAGCGGGACAGTGTAGCTTGACATTGCCATTACTGTCACGTACCACTTTGTAAGTAACTTGTTTTGCCTCTTGCGTAACTTCATCATACCTGCGCCCGATGAACCGCTTCACAGAATAAAAAGTGTTTTCTGGGTTCATTACACCCTGGCGCTT
AATAAAGCTTTACAAACCAAACTCTGGCTTCAATTGTGTAACCCAAGCTTTGATTCTTTCCTCTGTTAAATCGGATTGATTATCTTCATCAAGGGCAAGACCTACAAATTTACCATCACGAACAGCTTTAGACTCACTGAATTCATAACCTTCTGTAGGCCAATAGCCAACTGTTTCACCACCATTTTCTGAAATTTTTTCCTCTAGAATACCGAGGGCATCTTGAAATGTATCAGGATAACCAACCTGGTCTCCAGGAGCAAAATAAGCAACTTTTTTGCCGATGAAGTCAATGTTATCTAACTCATCATAAAAATTTTCCCAATCACTTTGCAATTCTCCAACATTCCAGGTAGGACAACCAACAACGATATAATCGTAGTTATTGAAATCACTTGGTTCAGCTTGTGAAATATCATATAAAGTTACAACACTATCACCACCAAACTCCTTCTGAATTATTTCTGATTCAGTTTGGGTATTGCCTGTTTGAGTACCAAAAAATAAACCAATATTAGACATTTTTACTCCTTTTATGTATTTGCAAAATTATTTCAATTAAAATATTTAGTAATAATTAATTGTTAGCTAGCTAATAATTAAATTTTTATTACAATCATTGTAAAAGGCATTGAAAAAGTAAATAAAAATTTTTATTCTACGTTATTTCAAAAATATTTACTTACATATACTTAACCTTTATAGTGATGTAATATACTCTAATTCCTATTTTACTTATAAATACCATCTCAGCTTAATGTAACGAATTTTTCTGTTTATCTTTAAATACAAAAAATTCAACAAAACTACAGAAAATTAATCTTAATAACACAAAACAAGTATCAATCTGTAATACAACTAAGCTTAAATAAATTAATAGAAAGCTTCATCTATCTAATAGGTTGAGAATAGTTTATGTCTAATGACATAAATTCATTCGTGTTGATTTCATTTGGGTATATTCATCTGATTTAGGATTTACTCCATTAAGTTTGTACTCATCAATGCCCGCCTGTTGGTATCCACAATTCTCATACAGTGCGCGAGCAAAGTAATCAATCGTTCGTCGCCATATCTAACTTTGAGTCAAACAAACCAGTTGGATTACCAACCCTCAACTAATCGCTTCTTTAAGGCGAGCGATCGCACATTTAACTGTTGGTTGTCACAAGAGAACTAATACTACAGCAGTATATTTAACAACTAAGGGTGGTTCAACTTTCGCTGCGACTCCTCCAACGCGCTGAAATACACAGGACTGATGCGATCGCAAACTCTTTGACTAAATTCCATACATTATCATGACCATCTCCCAAACAAACAAGTGGGTTAACCAGATGCTGACTATTAACATCCCCTGAGTTCGGAGTTGTAGGTCTATTTGACTGGTTCAAAGCGATGATGGAACGGCTTTGTTGCATGAATTAAAAAAAGACACACCATCACCTACTTCTAGGATAGACACATCAAACGTCCCACCGCCTAAGTCAAATACCAAGATAATTTCGTTAGTTTTCTTGTCAAGTCCGTAAGCGAGGGCCGCCGCCGTGGGCTAGTTGATAATTCGCAGAACTTTAATCCCGGCAATTCTACTGGCATCTTTGGTAGCCTGCCGTTGAGAGTCATTGAAATAGGCAGGGGTGGTAATTACCGCTTGCCTCACTGGTTCCCCCAGATATGTGCTGGCATCATCTATCAGCTTGCGGACTACCTCATACCATTTCACGAAAAACCTGATACACATGTAAACTCTGAAACCCTTGCTGTATCAAAGTTTTGTAATTACGAATTACGAATTACGAATTGATATCAGCCGAGATTTCTTCGGGTGAAAATTCCTTGTTCAGAGCGGGACAGTGTAGCTTGACATTGCCATTACTGTCACGTACCACTTTGTAAGTAACTTGTTTTGCCTCTTGCGTAACTTCATCATACCTGCGCCCGATGAACCGCTTCACAGAATAAAAAGTGTTTTCTGGGTTCATTACACCCTGGCGCTT
AATAAAGCTTTACAAACCAAACTCTGGCTTCAATTGTGTAACCCAAGCTTTGATTCTTTCCTCTGTTAAATCGGATTGATTATCTTCATCAAGGGCAAGACCTACAAATTTACCATCACGAACAGCTTTAGACTCACTGAATTCATAACCTTCTGTAGGCCAATAGCCAACTGTTTCACCACCATTTTCTGAAATTTTTTCCTCTAGAATACCGAGGGCATCTTGAAATGTATCAGGATAACCAACCTGGTCTCCAGGAGCAAAATAAGCAACTTTTTTGCCGATGAAGTCAATGTTATCTAACTCATCATAAAAATTTTCCCAATCACTTTGCAATTCTCCAACATTCCAGGTAGGACAACCAACAACGATATAATCGTAGTTATTGAAATCACTTGGTTCAGCTTGTGAAATATCATATAAAGTTACAACACTATCACCACCAAACTCCTTCTGAATTATTTCTGATTCAGTTTGGGTATTGCCTGTTTGAGTACCAAAAAATAAACCAATATTAGACATTTTTACTCCTTTTATGTATTTGCAAAATTATTTCAATTAAAATATTTAGTAATAATTAATTGTTAGCTAGCTAATAATTAAATTTTTATTACAATCATTGTAAAAGGCATTGAAAAAGTAAATAAAAATTTTTATTCTACGTTATTTCAAAAATATTTACTTACATATACTTAACCTTTATAGTGATGTAATATACTCTAATTCCTATTTTACTTATAAATACCATCTCAGCTTAATGTAACGAATTTTTCTGTTTATCTTTAAATACAAAAAATTCAACAAAACTACAGAAAATTAATCTTAATAACACAAAACAAGTATCAATCTGTAATACAACTAAGCTTAAATAAATTAATAGAAAGCTTCATCTATCTAATAGGTTGAGAATAGTTTATGTCTAATGACATAAATTCATTCGTGTTGATTTCATTTGGGTATATTCATCTGATTTAGGATTTACTCCATTAAGTTTGTACTCATCAATGCCCGCCTGTTGGTATCCACAATTCTCATACAGTGCGCGAGCAAAGTAATCAATCGTTCGTCGCCATATCTAACTTTGAGTCAAACAAACCAGTTGGATTACCAACCCTCAACTAATCGCTTCTTTAAGGCGAGCGATCGCACATTTAACTGTTGGTTGTCACAAGAGAACTAATACTACAGCAGTATATTTAACAACTAAGGGTGGTTCAACTTTCGCTGCGACTCCTCCAACGCGCTGAAATACACAGGACTGATGCGATCGCAAACTCTTTGACTAAATTCCATACATTATCATGACCATCTCCCAAACAAACAAGTGGGTTAACCAGATGCTGACTATTAACATCCCCTGAGTTCGGAGTTGTAGGTCTATTTGACTGGTTCAAAGCGATGATGGAACGGCTTTGTTGCATGAATTAAAAAAAGACACACCATCACCTACTTCTAGGATAGACACATCAAACGTCCCACCGCCTAAGTCAAATACCAAGATAATTTCGTTAGTTTTCTTGTCAAGTCCGTAAGCGAGGGCCGCCGCCGTGGGCTAGTTGATAATTCGCAGAACTTTAATCCCGGCAATTCTACTGGCATCTTTGGTAGCCTGCCGTTGAGAGTCATTGAAATAGGCAGGGGTGGTAATTACCGCTTGCCTCACTGGTTCCCCCAGATATGTGCTGGCATCATCTATCAGCTTGCGGACTACCTCATACCATTTCACGAAAAACCTGATACACATGTAAACTCTGAAACCCTTGCTGTATCAAAGTTTTGTAATTACGAATTACGAATTACGAATTGATATCAGCCGAGATTTCTTCGGGTGAAAATTCCTTGTTCAGAGCGGGACAGTGTAGCTTGACATTGCCATTACTGTCACGTACCACTTTGTAAGTAACTTGTTTTGCCTCTTGCGTAACTTCATCATACCTGCGCCCGATGAACCGCTTCACAGAATAAAAAGTGTTTTCTGGGTTCATTACACCCTGGCGCTT
Program the computer
Surprise!

26. Biology researchers do not program
Program the computer
10 Biology and Microbiology Depts at major universities

27. Why hasn't it happened? Programming languages
An alternative

28. Lives of the Scientist
(Part II)

29. Repeated sequences bacterial genomes
Genome of E. coli K12 str MG1655
genes
genes
REP sequences

33. Algorithm to extract REP sequences
Pattern

34. Algorithm to extract REP sequences
Pattern
" "

35. Algorithm to extract REP sequences
Pattern
"repeat_region "

36. Algorithm to extract REP sequences
Pattern
"repeat_region "

37. Algorithm to extract REP sequences
Pattern
"repeat_region "
Special symbols
... As many of previous character as possible

38. Algorithm to extract REP sequences
Pattern
"repeat_region "
Special symbols
... As many of previous character as possible

39. Algorithm to extract REP sequences
Pattern
"repeat_region "
Special symbols
... As many of previous character as possible # A single digit

40. Algorithm to extract REP sequences
Pattern
"repeat_region ...# "
Special symbols
... As many of previous character as possible # A single digit

41. Algorithm to extract REP sequences
Pattern
"repeat_region ...# "
Special symbols
... As many of previous character as possible # A single digit

42. Algorithm to extract REP sequences
Pattern
"repeat_region ...# "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside

43. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...) "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside

44. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...) "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside

45. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...) "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character

46. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)** "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character

47. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...) "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character

48. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...)* "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character

49. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...)* "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character .. As few of previous character as necessary

50. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...)* "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character .. As few of previous character as necessary

51. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...)* "
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character .. As few of previous character as necessary ' ' or ''

52. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...)*..' '"
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character .. As few of previous character as necessary ' ' or ''

53. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...)*..'( )'"
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character .. As few of previous character as necessary ' ' or ''

54. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...)*..'(*..)'"
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character .. As few of previous character as necessary ' ' or ''

55. We start
Go to:
Click: MICR 653

56. www.people.vcu.edu/~elhaij Click MICR 653
Using Firefox
Click MICR 653

58. biobike.csbc.vcu.edu

63. Function palette
Workspace
Results window

65. General Syntax of BioBIKE
Function-name
Argument (object)
Keyword
object
Flag
The basic unit of BioBIKE is the function box. It consists of the name of a function, perhaps one or more required arguments, and optional keywords and flags.
A function may be thought of as a black box: you feed it information, it produces a product.

66. General Syntax of BioBIKE
Function-name
Argument (object)
Keyword
object
Flag
Function boxes contain the following elements:
Function-name (e.g. SEQUENCE-OF or LENGTH-OF)
Argument: Required, acted on by function
Keyword clause: Optional, more information
Flag: Optional, more (yes/no) information

67. General Syntax of BioBIKE
Function-name
Argument (object)
Keyword
object
Flag
… and icons to help you work with functions:
Option icon: Brings up a menu of keywords and flags
Action icon: Brings up a menu enabling you to execute a function, copy and paste, information, get help, etc
Clear/Delete icon: Removes information you entered or removes box entirely

68. Functions
Sin
Sin (angle)
Angle

69. Functions
Length
Entity

70. Functions variable vs literal Length Entity "icahLnlna bormA" 14
Abraham Lincoln
192
"Abraham Lincoln" 14
variable vs literal

71. Functions list vs single value Length Entity "icahLnlna bormA" 14
Abraham Lincoln
192
"Abraham Lincoln" 14
US-presidents 44
list vs single value

72. single application of a function vs iteration of a function
Functions
Length
Entity
"icahLnlna bormA" 14
Abraham Lincoln
192
"Abraham Lincoln" 14
US-presidents
( …) 44
single application of a function vs iteration of a function

73. Functions
Arcsin
Angle
Sin
Angle

74. Functions
Arcsin
Angle
Sin (angle)
Nested functions Evaluated from the inside out A box is replaced by its value

75. Functions
"transposase"
Gene (npf0076)

76. Functions
Gene (npf0076)
Nested functions Evaluated from the inside out A box is replaced by its value

77. CLOSE BOXES BEFORE EXECUTING White is incompatible with execution
Pitfalls (the most common error in the language)
Gene (npf0076)
CLOSE BOXES BEFORE EXECUTING White is incompatible with execution

78. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...)*..'(*..)'"
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character .. As few of previous character as necessary ' ' or ''

80. Algorithm to extract REP sequences
Pattern
"repeat_region ...(#...)**(#...)*..'(*..)'"
Special symbols
... As many of previous character as possible # A single digit () Capture what's inside * Any character .. As few of previous character as necessary ' ' or ''

82. Mining files for data BUT... Pattern matching Quick and easy
Highly flexible
Works great
BUT...
Unforgiving (1 mismatch  death)

83. Conserved motifs of methyltransferases
Pattern
"[DS]PP[YF]"
Special symbols
[ ] Character set

84. Searching for conserved motifs
Pattern matching
Quick and easy
Unforgiving (1 mismatch  death)
Ignores lots of information
Position-specific scoring matrices (PSSMs)

85. Searching for conserved motifs What if you don’t have one?
Pattern matching
Quick and easy
Unforgiving (1 mismatch  death)
Ignores lots of information
Position-specific scoring matrices (PSSMs)
Needs training set
What if you don’t have one?

86. Lives of the Scientist
(Part III)

88. What to do with no training set?
New pattern discovery (Meme, Gibbs sampler, BioProspector)
snRNA U1 (pU1-6) AGGTATATGGAGCTGTGACAGGGCAGAAGTGTGTGAAGTC
histone H1t GCCCTACCCTATATAAGGCCCCGAGGCCGCCCGGGTGTTT
HMG-14 CGGCCGGCGGGGAGGGGGAGCCCGCGGCCGGGGACGCGGG
TP1 GCCAAGGCCTTAAATACCCAGACTCCTGCCCCCGGGCCTT
protamine P1 CCCTGGCATCTATAACAGGCCGCAGAGCTGGCCCCTGACT
nucleolin GCAGGCTCAGTCTTTCGCCTCAGTCTCGAGCTCTCGCTGG
snRNP E TGCCGCCGCGTGACCTTCACACTTCCGCTTCCGGTTCTTT
rp S14 GACACGGAAGTGACCCCCGTCGCTCCGCCCTCTCCCACTC
rp S17 TGGCCTAAGCTTTAACAGGCTTCGCCTGTGCTTCCTGTTT
ribosomal p. S19 ACCCTACGCCCGACTTGTGCGCCCGGGAAACCCCGTCGTT
a'-tubulin ba'1 GGTCTGGGCGTCCCGGCTGGGCCCCGTGTCTGTGCGCACG
b'-tubulin b'2 GGGAGGGTATATAAGCGTTGGCGGACGGTCGGTTGTAGCA
a'-actin skel-m. CCGCGGGCTATATAAAACCTGAGCAGAGGGACAAGCGGCC
a'-cardiac actin TCAGCGTTCTATAAAGCGGCCCTCCTGGAGCCAGCCACCC
b'-actin CGCGGCGGCGCCCTATAAAACCCAGCGGCGCGACGCGCCA
Human sequences 5’ to transcriptional start
“TATA box”?

89. How does Meme work?
snRNA U1 (pU1-6) AGGTATATGGAGCTGTGACAGGGCAGAAGTGTGTGAAGTC
histone H1t GCCCTACCCTATATAAGGCCCCGAGGCCGCCCGGGTGTTT
HMG-14 CGGCCGGCGGGGAGGGGGAGCCCGCGGCCGGGGACGCGGG
TP1 GCCAAGGCCTTAAATACCCAGACTCCTGCCCCCGGGCCTT
protamine P1 CCCTGGCATCTATAACAGGCCGCAGAGCTGGCCCCTGACT
Step 1. Arbitrarily choose candidate pattern from a sequence

90. How does Meme work?
snRNA U1 (pU1-6) AGGTATATGGAGCTGTGACAGGGCAGAAGTGTGTGAAGTC
histone H1t GCCCTACCCTATATAAGGCCCCGAGGCCGCCCGGGTGTTT
HMG-14 CGGCCGGCGGGGAGGGGGAGCCCGCGGCCGGGGACGCGGG
TP1 GCCAAGGCCTTAAATACCCAGACTCCTGCCCCCGGGCCTT
protamine P1 CCCTGGCATCTATAACAGGCCGCAGAGCTGGCCCCTGACT
Step 1. Arbitrarily choose candidate pattern from a sequence
Step 2. Find best matches to pattern in all sequences

91. How does Meme work?
snRNA U1 (pU1-6) AGGTATATGGAGCTGTGACAGGGCAGAAGTGTGTGAAGTC
histone H1t GCCCTACCCTATATAAGGCCCCGAGGCCGCCCGGGTGTTT
HMG-14 CGGCCGGCGGGGAGGGGGAGCCCGCGGCCGGGGACGCGGG
TP1 GCCAAGGCCTTAAATACCCAGACTCCTGCCCCCGGGCCTT
protamine P1 CCCTGGCATCTATAACAGGCCGCAGAGCTGGCCCCTGACT
Step 1. Arbitrarily choose candidate pattern from a sequence
Step 2. Find best matches to pattern in all sequences
Step 3. Construct position-dependent frequency table based on matches
GACAGGGCAGAA GCCCGGGTGTTT GCCGGGGACGCG GCCCCCGGGCCT GCCGCAGAGCTG
A C G T

92. How does Meme work?
snRNA U1 (pU1-6) AGGTATATGGAGCTGTGACAGGGCAGAAGTGTGTGAAGTC
histone H1t GCCCTACCCTATATAAGGCCCCGAGGCCGCCCGGGTGTTT
HMG-14 CGGCCGGCGGGGAGGGGGAGCCCGCGGCCGGGGACGCGGG
TP1 GCCAAGGCCTTAAATACCCAGACTCCTGCCCCCGGGCCTT
protamine P1 CCCTGGCATCTATAACAGGCCGCAGAGCTGGCCCCTGACT
Step 1. Arbitrarily choose candidate pattern from a sequence
Step 2. Find best matches to pattern in all sequences
Step 3. Construct position-dependent frequency table based on matches
Step 4. Calculate relative probability of matches from frequency table
GACAGGGCAGAA GCCCGGGTGTTT GCCGGGGACGCG GCCCCCGGGCCT GCCGCAGAGCTG
A C G T

93. How does Meme work?
snRNA U1 (pU1-6) AGGTATATGGAGCTGTGACAGGGCAGAAGTGTGTGAAGTC
histone H1t GCCCTACCCTATATAAGGCCCCGAGGCCGCCCGGGTGTTT
HMG-14 CGGCCGGCGGGGAGGGGGAGCCCGCGGCCGGGGACGCGGG
TP1 GCCAAGGCCTTAAATACCCAGACTCCTGCCCCCGGGCCTT
protamine P1 CCCTGGCATCTATAACAGGCCGCAGAGCTGGCCCCTGACT
Step 1. Arbitrarily choose candidate pattern from a sequence
Step 2. Find best matches to pattern in all sequences
Step 3. Construct position-dependent frequency table based on matches
Step 4. Calculate relative probability of matches from frequency table
Step 5. If probability score high, remember pattern and score

94. How does Meme work?
snRNA U1 (pU1-6) AGGTATATGGAGCTGTGACAGGGCAGAAGTGTGTGAAGTC
histone H1t GCCCTACCCTATATAAGGCCCCGAGGCCGCCCGGGTGTTT
HMG-14 CGGCCGGCGGGGAGGGGGAGCCCGCGGCCGGGGACGCGGG
TP1 GCCAAGGCCTTAAATACCCAGACTCCTGCCCCCGGGCCTT
protamine P1 CCCTGGCATCTATAACAGGCCGCAGAGCTGGCCCCTGACT
Step 1. Arbitrarily choose candidate pattern from a sequence
Step 2. Find best matches to pattern in all sequences
Step 3. Construct position-dependent frequency table based on matches
Step 4. Calculate relative probability of matches from frequency table
Step 5. If probability score high, remember pattern and score
Step 6. Repeat Steps 1 - 5

95. What to do with no training set?
New pattern discovery (Meme, Gibbs sampler, BioProspector)
snRNA U1 (pU1-6) AGGTATATGGAGCTGTGACAGGGCAGAAGTGTGTGAAGTC
histone H1t GCCCTACCCTATATAAGGCCCCGAGGCCGCCCGGGTGTTT
HMG-14 CGGCCGGCGGGGAGGGGGAGCCCGCGGCCGGGGACGCGGG
TP1 GCCAAGGCCTTAAATACCCAGACTCCTGCCCCCGGGCCTT
protamine P1 CCCTGGCATCTATAACAGGCCGCAGAGCTGGCCCCTGACT
nucleolin GCAGGCTCAGTCTTTCGCCTCAGTCTCGAGCTCTCGCTGG
snRNP E TGCCGCCGCGTGACCTTCACACTTCCGCTTCCGGTTCTTT
rp S14 GACACGGAAGTGACCCCCGTCGCTCCGCCCTCTCCCACTC
rp S17 TGGCCTAAGCTTTAACAGGCTTCGCCTGTGCTTCCTGTTT
ribosomal p. S19 ACCCTACGCCCGACTTGTGCGCCCGGGAAACCCCGTCGTT
a'-tubulin ba'1 GGTCTGGGCGTCCCGGCTGGGCCCCGTGTCTGTGCGCACG
b'-tubulin b'2 GGGAGGGTATATAAGCGTTGGCGGACGGTCGGTTGTAGCA
a'-actin skel-m. CCGCGGGCTATATAAAACCTGAGCAGAGGGACAAGCGGCC
a'-cardiac actin TCAGCGTTCTATAAAGCGGCCCTCCTGGAGCCAGCCACCC
b'-actin CGCGGCGGCGCCCTATAAAACCCAGCGGCGCGACGCGCCA
Human sequences 5’ to transcriptional start

96. Searching for conserved motifs
Pattern matching
Quick and easy
Unforgiving (1 mismatch  death)
Ignores lots of information
Position-specific scoring matrices (PSSMs)
Needs training set
Meme, Gibbs sampler, et al (PSSM in reverse)
Relatively unbiased
Can't easily handle variable-length gaps

97. Moral of the Stories

100. Biology researchers do not program
Program the computer
10 Biology and Microbiology Depts at major universities

101. Are you comfortable using programming in the service of your research?
I have no experience in computer programming
I am marginally experienced with programming
I have extremely limited experience in computer programming
I have very little experience
I used to work a lot with programs such as Matlab and R
I have never learned it before
I have very little experience in computer programming
I’m using now iTol service, uniprot, and DEG
Minimal programming in actual languages
I have no experience in computer programming

102. www.people.vcu.edu/~elhaij Click MICR 653
Using Firefox
Click MICR 653

104. Scientific Questions
I. What determines the beginning of a gene?

105. Scientific Questions
I. What determines the beginning of a gene?

106. Scientific Questions I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
HIV

107. Scientific Questions I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?

108. Scientific Questions I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?

109. Scientific Questions I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
III. Determination of short tandem repeats (STRs)

110. Scientific Questions I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
III. Determination of short tandem repeats (STRs)

111. Scientific Questions I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
III. Determination of short tandem repeats (STRs)
IV. Analysis of gene expression data

112. Metabolic correlates to N-deprivation
What enzymes of carbon metabolism are affected by N-starvation?
Pentose Phosphate Pathway
Glycogen metabolism
Carbon fixation
Cyanobacteria use primarily the reactions of the Pentose Phosphate Pathway to break down glucose derivatives. They use carbon fixation reactions to build glucose. These sets overlap a great deal.

113. Scientific Questions RNAseq
I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
III. Determination of short tandem repeats (STRs)
IV. Analysis of gene expression data
RNAseq

114. Measuring RNA through Microarrays
RNA from cell type #1 + RNA from cell type #2
Spot
Scan for red fluorescence Scan for green fluorescence
Combine images
Type #1 RNA > Type #2 RNA
Type #2 RNA > Type #1 RNA
Type #1 RNA  Type #2 RNA
Courtesy of Inst. für Hormon-und Fortpflanzungsforschung, Universität Hamburg

115. Scientific Questions Difference in intensity chip to chip
I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
III. Determination of short tandem repeats (STRs)
IV. Analysis of gene expression data
different conditions or different replicates
Difference in intensity chip to chip

116. Scientific Questions Difference in intensity chip to chip
I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
III. Determination of short tandem repeats (STRs)
IV. Analysis of gene expression data
different conditions or different replicates
Difference in intensity chip to chip

117. Scientific Questions I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
III. Determination of short tandem repeats (STRs)
IV. Analysis of gene expression data
V. CRISPRs in enteric bacteria
GTTTCAATCCCTGATAGGGATTTTAGAGGGTTTTAACAATAACTGGATAGCACTAGCAGAAGGGCTAGAAGGTTTCAATCCCTGATAGGGATTTTAGAGGGTTTTAACGTAT

118. Scientific Questions I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
III. Determination of short tandem repeats (STRs)
IV. Analysis of gene expression data
V. CRISPRs in enteric bacteria
GTTTCAATCCCTGATAGGGATTTTAGAGGGTTTTAACAATAACTGGATAGCACTAGCAGAAGGGCTAGAAGGTTTCAATCCCTGATAGGGATTTTAGAGGGTTTTAACGTAT

119. Scientific Questions
VI. Finding targets for DNA-binding proteins

120. Scientific Questions I. What determines the beginning of a gene?
II. Where in a bacterial genome are viruses integrated?
III. Determination of short tandem repeats (STRs)
IV. Analysis of gene expression data
V. CRISPRs in enteric bacteria
VI. Finding targets for DNA-binding proteins (targets known)
VII. Finding targets for DNA-binding proteins (genes known)