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Bioinformatics

Bioinformatics. One of many definitions : Computer assisted use of large databases for biomedical purposes. I. Data structures; data mining; use of web-based environments. II. Sequence analyses; genomics and proteomics.

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Bioinformatics

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  1. Bioinformatics One of many definitions: Computer assisted use of large databases for biomedical purposes I. Data structures; data mining; use of web-based environments II. Sequence analyses; genomics and proteomics III. Pathways and networks; information retrieval; flux analyses IV. Statistics; maximum likelihood and probabilistic methods AS APPLIED TO BIOLOGY-DRIVEN QUESTIONS

  2. germination of sorus spores growth of encapsulation amoebae of spores chemotaxis to cAMP 24 hours stalk 18 hours 6 hours vacuolization of stalk cells 12 hours 5 aggregate (10 cells) tipped mound finger Are there shared genes and networks? How do cells communicate? What is the genetic basis of morphogenesis? What determines tissue proportions? THE LIFE CYCLE OF DICTYOSTELIUM DISCOIDEUM

  3. K-means clustering [5 groups]

  4. Clustering of developmentally regulated genes Early genes Middle genes Late genes Downers

  5. Curve fitting

  6. EXPRESSION PERIODS FOR MARKER GENES KP BOTH AX4

  7. Prestalk cells And 3 new genes And 26 new genes PKA PKA Precocious initiation of transcription Dependent Sequence in Dictyostelium Development ecmA tagB Stalk cells tagC yakA Gbg pufA GBF acrA ecmB carA Prespore cells acaA pkaC spiA LagC mybC stkA csaA CRAC cotA CAR3 Spores csbA Pia cotB RegA ZAK1 ERK2 cotC GSK3 Ga2 PKA PKA Precocious cessation of transcription

  8. gadA SSA273 wacA SSJ886 SSB695 SLD184 SSG693 SLB103 spiA Genes induced by cAMPbut not by PKA SLK857 Prespore specific genes SSL490 mybC cAMP acting independently of PKA SLE837 acbA

  9. Extracellular signal SDF2 DhkA two-component receptor kinase in prespore cells PKA SPORE ENCAPSULATION acrA cAMP MybC Dependent Prespore Genes gadA SSA273 wacA SSJ886 SLK857 SSB695 SSL490 SLD184 cAMP mybC SSG693 acbA SLB103 spiA

  10. Bioinformatics AS APPLIED TO THE GENETICS AND CELL BIOLOGY OF DICTYOSTELIUM I. Data structures-> mapping and genomic sequencing II. Sequence analyses-> annotation III. Pathways and networks-> microarray gene expression IV. Statistics-> curve-fitting Challenges for the future: 1) apply to other complex systems 2) predict experimental outcomes 3) recognize higher order complexity

  11. Are there shared genes and networks? How do cells communicate? What is the genetic basis of morphogenesis? What determines tissue proportions? QUESTIONS ANSWERS Many but not all are shared cAMP and peptide signals A few genes recognized so far Bioinformatics may not tell

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