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ICS280 Homework 1

ICS280 Homework 1. Due Thursday Jan 16 Read 2 of the 4 review articles Get software. DNA  RNA  Protein  Gene Regulation (DNA). DNA (+ bound proteins). mRNA. Transcription to mRNA ; Translation to protein. Protein (MyoD). Structures, motors, sensors, effectors,

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ICS280 Homework 1

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  1. ICS280 Homework 1 • Due Thursday Jan 16 • Read 2 of the 4 review articles • Get software

  2. DNA  RNA  Protein Gene Regulation (DNA) DNA (+ bound proteins) mRNA Transcription to mRNA; Translation to protein Protein (MyoD) Structures, motors, sensors, effectors, feedback circuitry, ... Regulation of DNA transcription by proteins (transcription factors)

  3. Gene Expression Data: Immunofluorescence hunchback and Kruppel with nuclear mask (Kosman, Reinitz, Sharp PSB 1998)

  4. Gene Expression Data:Immunofluorescence Drosophila gap and pair-rule gene expression as protein. Green: Kruppel. Blue: giant. Red: even-skipped. Courtesy John Reinitz.

  5. Gene Expression Clusters - C. Elegans Gene

  6. Transcriptional Gene Regulation Networks • Is oversimplified by mass-action kinetics • Gene Regulation Network (GRN) model Drosophila eve stripe expression in model (right) and data (left). Green: eve expression, red: kni expression. From [Reinitz and Sharp, Mech. of Devel., 49:133-158, 1995 ]. [Mjolsness et al. J. Theor. Biol. 152: 429-453, 1991]

  7. WUS Fletcher et al., Science v. 283, 1999 Brand et. al., Science 289, 617-619, (2000)

  8. Meristem Simulation

  9. Repressilator

  10. Repressilator

  11. Eukaryotic Cell Cycle - Schematic J. Tyson and B. Novak, J. theor. Biol. (2001) 210, 249}263

  12. Cell CycleProtein Interactions J. Tyson and B. Novak, J. theor. Biol. (2001) 210, 249}263

  13. annealer state parameters observed data templates SBML model SBML model LA code (C++) model parameters SOLUTION/ OPTIMIZATION ENGINE CODE WRITER SOLVER/OPTMIZER FOR THE CELL MODEL SBML CELL MODEL READER CELLERATOR interactive biological model description Systems Biology Markup Language model DIMENSION REDUCTION OTHER APPLICATIONS FOR SBML MODELS . . . Biological Hypotheses Biology User Regulations and reactions Mathematical model generation Simulation Datasets Mining Simulation results Followup experiments Optimization Cell Simulation Software

  14. MAP Kinase Pathways in Solution INPUT OUTPUT

  15. Cellerator Demo

  16. Cellerator: Automatic Model Generation

  17. A B C Input Canonical Form Biochemical Notation Output Canonical Form System of ODEs Activity (e.g., Cell Division) Solver Concentrations vs. Time Model Generationand Use

  18. E.g. MAP Kinase Cascade J. Ferrell model w/o scaffold With A. Levchenko

  19. Cellerator Arrow Translation

  20. Elementary Reactions • Bimolecular in solution: • A, B {C} • Example: Yeast Fus3 phosphorylates Far1, arrests cell cycle. • FUS3, KSS1 also phosphorylate Ste12 TF/Dig1/Dig2, leads to mating • Binding/unbinding at a site: • A, S  S-A • Example: Swi5p binds to DNA e.g. UTR for HO, responsible for mating type switch in daughter yeast cells.

  21. SWI5 details • Dephosphorylation of Swi5 by cdc14p is instrumental in up-regulating Sic1p level which leads to M progression [MIPS, BJW notes] • Nuclear localization (NLS) sequence is normally phosphorylated in S, G2, and M when Swi5p is located in the cytoplasm, and dephosphorylated during G1 when Swi5p enters the nucleus . Phosphorylation of the NLS is catalyzed by the B cyclin kinase. Three serines phosphorylated by cdc28p in vitro [MIPS] • Pho2p-Swi5p-DNA ternary complex is significantly more stable (t[1/2] = 20 min) than either Pho2p-DNA (t[1/2] = 2 min) or  Swi5p-DNA (t[1/2] = 15 sec) binary complexes [BJW notes]

  22. Transcription Factor Binding Note: n=2 homodimer cooperativity coefficient both amplifies and suppresses signals. Heterodimers increase specificity.

  23. TF Activation before Binding

  24. Mass Action Kinetics • Law of mass action for dilute solution in equilibrium: • Applied to bimolecular “prereaction” interactions:

  25. Cellerator Arrows: Catalytic Reactions  

  26. Cellerator Arrows: Transcriptional Regulation

  27. MAPK Pathways in Saccharomyces cerevisiae http://www.genome.ad.jp/kegg/

  28. MAPK cascades Madhani, HD. Fink, GR. THE RIDDLE OF MAP KINASE SIGNALING SPECIFICITY [Review]. Trends in Genetics. 14(4):151-155, 1998 Apr.

  29. KEGG yeast cell cycle

  30. GO hierarchy for Molecular Function:Transcription Factor Source: SGD

  31. SigmoidReaction Schemain UML

  32. Sigmoid Reactant Schema in UML

  33. Sigmoid Knowledge Source,Model Schemata

  34. Regulatory Cell Models Cellerator, SBML Python/Java/CORBA conversion conversion MLX Analyses - Clustering - Classification - Cross-validation - Scoring - Gene list tools Bioinformatics Software Architecture GUI - Genespring - Mimir - (Genetrix, others?) Expression DB - MAGE-OM + mods - Genex - FGDB Sequence DB Image DB - MLX image classes - Diamond Eye (JPL) Reactions DB

  35. Current Cellerator Library • Myogenesis (Chris Hart) • CMX Mitotic Oscillator (Goldbeter) • Repressilator (Elowitz & Leibler) • IP3 Calcium Channel (DeYoung & Keizer) • MAPK on Scaffold • Cell Cycle (Novak & Tyson) • Glycolysis (Sel’kov) • Ring Oscillator (enzymatic or transcriptional) • Meristem (in progress) • Hematopoietic Differentiation (in progress; includes C/EPB; PU.1; GATA-1; AML1; CBF;NFKB; CSFR)

  36. Cellerator Canonical Forms in Everyday Language • Input: Arrows + IC + rates (Palette Driven) • Mass action • Enzymatic • Transcriptional • Cascades • Modules (e.g., MAPK) • Intermediate Output • simple chemical reactions (where appropriate) • Output - ODES • Mathematica equations, SBML, C, FORTRAN, HTML, MATHML, XML • Optional Numerical Solution + Plots

  37. Cellerator Arrows: Law of Mass Action  

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