1 / 1

Introduction: bio-logic

A. B. A. B. A. B. B. A. RNApol. RNApol. +. -. ++. A. B. A. B. Introduction: bio-logic Informal descriptions of experimental observations on gene expression patterns often translate readily into the language of formal logic:. From TF binding to cis- regulatory logic

preston-nunez
Download Presentation

Introduction: bio-logic

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A B A B A B B A RNApol RNApol + - ++ A B A B Introduction: bio-logic Informal descriptions of experimental observations on gene expression patterns often translate readily into the language of formal logic: From TF binding to cis-regulatory logic The modulation factor  =W0 + WA+ WB + WABdetermines the transcription initiation rate. Special cases: The Logic of Gene RegulationMaria J. Schilstra & Hamid BolouriBiocomputation Research Group, University of Hertfordshire, Hatfield, UKhttp://strc.herts.ac.uk/bio/maria/NetBuilder/index.html 0 A B AB 1) 1) : logical AND, : logical OR, : logical NOT operators Questions 1. How do these logical operations relate to the biochemistry of gene expression? 2. Do the rules of Boolean algebra hold for ‘bio-logical’ operations? 3. Is the logical approach always justified? • The expressions for the modulation factor  hold for Booleanandcontinuous values between 0 and 1 • The expressions for obey thelaws of Boolean algebra (associative, commutative, De Morgan’s, etc.) • An expression for  can substitute a variable in another expression for . Transcription initiation: a minimal model Transcription factors (TFs) bind to their cis-regulatory binding sites, where they somehow affect the transcription initiation rate. Primitives In the expression for,  and  areprimitive: they cannot be linearized further. If binding of A depends on the presence of bound B, it may be necessary to use a primitive that contains [A] and [B] terms. Below: various primitives.a = [A]/KA, b = [B]/KB Fraction of time that the binding sites for A and B are unoccupied (y0), occupied only with A (yA), or simultaneously with A and B (yAB). Dependence of the dynamics of the concentration of the gene product P on the transcription initiation rate, kinitiation: Different TF combinations stimulate or repress transcription to different extents. EXAMPLE: Only A: weak stimulation Only B: repression of the effect of other factors A and B together: significant stimulation No A or B: no initiation • The transcription initiation rate kinitiation is determined by: • The maximum initiation rate (kiniMax) • The occupancy of the TF binding sites (y0, yA, yB, yAB) • The extent to which each complex stimulates initiation (w0, wA, wB, wAB) Answers 1. The biochemistry of gene expression relates to combinatorial logic as shown above 2. The rules of Boolean algebra hold for bio-logical operations, but... 3. ... strictly speaking, the logical approach is only justified for independent cis-regulatory binding sites. In practice, its use (including the choice of primitives) will depend on the accuracy of the data to be modelled, and on prior knowledge of the system If A and B do not affect each other’s binding (i.e.KA/KA(B) = 1), then the expression for  can belinearized to:  =W0 + WA+ WB + WAB ( = [B]/(KB + [B]),  = [B]/(KB + [B]), W0 = w0, WA = wA – W0, wAB = wAB – (W0+WA+WB)

More Related