timing from stochasticity
play

Timing from Stochasticity Scott Yang Nick Rhind (UMass Med) John - PowerPoint PPT Presentation

Jul 25, 2023 •373 likes •679 views

Modelling the Genome-wide Replication Program of Budding Yeast: Timing from Stochasticity Scott Yang Nick Rhind (UMass Med) John Bechhoefer (SFU) CMMT TGIF Series Dec 17, 2010 Take-home messages Should consider DNA replication from a

  1. Modelling the Genome-wide Replication Program of Budding Yeast: Timing from Stochasticity Scott Yang Nick Rhind (UMass Med) John Bechhoefer (SFU) CMMT TGIF Series Dec 17, 2010

  2. Take-home messages • Should consider DNA replication from a stochastic point of view • Precise timing of the replication program can emerge from stochasticity

  3. DNA replication http://www.paterson.man.ac.uk/cellcycle/replication.stm

  4. DNA replication: the Kinetics S phase S Non-replicated G1 Potential origins

  5. DNA replication: the Kinetics S phase S Non-replicated G1 Potential origins Origins + forks = replication program

  6. A Microarray Experiment synchronize Raghuraman et al . Science 2001

  7. Replication profiles Position x 100 % replication 0 Time (min) Raghuraman et al . Science 2001

  8. Replication profiles Replication time profile VI Raghuraman et al . Science 2001

  9. Replication profiles Position x Position x 100 100 % replication % replication 0 0 Time (min) Time (min) Raghuraman et al . Science 2001

  10. Replication profiles Replication time profile Replication fraction profile 100 VI % Replication 0 Raghuraman et al . Science 2001 McCune et al. Genetics 2008

  11. Point of Views More deterministic • Each origin has a preprogrammed firing time • plus some variation around that time

  12. Point of Views More deterministic More stochastic • Each origin has a • Each origin has a distribution of firing times preprogrammed firing time • has an expected firing • plus some variation around time that time

  13. Point of Views More deterministic More stochastic • Each origin has a • Each origin has a distribution of firing times preprogrammed firing time • has an expected firing • plus some variation around time that time • How to ensure precise firing • What counts the time and time if needed? how?

  14. Parametric model Firing-time distribution 0 100 200 Genome position (kb) x: origin position Cumulative firing-time distribution t 1/2 : median of distribution = sigmoid function t w : width of distribution v: globally constant fork velocity

  15. Parametric model Firing-time distribution 0 100 200 Genome position (kb) 100 x: origin position % rep. t 1/2 : median of distribution t w : width of distribution 0 v: globally constant fork velocity

  16. Key theoretical idea      N x x          i  f ( x , t ) 1 1 t   i     v    i 1 global fork velocity

  17. Result 1: fit McCune 2008

  18. Result 1: fit McCune 2008

  19. Result 2: firing-time distributions

  20. An idea Maybe…origins The number of MCM with wi th lot lots s of of exceeds the number MC MCM f M fire re of ORC by a factor of ear arly. y. 10 – 100 in various organisms! Nick Hyrien 2003

  21. Multiple stochastic initiators Firing-time dist. Time (min)

  22. Multiple initiator model Increasing # of initiators

  23. Point of Views More stochastic • How to ensure precise firing time if needed?

  24. Point of Views More stochastic • How to ensure precise firing time if needed? • Give it lots of MCM

  25. Point of Views More deterministic More stochastic • How to ensure precise firing • What counts the time and time if needed? how? • Give it lots of MCM

  26. Point of Views More deterministic More stochastic • How to ensure precise firing • What counts the time and time if needed? how? • Give it lots of MCM • ????

  27. Conclusions • DNA replication is a stochastic process • We have developed a flexible, analytical model • Timing needs not be from an explicit clock (contrary to most biologists’ intuitions?) • Timing can emerge from multiple stochastic initiators (MCM2 – 7) Yang, Rhind, Bechhoefer, MSB 2010

  28. Current work • Probe MCM occupancy and other factors • Other experimental setups & techniques • Other organisms  universal program? Molecular Systems Biology 6 :404 (2010) Thank you!

  29. Toy replication fraction profile A culture of cells T minutes into S phase 1 origin Average 100 % rep + + + + … 0 position Firing-time distribution

Recommend

Introduction to Data Science: Statistical X i = {0, 1} x 1 , x 2 , x 3 , , x 100 x 1 , x 2 , x

Introduction to Data Science: Statistical X i = {0, 1} x 1 , x 2 , x 3 , , x 100 x 1 , x 2 , x

Why Stats? Why Probability? Why Probability? Variation, randomness and stochasticity Variation, randomness and stochasticity Variation, randomness and stochasticity One nal word Why Probability? Why Probability? Why Probability? Why

1.32k views • 89 slides
Kolmogorov-Loveland stochasticity and Kolmogorov complexity Laurent Bienvenu Laboratoire

Kolmogorov-Loveland stochasticity and Kolmogorov complexity Laurent Bienvenu Laboratoire

Stochasticity Randomness and Kolmogorov complexity Our result Kolmogorov-Loveland stochasticity and Kolmogorov complexity Laurent Bienvenu Laboratoire dInformatique Fondamentale Marseille, France Symposium on Theoretical Aspects of

530 views • 48 slides
The Dawning of the Age of Stochasticity For over two millennia, Aristotles logic has ruled

The Dawning of the Age of Stochasticity For over two millennia, Aristotles logic has ruled

The Dawning of the Age of Stochasticity For over two millennia, Aristotles logic has ruled over the thinking of western intellectuals. All precise theories, all sci- entific models, even models of the process of thinking itself, have in

1.03k views • 34 slides
Stochasticity in Algorithmic Statistics for Polynomial Time Alexey Milovanov, Nikolay

Stochasticity in Algorithmic Statistics for Polynomial Time Alexey Milovanov, Nikolay

Stochasticity in Algorithmic Statistics for Polynomial Time Alexey Milovanov, Nikolay Vereshchagin National Research University Higher School of Economics CCC 2017, Riga 1 / 15 Algorithmic Statistics A black box that samples from

555 views • 54 slides
Tuning numerical parameters of algorithms: sampling and stochasticity handling Z. Yuan, T. St

Tuning numerical parameters of algorithms: sampling and stochasticity handling Z. Yuan, T. St

Tuning numerical parameters of algorithms: sampling and stochasticity handling Z. Yuan, T. St utzle, M. Birattari, M. Montes de Oca IRIDIA, CoDE, Universit e Libre de Bruxelles Brussels, Belgium zyuan@ulb.ac.be iridia.ulb.ac.be/~zyuan

810 views • 50 slides
Reconciling Rationality and Stochasticity: Rich Behavioral Models in Two-Player Games Mickael

Reconciling Rationality and Stochasticity: Rich Behavioral Models in Two-Player Games Mickael

Reconciling Rationality and Stochasticity: Rich Behavioral Models in Two-Player Games Mickael Randour Computer Science Department, ULB - Universit e libre de Bruxelles, Belgium July 24, 2016 GAMES 2016 - 5th World Congress of the Game Theory

599 views • 34 slides
Two Perspectives on Travelling Waves and Stochasticity Christian Kuehn Vienna University of

Two Perspectives on Travelling Waves and Stochasticity Christian Kuehn Vienna University of

Two Perspectives on Travelling Waves and Stochasticity Christian Kuehn Vienna University of Technology Institute for Analysis and Scientific Computing Overview Topic 1: Travelling Waves and Anomalous Diffusion Review of reaction-diffusion

750 views • 72 slides
New Modification of Restricted Boltzmann Machine that Considers the Stochasticity of Real Neural

New Modification of Restricted Boltzmann Machine that Considers the Stochasticity of Real Neural

New Modification of Restricted Boltzmann Machine that Considers the Stochasticity of Real Neural Network Guillermo Barrios Morales Ruoyu Zhao Restricted Boltzmann Machines (RBM) Probability of Each state of RBM has an energy: Probability

313 views • 18 slides
Timing Analysis Timing Path Groups and Types Timing paths are grouped into path groups

Timing Analysis Timing Path Groups and Types Timing paths are grouped into path groups

Introduction to Digital VLSI Logic Synthesis Timing Analysis Timing Path Groups and Types Timing paths are grouped into path groups according to the clock associated with the endpoint of the path. There is a default path group that

541 views • 18 slides
FORMAL MODELING AND VERIFICATION FOR TIMING PREDICTABILITY Mathieu Jan, Mihail Asavoae, Belgacem

FORMAL MODELING AND VERIFICATION FOR TIMING PREDICTABILITY Mathieu Jan, Mihail Asavoae, Belgacem

FORMAL MODELING AND VERIFICATION FOR TIMING PREDICTABILITY Mathieu Jan, Mihail Asavoae, Belgacem Ben Hedia ERTS 2020 Toulouse Outline of the talk Motivations and goals Timing anomalies in Worst-Case Timing Reasoning An example of a timing

286 views • 16 slides
Top 5 Timing Closure Techniques Greg Daughtry Correct Timing Constraints Analyze Before

Top 5 Timing Closure Techniques Greg Daughtry Correct Timing Constraints Analyze Before

Top 5 Timing Closure Techniques Greg Daughtry Correct Timing Constraints Analyze Before Doing Implementation Strategies and Directives Congestion and Complexity Advanced Physical Optimization Create Good Timing Constraints

659 views • 31 slides
X-ray ray Timing and Timing and Polarizati Polarization on mi missi ssion & & inst

X-ray ray Timing and Timing and Polarizati Polarization on mi missi ssion & & inst

X-ray ray Timing and Timing and Polarizati Polarization on mi missi ssion & & inst strumen mentation DONG Y Yongw ngwei Center fo r for r Parti rticle A Astroph trophysics Ins nstitute o of High Ene igh Energy P gy

437 views • 15 slides
Timing and Coordination Essential Knowledge 2.E.2 and 2.E.3 Timing and Coordination Timing

Timing and Coordination Essential Knowledge 2.E.2 and 2.E.3 Timing and Coordination Timing

Timing and Coordination Essential Knowledge 2.E.2 and 2.E.3 Timing and Coordination Timing and coordination of physiological events are regulated by multiple mechanisms ( 2.E.2 ) Timing and coordination of physiological events are

598 views • 37 slides
A Highly Compressed Timing Macro-modeling Algorithm for Hierarchical and Incremental Timing

A Highly Compressed Timing Macro-modeling Algorithm for Hierarchical and Incremental Timing

A Highly Compressed Timing Macro-modeling Algorithm for Hierarchical and Incremental Timing Analysis Tin-Yin Lai, and Martin D. F. Wong March. 16, 2018 Outline Introduction Timing Macro-modeling Problem Formulation Previous

397 views • 23 slides
Digital Design Discussion: RTL Storage Components Shift Register Timing Register File Timing

Digital Design Discussion: RTL Storage Components Shift Register Timing Register File Timing

Principles Of Digital Design Discussion: RTL Storage Components Shift Register Timing Register File Timing RAM Up/Down Counter FIFO Queue Shift Register Timing Problem: Complete the timing diagram for the shift register shown. Assume

302 views • 12 slides
Timing Library Format (TLF) Advanced VLSI Design CMPE 414 Timing Library Format (TLF) TLF is an

Timing Library Format (TLF) Advanced VLSI Design CMPE 414 Timing Library Format (TLF) TLF is an

Timing Library Format (TLF) Advanced VLSI Design CMPE 414 Timing Library Format (TLF) TLF is an ASCII representation of the timing and power parameters associated with any cell in a particular semiconductor technology The timing and power

308 views • 15 slides
Agenda Compare 4 alternative timing mechanisms (long and short the S&P 500)

Agenda Compare 4 alternative timing mechanisms (long and short the S&P 500)

Agenda Compare 4 alternative timing mechanisms (long and short the S&P 500) VectorVest confirmed ups and downs EMA / RT combo Timing Cube Ride the Waves Show the results of using the best timing method with a pair

804 views • 44 slides
1 Clock skew optimization Another approach for sequential timing optimization

1 Clock skew optimization Another approach for sequential timing optimization

Sequential Timing Optimization Long path timing constraints Data must not reach destination FF too late d max (i,j) s i + d(i,j) + T setup s j + P i j s s i i sj d(i,j) T setup Short path timing constraints FF should not

86 views • 7 slides
Liberty Timing File (LIB) Advanced VLSI Design CMPE 641 Liberty Timing File The .lib file is an

Liberty Timing File (LIB) Advanced VLSI Design CMPE 641 Liberty Timing File The .lib file is an

Liberty Timing File (LIB) Advanced VLSI Design CMPE 641 Liberty Timing File The .lib file is an ASCII representation of the timing and power parameters associated with any cell in a particular semiconductor technology The timing and power

298 views • 14 slides
A Compact and Accurate Timing Macro Model for Efficient Hierarchical Timing Analysis Pei-Yu Lee ,

A Compact and Accurate Timing Macro Model for Efficient Hierarchical Timing Analysis Pei-Yu Lee ,

A Compact and Accurate Timing Macro Model for Efficient Hierarchical Timing Analysis Pei-Yu Lee , Iris Hui-Ru Jiang, Ting-You Yang National Chiao Tung University Outline Introduction Problem Formulation Proposed Algorithm

807 views • 36 slides
Discussion: Remote Timing Attacks are Practical 600.624 2/11/05 Outline Why are timing

Discussion: Remote Timing Attacks are Practical 600.624 2/11/05 Outline Why are timing

Discussion: Remote Timing Attacks are Practical 600.624 2/11/05 Outline Why are timing attacks important? Clarifications Zero-One Gap / Neighborhood Size etc. Problems Questions Extensions Contribution Discussion

645 views • 26 slides
X-ray spectral timing: methods and interpretation Phil Uttley Why spectral-timing?

X-ray spectral timing: methods and interpretation Phil Uttley Why spectral-timing?

X-ray spectral timing: methods and interpretation Phil Uttley Why spectral-timing? Spectra are complex, hard to disentangle and GX 339-4 hard state interpretations are often degenerate model-rich (we have physical

424 views • 17 slides
Precision timing with PbWO 4 crystals and prospects for a precision timing upgrade of the CMS

Precision timing with PbWO 4 crystals and prospects for a precision timing upgrade of the CMS

Precision timing with PbWO 4 crystals and prospects for a precision timing upgrade of the CMS electromagnetic calorimeter at HL-LHC Simone Pigazzini on behalf of the CMS collaboration CALOR 2016 Simone Pigazzini Precision timing with PbWO

484 views • 12 slides
Agenda Who we are What this talk is about Why? Background Timing as a

Agenda Who we are What this talk is about Why? Background Timing as a

Agenda Who we are What this talk is about Why? Background Timing as a Channel Timing as a Vector Privacy Implications - XSRT? Another acronym - (D)XSRT! Conclusion / Questions Who we are.. SensePost

785 views • 46 slides

More recommend