Computational models of neuronal biochemistry

Size: px
Start display at page:

Download "Computational models of neuronal biochemistry"

Transcription

1 Computational models of neuronal biochemistry Melanie I Stefan Centre for Discovery Brain Sciences, University of Edinburgh 25 August 2017 melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

2 Stefan lab, University of Edinburgh Models of neuronal biochemistry 25 August / 24

3 Modelling neuronal protein signalling Outline 1 Modelling neuronal protein signalling 2 Space affects chemical signalling 3 Chemical signalling affects space melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

4 Modelling neuronal protein signalling Calcium signalling in (early) LTP Models of neuronal biochemistry 25 August / 24

5 Modelling neuronal protein signalling Calcium signalling in (early) LTP Models of neuronal biochemistry 25 August / 24

6 Modelling neuronal protein signalling Calcium signalling in (early) LTP Models of neuronal biochemistry 25 August / 24

7 Modelling neuronal protein signalling Calcium signalling in (early) LTP Models of neuronal biochemistry 25 August / 24

8 Modelling neuronal protein signalling Calcium signalling in (early) LTP Models of neuronal biochemistry 25 August / 24

9 Modelling neuronal protein signalling Calcium signalling in (early) LTP Models of neuronal biochemistry 25 August / 24

10 Modelling neuronal protein signalling Calcium signalling in (early) LTP Models of neuronal biochemistry 25 August / 24

11 Modelling neuronal protein signalling Of course, it s more complicated Kennedy et al. Nat Rev Neurosci, melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

12 Space affects chemical signalling Outline 1 Modelling neuronal protein signalling 2 Space affects chemical signalling 3 Chemical signalling affects space melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

13 Space affects chemical signalling Space affects chemical signalling Kennedy et al. Nat Rev Neurosci, Biochemistry in small compartments Biological compartments are not well-mixed Ligand concentration can be small There is competition This can lead to counter-intuitive biochemical behaviours One example is the high-dose hook effect Models of neuronal biochemistry 25 August / 24

14 Space affects chemical signalling But first... Models of neuronal biochemistry 25 August / 24

15 Space affects chemical signalling But first... Models of neuronal biochemistry 25 August / 24

16 Space affects chemical signalling But first... Consider this game All available Panini cards are distributed among N players A player wins if they have a full Austria set melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

17 Space affects chemical signalling But first... Consider this game All available Panini cards are distributed among N players A player wins if they have a full Austria set How many winners can there be? melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

18 Space affects chemical signalling But first... Consider this game All available Panini cards are distributed among N players A player wins if they have a full Austria set How many winners can there be? How could we increase the number of winners? melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

19 Space affects chemical signalling How to win a game melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

20 Space affects chemical signalling How to win a game melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

21 Space affects chemical signalling OK, but why should I care? melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

22 Space affects chemical signalling OK, but why should I care? Calmodulin Ranjita Dutta Roy Karolinska Insitutet, Stockholm, Charité, Berlin Dutta-Roy et al. BMC Sys Biol, melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

23 Space affects chemical signalling Calmodulin is an allosteric protein Stefan et al. PNAS, Models of neuronal biochemistry 25 August / 24

24 Space affects chemical signalling Wild-type calmodulin shows a hook effect melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

25 Space affects chemical signalling Non-cooperative mutant shows a stronger hook effect melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

26 Space affects chemical signalling More is not always better (for allosteric activators) Models of neuronal biochemistry 25 August / 24

27 Space affects chemical signalling More is not always better (for allosteric activators) Models of neuronal biochemistry 25 August / 24

28 Chemical signalling affects space Outline 1 Modelling neuronal protein signalling 2 Space affects chemical signalling 3 Chemical signalling affects space melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

29 Chemical signalling affects space Chemical signalling affects space Actin cytoskeleton confers structural stability and strength Actin monomers assemble into branched strands Calcium signalling changes actin dynamics Models of neuronal biochemistry 25 August / 24

30 Chemical signalling affects space How does the spine cytoskeleton grow and change? Kadri Pajo Pajo and Stefan submitted Models of neuronal biochemistry 25 August / 24

31 Chemical signalling affects space MCell MCell Agent-based spatial stochastic simulator (Kerr et al. SIAM J Sci Comput., 2008) Allows for modelling of multi-state molecules (Stefan et al. PLoS Comp Biol, 2014) Available at Integration with blender for model definition and visualisation melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

32 Chemical signalling affects space Modelling actin cytoskeleton dynamics Models of neuronal biochemistry 25 August / 24

33 Chemical signalling affects space Modelling actin cytoskeleton dynamics Models of neuronal biochemistry 25 August / 24

34 Chemical signalling affects space Modelling actin cytoskeleton dynamics Models of neuronal biochemistry 25 August / 24

35 Chemical signalling affects space Modelling actin cytoskeleton dynamics Models of neuronal biochemistry 25 August / 24

36 Chemical signalling affects space Take-home messages Stefan et al. PLoS Comp Biol, 2014 Subcellular space is not a test-tube The biochemistry of cellular compartments is often non-intuitive New tools allow us to create spatial models of biochemical signalling We can model structural change and chemical interactions on the same platform melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

37 Chemical signalling affects space Come and say hi! Stefan Lab Isla Smith - High-dose hook effect in diagnostic testing Jana Finz gar - mglur-nmdar interactions Lewis Strachan, Richard Fitzpatrick - Pathway modelling in autism spectrum disorders Salvador Garcı a Gonza lez - Learning analytics software Susana Roma n Garcı a - CaMKII interactions with NMDA receptors Tara O Driscoll - CaMKII autoactivation Zale Cao - Neuronal networks in C. elegans Alumni Excellence Ogunbayo - Components of a minimal memory sytem Kadri Pajo - Actin cytoskeleton remodelling Yubin Xie - Multi-scale modelling of plasticity in the MVN melanie.stefan@ed.ac.uk Models of neuronal biochemistry 25 August / 24

Connecting Epilepsy and Alzheimer s Disease: A Computational Modeling Framework

Connecting Epilepsy and Alzheimer s Disease: A Computational Modeling Framework Connecting Epilepsy and Alzheimer s Disease: A Computational Modeling Framework Péter Érdi perdi@kzoo.edu Henry R. Luce Professor Center for Complex Systems Studies Kalamazoo College http://people.kzoo.edu/

More information

Diffusion-activation model of CaMKII translocation waves in dendrites

Diffusion-activation model of CaMKII translocation waves in dendrites Diffusion-activation model of CaMKII translocation waves in dendrites Berton Earnshaw Department of Mathematics Michigan State University Paul Bressloff Mathematical Institute University of Oxford August

More information

Diffusion-activation model of CaMKII translocation waves in dendrites

Diffusion-activation model of CaMKII translocation waves in dendrites Diffusion-activation model of CaMKII translocation waves in dendrites Paul Bressloff Berton Earnshaw Department of Mathematics University of Utah June 2, 2009 Bressloff, Earnshaw (Utah) Diffusion-activation

More information

A local sensitivity analysis of Ca 2+ -calmodulin binding and its influence over PP1 activity

A local sensitivity analysis of Ca 2+ -calmodulin binding and its influence over PP1 activity 22nd International Congress on Modelling and Simulation, Hobart, Tasmania, Australia, 3 to 8 December 2017 mssanz.org.au/modsim2017 A local sensitivity analysis of Ca 2+ -calmodulin binding and its influence

More information

Sampling-based probabilistic inference through neural and synaptic dynamics

Sampling-based probabilistic inference through neural and synaptic dynamics Sampling-based probabilistic inference through neural and synaptic dynamics Wolfgang Maass for Robert Legenstein Institute for Theoretical Computer Science Graz University of Technology, Austria Institute

More information

Identification of TARP Phosphorylation Sites and Their Significance in the Brain

Identification of TARP Phosphorylation Sites and Their Significance in the Brain Identification of TARP Phosphorylation Sites and Their Significance in the Brain Susumu Tomita @ SHM BE17 Department of Cellular and Molecular Physiology NIDA Neuroproteomics Center, December 13, 2008

More information

A Dynamic Model of Interactions of Ca 2+, Calmodulin, and Catalytic Subunits of Ca 2+ /Calmodulin-Dependent Protein Kinase II

A Dynamic Model of Interactions of Ca 2+, Calmodulin, and Catalytic Subunits of Ca 2+ /Calmodulin-Dependent Protein Kinase II A Dynamic Model of Interactions of Ca 2+, Calmodulin, and Catalytic Subunits of Ca 2+ /Calmodulin-Dependent Protein Kinase II Shirley Pepke 1., Tamara Kinzer-Ursem 2., Stefan Mihalas 2, Mary B. Kennedy

More information

Signaling to the Nucleus by an L-type Calcium Channel- Calmodulin Complex Through the MAP Kinase Pathway

Signaling to the Nucleus by an L-type Calcium Channel- Calmodulin Complex Through the MAP Kinase Pathway Signaling to the Nucleus by an L-type Calcium Channel- Calmodulin Complex Through the MAP Kinase Pathway Ricardo E. Dolmetsch, Urvi Pajvani, Katherine Fife, James M. Spotts, Michael E. Greenberg Science

More information

Intracellular transport

Intracellular transport Transport in cells Intracellular transport introduction: transport in cells, molecular players etc. cooperation of motors, forces good and bad transport regulation, traffic issues, Stefan Klumpp image

More information

Neurite initiation. Neurite formation begins with a bud that sprouts from the cell body. One or several neurites can sprout at a time.

Neurite initiation. Neurite formation begins with a bud that sprouts from the cell body. One or several neurites can sprout at a time. Neurite initiation. Neuronal maturation initiation f-actin polarization and maturation tubulin stage 1: "spherical" neuron stage 2: neurons extend several neurites stage 3: one neurite accelerates its

More information

Design Principles of a Bacterial Signalling Network

Design Principles of a Bacterial Signalling Network Design Principles of a Bacterial Signalling Network Why is chemotaxis more complicated than needed? Jens Timmer Freiburg Institute for Advanced Studies Center for Systems Biology Center for Data Analysis

More information

The thermodynamics of cellular computation

The thermodynamics of cellular computation The thermodynamics of cellular computation Sourjik and Wingreen (2012) Cur. Opinions in Cell Bio. Pankaj Mehta Collaborators: David Schwab, Charles Fisher, Mo Khalil Cells perform complex computations

More information

7.32/7.81J/8.591J. Rm Rm (under construction) Alexander van Oudenaarden Jialing Li. Bernardo Pando. Rm.

7.32/7.81J/8.591J. Rm Rm (under construction) Alexander van Oudenaarden Jialing Li. Bernardo Pando. Rm. Introducing... 7.32/7.81J/8.591J Systems Biology modeling biological networks Lectures: Recitations: ti TR 1:00-2:30 PM W 4:00-5:00 PM Rm. 6-120 Rm. 26-204 (under construction) Alexander van Oudenaarden

More information

COMBINATORIAL CHEMISTRY: CURRENT APPROACH

COMBINATORIAL CHEMISTRY: CURRENT APPROACH COMBINATORIAL CHEMISTRY: CURRENT APPROACH Dwivedi A. 1, Sitoke A. 2, Joshi V. 3, Akhtar A.K. 4* and Chaturvedi M. 1, NRI Institute of Pharmaceutical Sciences, Bhopal, M.P.-India 2, SRM College of Pharmacy,

More information

Systems Biology: A Personal View IX. Landscapes. Sitabhra Sinha IMSc Chennai

Systems Biology: A Personal View IX. Landscapes. Sitabhra Sinha IMSc Chennai Systems Biology: A Personal View IX. Landscapes Sitabhra Sinha IMSc Chennai Fitness Landscapes Sewall Wright pioneered the description of how genotype or phenotypic fitness are related in terms of a fitness

More information

Energy Transformation and Metabolism (Outline)

Energy Transformation and Metabolism (Outline) Energy Transformation and Metabolism (Outline) - Definitions & Laws of Thermodynamics - Overview of energy flow ecosystem - Biochemical processes: Anabolic/endergonic & Catabolic/exergonic - Chemical reactions

More information

Lecture Notes for Fall Network Modeling. Ernest Fraenkel

Lecture Notes for Fall Network Modeling. Ernest Fraenkel Lecture Notes for 20.320 Fall 2012 Network Modeling Ernest Fraenkel In this lecture we will explore ways in which network models can help us to understand better biological data. We will explore how networks

More information

REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR

REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR Grade Requirement: All courses required for the Biochemistry major (CH, MATH, PHYS, BI courses) must be graded and passed with a grade of C- or better. Core Chemistry

More information

Modelling with cellular automata

Modelling with cellular automata Modelling with cellular automata Shan He School for Computational Science University of Birmingham Module 06-23836: Computational Modelling with MATLAB Outline Outline of Topics Concepts about cellular

More information

Evolutionary Games and Computer Simulations

Evolutionary Games and Computer Simulations Evolutionary Games and Computer Simulations Bernardo A. Huberman and Natalie S. Glance Dynamics of Computation Group Xerox Palo Alto Research Center Palo Alto, CA 94304 Abstract The prisoner s dilemma

More information

Quantum stochasticity and neuronal computations

Quantum stochasticity and neuronal computations Institute for Clinical Neuroanatomy Dr. Senckenbergische Anatomie J.-W. Goethe Universität, Frankfurt am Main Quantum stochasticity and neuronal computations Peter Jedlička, MD Definition A stochastic

More information

C. elegans L1 cell adhesion molecule functions in axon guidance

C. elegans L1 cell adhesion molecule functions in axon guidance C. elegans L1 cell adhesion molecule functions in axon guidance Biorad Lihsia Chen Dept. of Genetics, Cell Biology & Development Developmental Biology Center C. elegans embryogenesis Goldstein lab, UNC-Chapel

More information

Biochemical Reactions and Logic Computation

Biochemical Reactions and Logic Computation Biochemical Reactions and Logic Computation Biochemical Reactions and Biology Complex behaviors of a living organism originate from systems of biochemical reactions Jie-Hong Roland Jiang (Introduction

More information

Illustrating the Steady-state Condition and the Single-molecule Kinetic Method with the NMDA Receptor hs

Illustrating the Steady-state Condition and the Single-molecule Kinetic Method with the NMDA Receptor hs Q 2009 by The International Union of Biochemistry and Molecular Biology BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION Vol. 37, No. 6, pp. 333 338, 2009 Articles Illustrating the Steady-state Condition and

More information

Lecture 4: Importance of Noise and Fluctuations

Lecture 4: Importance of Noise and Fluctuations Lecture 4: Importance of Noise and Fluctuations Jordi Soriano Fradera Dept. Física de la Matèria Condensada, Universitat de Barcelona UB Institute of Complex Systems September 2016 1. Noise in biological

More information

Diffusion. CS/CME/BioE/Biophys/BMI 279 Nov. 15 and 20, 2016 Ron Dror

Diffusion. CS/CME/BioE/Biophys/BMI 279 Nov. 15 and 20, 2016 Ron Dror Diffusion CS/CME/BioE/Biophys/BMI 279 Nov. 15 and 20, 2016 Ron Dror 1 Outline How do molecules move around in a cell? Diffusion as a random walk (particle-based perspective) Continuum view of diffusion

More information

Baz, Par-6 and apkc are not required for axon or dendrite specification in Drosophila

Baz, Par-6 and apkc are not required for axon or dendrite specification in Drosophila Baz, Par-6 and apkc are not required for axon or dendrite specification in Drosophila Melissa M. Rolls and Chris Q. Doe, Inst. Neurosci and Inst. Mol. Biol., HHMI, Univ. Oregon, Eugene, Oregon 97403 Correspondence

More information

Biological Pathways Representation by Petri Nets and extension

Biological Pathways Representation by Petri Nets and extension Biological Pathways Representation by and extensions December 6, 2006 Biological Pathways Representation by and extension 1 The cell Pathways 2 Definitions 3 4 Biological Pathways Representation by and

More information

Calcium dynamics in dendritic spines, modeling and experiments

Calcium dynamics in dendritic spines, modeling and experiments Cell Calcium June 16, 2004 Calcium dynamics in dendritic spines, modeling and experiments D. Holcman 1,2 E. Korkotian 3 and M. Segal 3 1 3 Department of Mathematics, and Neurobiology The Weizmann Institute,

More information

Life Requires FREE ENERGY!

Life Requires FREE ENERGY! Life Requires FREE ENERGY! Ok, so Growth, reproduction and homeostasis of living systems requires free energy To be alive/stay living, you need to use energy. Duh But really, why is energy so important?

More information

EVOLUTIONARY STABILITY FOR TWO-STAGE HAWK-DOVE GAMES

EVOLUTIONARY STABILITY FOR TWO-STAGE HAWK-DOVE GAMES ROCKY MOUNTAIN JOURNAL OF MATHEMATICS olume 25, Number 1, Winter 1995 EOLUTIONARY STABILITY FOR TWO-STAGE HAWK-DOE GAMES R. CRESSMAN ABSTRACT. Although two individuals in a biological species often interact

More information

Molecular Cell Biology 5068 In Class Exam 1 September 30, Please print your name:

Molecular Cell Biology 5068 In Class Exam 1 September 30, Please print your name: Molecular Cell Biology 5068 In Class Exam 1 September 30, 2014 Exam Number: Please print your name: Instructions: Please write only on these pages, in the spaces allotted and not on the back. Write your

More information

Using Evolutionary Approaches To Study Biological Pathways. Pathways Have Evolved

Using Evolutionary Approaches To Study Biological Pathways. Pathways Have Evolved Pathways Have Evolved Using Evolutionary Approaches To Study Biological Pathways Orkun S. Soyer The Microsoft Research - University of Trento Centre for Computational and Systems Biology Protein-protein

More information

NGF - twenty years a-growing

NGF - twenty years a-growing NGF - twenty years a-growing A molecule vital to brain growth It is twenty years since the structure of nerve growth factor (NGF) was determined [ref. 1]. This molecule is more than 'quite interesting'

More information

Canadian Advanced Senior High

Canadian Advanced Senior High Canadian Advanced Senior High Department: Science Course Development Date: November 2017 Course Title: Biology Grade: 12 Course Type: Ministry Course Code: University SBI4U Credit Value: 1 Hours: 110 Ministry

More information

Course plan Academic Year Qualification MSc on Bioinformatics for Health Sciences. Subject name: Computational Systems Biology Code: 30180

Course plan Academic Year Qualification MSc on Bioinformatics for Health Sciences. Subject name: Computational Systems Biology Code: 30180 Course plan 201-201 Academic Year Qualification MSc on Bioinformatics for Health Sciences 1. Description of the subject Subject name: Code: 30180 Total credits: 5 Workload: 125 hours Year: 1st Term: 3

More information

Retrieving hits through in silico screening and expert assessment M. N. Drwal a,b and R. Griffith a

Retrieving hits through in silico screening and expert assessment M. N. Drwal a,b and R. Griffith a Retrieving hits through in silico screening and expert assessment M.. Drwal a,b and R. Griffith a a: School of Medical Sciences/Pharmacology, USW, Sydney, Australia b: Charité Berlin, Germany Abstract:

More information

Visual pigments. Neuroscience, Biochemistry Dr. Mamoun Ahram Third year, 2019

Visual pigments. Neuroscience, Biochemistry Dr. Mamoun Ahram Third year, 2019 Visual pigments Neuroscience, Biochemistry Dr. Mamoun Ahram Third year, 2019 References Webvision: The Organization of the Retina and Visual System (http://www.ncbi.nlm.nih.gov/books/nbk11522/#a 127) The

More information

The ubiquitin-proteasome-system

The ubiquitin-proteasome-system Repository of the Max Delbrück Center for Molecular Medicine (MDC) Berlin (Germany) http://edoc.mdc-berlin.de/13359/ The ubiquitin-proteasome-system Sommer, Thomas; Wolf, Dieter H. NOTICE: this is the

More information

Multiple spatial scales of AMPA receptor trafficking

Multiple spatial scales of AMPA receptor trafficking Multiple spatial scales of From synapse to spiny dendrite Paul Bressloff Berton Earnshaw Department of Mathematics University of Utah March 26, 2009 Bressloff, Earnshaw (Utah) Multiple scales of AMPAR

More information

Objectives INTRODUCTION TO METABOLISM. Metabolism. Catabolic Pathways. Anabolic Pathways 3/6/2011. How to Read a Chemical Equation

Objectives INTRODUCTION TO METABOLISM. Metabolism. Catabolic Pathways. Anabolic Pathways 3/6/2011. How to Read a Chemical Equation Objectives INTRODUCTION TO METABOLISM. Chapter 8 Metabolism, Energy, and Life Explain the role of catabolic and anabolic pathways in cell metabolism Distinguish between kinetic and potential energy Distinguish

More information

Global Chemistry Congress. June 10-12, 2019 Rome, Italy

Global Chemistry Congress. June 10-12, 2019 Rome, Italy June 10-12, 2019 Rome, Italy Global Chemistry Congress Phronesis, LLC, 919 North Market Street, Suite 950 Wilmington, Delaware 19801 USA Email: gcc@phronesisonline.net, gcc@phronesisonline.us Tel: +1 (302)

More information

What are some of the major questions in cell biology? (That require quantitative methods and reasoning)

What are some of the major questions in cell biology? (That require quantitative methods and reasoning) Introduction What are some of the major questions in cell biology? (That require quantitative methods and reasoning) Big questions How does a cell know when to divide? How does it coordinate the process

More information

REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR

REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR Grade Requirement: All courses required for the Biochemistry major (CH, MATH, PHYS, BI courses) must be graded and passed with a grade of C- or better. Core Chemistry

More information

Synapses. Electrophysiology and Vesicle release

Synapses. Electrophysiology and Vesicle release Synapses Electrophysiology and Vesicle release Major point Cell theory (cells being separated) implies that cells must communicate with each other through extracellular connections most communication is

More information

COURSE NUMBER: EH 590R SECTION: 1 SEMESTER: Fall COURSE TITLE: Computational Systems Biology: Modeling Biological Responses

COURSE NUMBER: EH 590R SECTION: 1 SEMESTER: Fall COURSE TITLE: Computational Systems Biology: Modeling Biological Responses DEPARTMENT: Environmental Health COURSE NUMBER: EH 590R SECTION: 1 SEMESTER: Fall 2017 CREDIT HOURS: 2 COURSE TITLE: Computational Systems Biology: Modeling Biological Responses COURSE LOCATION: TBD PREREQUISITE:

More information

1

1 http://photos1.blogger.com/img/13/2627/640/screenhunter_047.jpg 1 The Nose Knows http://graphics.jsonline.com/graphics/owlive/img/mar05/sideways.one0308_big.jpg 2 http://www.stlmoviereviewweekly.com/sitebuilder/images/sideways-253x364.jpg

More information

Chapter 6- An Introduction to Metabolism*

Chapter 6- An Introduction to Metabolism* Chapter 6- An Introduction to Metabolism* *Lecture notes are to be used as a study guide only and do not represent the comprehensive information you will need to know for the exams. The Energy of Life

More information

OrganicPad: a tool to investigate the development of representational competence in chemistry

OrganicPad: a tool to investigate the development of representational competence in chemistry OrganicPad: a tool to investigate the development of representational competence in chemistry (and a framework for future graphical metacognitive activities) Melanie M Cooper et. al. Lewis Structure the

More information

Advanced Higher Biology. Unit 1- Cells and Proteins 2c) Membrane Proteins

Advanced Higher Biology. Unit 1- Cells and Proteins 2c) Membrane Proteins Advanced Higher Biology Unit 1- Cells and Proteins 2c) Membrane Proteins Membrane Structure Phospholipid bilayer Transmembrane protein Integral protein Movement of Molecules Across Membranes Phospholipid

More information

Neural Circuit for Fly Mating

Neural Circuit for Fly Mating Neural Circuit for Fly Mating 2013/01/15 Tatsuo Okubo Image: Dickson lab Fly mating Sokolowski (Nat Rev Genetics, 2001) Drosophila courtship movie (Dylan Clyne) The Fru circuit Barry Dickson lab (http://www.imp.ac.at/research/research-groups/dickson-group/research/)

More information

Concept 6.1 To study cells, biologists use microscopes and the tools of biochemistry

Concept 6.1 To study cells, biologists use microscopes and the tools of biochemistry Name Period Chapter 6: A Tour of the Cell Concept 6.1 To study cells, biologists use microscopes and the tools of biochemistry 1. The study of cells has been limited by their small size, and so they were

More information

38050 Povo Trento (Italy), Via Sommarive 14 CAUSAL P-CALCULUS FOR BIOCHEMICAL MODELLING

38050 Povo Trento (Italy), Via Sommarive 14  CAUSAL P-CALCULUS FOR BIOCHEMICAL MODELLING UNIVERSITY OF TRENTO DEPARTMENT OF INFORMATION AND COMMUNICATION TECHNOLOGY 38050 Povo Trento (Italy), Via Sommarive 14 http://www.dit.unitn.it CAUSAL P-CALCULUS FOR BIOCHEMICAL MODELLING M. Curti, P.

More information

Ch 4: Cellular Metabolism, Part 1

Ch 4: Cellular Metabolism, Part 1 Developed by John Gallagher, MS, DVM Ch 4: Cellular Metabolism, Part 1 Energy as it relates to Biology Energy for synthesis and movement Energy transformation Enzymes and how they speed reactions Metabolism

More information

Models and Languages for Computational Systems Biology Lecture 1

Models and Languages for Computational Systems Biology Lecture 1 Models and Languages for Computational Systems Biology Lecture 1 Jane Hillston. LFCS and CSBE, University of Edinburgh 13th January 2011 Outline Introduction Motivation Measurement, Observation and Induction

More information

Cells to Tissues. Peter Takizawa Department of Cell Biology

Cells to Tissues. Peter Takizawa Department of Cell Biology Cells to Tissues Peter Takizawa Department of Cell Biology From one cell to ensembles of cells. Multicellular organisms require individual cells to work together in functional groups. This means cells

More information

arxiv: v1 [q-bio.nc] 18 Nov 2014

arxiv: v1 [q-bio.nc] 18 Nov 2014 Integration of rule-based models and compartmental models of neurons David C. Sterratt, Oksana Sorokina, and J. Douglas Armstrong School of Informatics, University of Edinburgh 1 Crichton St, Edinburgh

More information

Regulation of metabolism

Regulation of metabolism Regulation of metabolism So far in this course we have assumed that the metabolic system is in steady state For the rest of the course, we will abandon this assumption, and look at techniques for analyzing

More information

Organelle Structure and function

Organelle Structure and function Organelle Structure and function Organelles Molecules Cellular function Ch 5: Cells, the working units of life Ch 27: The origin and diversification of Eukaryotes Discussion Summary: Week 2 Cell Biology

More information

Introduction to Bioinformatics

Introduction to Bioinformatics Systems biology Introduction to Bioinformatics Systems biology: modeling biological p Study of whole biological systems p Wholeness : Organization of dynamic interactions Different behaviour of the individual

More information

Learning the collective dynamics of complex biological systems. from neurons to animal groups. Thierry Mora

Learning the collective dynamics of complex biological systems. from neurons to animal groups. Thierry Mora Learning the collective dynamics of complex biological systems from neurons to animal groups Thierry Mora Università Sapienza Rome A. Cavagna I. Giardina O. Pohl E. Silvestri M. Viale Aberdeen University

More information

dynamic processes in cells (a systems approach to biology)

dynamic processes in cells (a systems approach to biology) dynamic processes in cells (a systems approach to biology) jeremy gunawardena department of systems biology harvard medical school lecture 7 22 september 2016 weak linkage in molecular regulation PTM construct

More information

An Introduction to Metabolism

An Introduction to Metabolism An Introduction to Metabolism Chapter 8 Objectives Distinguish between the following pairs of terms: catabolic and anabolic pathways; kinetic and potential energy; open and closed systems; exergonic and

More information

Presentation Microcalorimetry for Life Science Research

Presentation Microcalorimetry for Life Science Research Presentation Microcalorimetry for Life Science Research MicroCalorimetry The Universal Detector Heat is either generated or absorbed in every chemical process Capable of thermal measurements over a wide

More information

Understanding Science Through the Lens of Computation. Richard M. Karp Nov. 3, 2007

Understanding Science Through the Lens of Computation. Richard M. Karp Nov. 3, 2007 Understanding Science Through the Lens of Computation Richard M. Karp Nov. 3, 2007 The Computational Lens Exposes the computational nature of natural processes and provides a language for their description.

More information

What I do. (and what I want to do) Berton Earnshaw. March 1, Department of Mathematics, University of Utah Salt Lake City, Utah 84112

What I do. (and what I want to do) Berton Earnshaw. March 1, Department of Mathematics, University of Utah Salt Lake City, Utah 84112 What I do (and what I want to do) Berton Earnshaw Department of Mathematics, University of Utah Salt Lake City, Utah 84112 March 1, 2008 Current projects What I do AMPA receptor trafficking Synaptic plasticity

More information

Oxford Surveys In Evolutionary Biology: Volume 1: 1984 READ ONLINE

Oxford Surveys In Evolutionary Biology: Volume 1: 1984 READ ONLINE Oxford Surveys In Evolutionary Biology: Volume 1: 1984 READ ONLINE If searched for the ebook Oxford Surveys in Evolutionary Biology: Volume 1: 1984 in pdf format, then you've come to the faithful site.

More information

REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR

REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR REQUIREMENTS FOR THE BIOCHEMISTRY MAJOR Grade Requirement: All courses required for the Biochemistry major (CH, MATH, PHYS, BI courses) must be graded and passed with a grade of C- or better. Core Chemistry

More information

Trophic Factors. Trophic Factors. History 2. History Growth Factors. Giles Plant

Trophic Factors. Trophic Factors. History 2. History Growth Factors. Giles Plant 217 - Growth Factors Giles Plant Role in: Growth and Trophic Factors Soluble/diffusible factors - polypeptides Proliferation Differentiation (ie Cancer) Survival (degenerative diseases) Innervation Maintenance

More information

Valentin Goranko Stockholm University. ESSLLI 2018 August 6-10, of 29

Valentin Goranko Stockholm University. ESSLLI 2018 August 6-10, of 29 ESSLLI 2018 course Logics for Epistemic and Strategic Reasoning in Multi-Agent Systems Lecture 5: Logics for temporal strategic reasoning with incomplete and imperfect information Valentin Goranko Stockholm

More information

Scientists have been measuring organisms metabolic rate per gram as a way of

Scientists have been measuring organisms metabolic rate per gram as a way of 1 Mechanism of Power Laws in Allometric Scaling in Biology Thursday 3/22/12: Scientists have been measuring organisms metabolic rate per gram as a way of comparing various species metabolic efficiency.

More information

Sophisticated Synapses: Modeling Synaptic Modulation by Astrocytes Suhita Nadkarni

Sophisticated Synapses: Modeling Synaptic Modulation by Astrocytes Suhita Nadkarni Sophisticated Synapses: Modeling Synaptic Modulation by Astrocytes Suhita Nadkarni Indian Institute of Science Education and Research Simple vs Complex Synapses are immensely complex - a large number

More information

The Environmental Smart Card

The Environmental Smart Card The Environmental Smart Card NIKOLA TESLA Alpha Waves in the human brain are between 6 and 8 Hz, the wave frequency in the human cavity, modulates between 6 and 8 Hz. All biological systems operate in

More information

CS885 Reinforcement Learning Lecture 7a: May 23, 2018

CS885 Reinforcement Learning Lecture 7a: May 23, 2018 CS885 Reinforcement Learning Lecture 7a: May 23, 2018 Policy Gradient Methods [SutBar] Sec. 13.1-13.3, 13.7 [SigBuf] Sec. 5.1-5.2, [RusNor] Sec. 21.5 CS885 Spring 2018 Pascal Poupart 1 Outline Stochastic

More information

Nature Chem. Nature Chem.

Nature Chem. Nature Chem. Life is one of the most complicated systems on the earth. To understand the living system, scientists have devoted their efforts in two different ways: (i) to control the living systems by chemicals and/or

More information

Advanced Fluorescence Microscopy I: Fluorescence (Foster) Resonance Energy Transfer

Advanced Fluorescence Microscopy I: Fluorescence (Foster) Resonance Energy Transfer Advanced Fluorescence Microscopy I: Fluorescence (Foster) Resonance Energy Transfer 3.0 Pax 2.5 2.0 1200 800 400 GFP- Pax GFP-Pax + FATmCherry FAT FAT 1.5 Lifetime (ns) 0 1500 2000 2500 3000 Average lifetime

More information

An Introduction to Metabolism

An Introduction to Metabolism An Introduction to Metabolism I. All of an organism=s chemical reactions taken together is called metabolism. A. Metabolic pathways begin with a specific molecule, which is then altered in a series of

More information

Rice/TCU REU on Computational Neuroscience. Fundamentals of Molecular Imaging

Rice/TCU REU on Computational Neuroscience. Fundamentals of Molecular Imaging Rice/TCU REU on Computational Neuroscience Fundamentals of Molecular Imaging June 3, 2008 Neal Waxham 713-500-5621 m.n.waxham@uth.tmc.edu Objectives Brief discussion of optical resolution and lasers as

More information

A Database of human biological pathways

A Database of human biological pathways A Database of human biological pathways Steve Jupe - sjupe@ebi.ac.uk 1 Rationale Journal information Nature 407(6805):770-6.The Biochemistry of Apoptosis. Caspase-8 is the key initiator caspase in the

More information

Bypass and interaction suppressors; pathway analysis

Bypass and interaction suppressors; pathway analysis Bypass and interaction suppressors; pathway analysis The isolation of extragenic suppressors is a powerful tool for identifying genes that encode proteins that function in the same process as a gene of

More information

Dendritic computation

Dendritic computation Dendritic computation Dendrites as computational elements: Passive contributions to computation Active contributions to computation Examples Geometry matters: the isopotential cell Injecting current I

More information

Neurogranin Controls the Spatiotemporal Pattern of Postsynaptic Ca 21 /CaM Signaling

Neurogranin Controls the Spatiotemporal Pattern of Postsynaptic Ca 21 /CaM Signaling 3848 Biophysical Journal Volume 93 December 2007 3848 3859 Neurogranin Controls the Spatiotemporal Pattern of Postsynaptic Ca 21 /CaM Signaling Yoshihisa Kubota,* John A. Putkey, y and M. Neal Waxham*

More information

PHARMACOLOGY G PROTEIN COUPLED RECEPTORS

PHARMACOLOGY G PROTEIN COUPLED RECEPTORS PHARMACOLOGY G PROTEIN COUPLED RECEPTORS Edited by Richard R. Neubig Department of of Michigan Medical School Ann Arbor, Michigan, USA Serial Editor S. J. Enna Department of Molecular and Integrative Physiology

More information

13-3. Synthesis-Secretory pathway: Sort lumenal proteins, Secrete proteins, Sort membrane proteins

13-3. Synthesis-Secretory pathway: Sort lumenal proteins, Secrete proteins, Sort membrane proteins 13-3. Synthesis-Secretory pathway: Sort lumenal proteins, Secrete proteins, Sort membrane proteins Molecular sorting: specific budding, vesicular transport, fusion 1. Why is this important? A. Form and

More information

Activation of a receptor. Assembly of the complex

Activation of a receptor. Assembly of the complex Activation of a receptor ligand inactive, monomeric active, dimeric When activated by growth factor binding, the growth factor receptor tyrosine kinase phosphorylates the neighboring receptor. Assembly

More information

Dendrites - receives information from other neuron cells - input receivers.

Dendrites - receives information from other neuron cells - input receivers. The Nerve Tissue Neuron - the nerve cell Dendrites - receives information from other neuron cells - input receivers. Cell body - includes usual parts of the organelles of a cell (nucleus, mitochondria)

More information

Outline. The ensemble folding kinetics of protein G from an all-atom Monte Carlo simulation. Unfolded Folded. What is protein folding?

Outline. The ensemble folding kinetics of protein G from an all-atom Monte Carlo simulation. Unfolded Folded. What is protein folding? The ensemble folding kinetics of protein G from an all-atom Monte Carlo simulation By Jun Shimada and Eugine Shaknovich Bill Hawse Dr. Bahar Elisa Sandvik and Mehrdad Safavian Outline Background on protein

More information

The sense of smell Outline Main Olfactory System Odor Detection Odor Coding Accessory Olfactory System Pheromone Detection Pheromone Coding

The sense of smell Outline Main Olfactory System Odor Detection Odor Coding Accessory Olfactory System Pheromone Detection Pheromone Coding The sense of smell Outline Main Olfactory System Odor Detection Odor Coding Accessory Olfactory System Pheromone Detection Pheromone Coding 1 Human experiment: How well do we taste without smell? 2 Brief

More information

The University of Jordan. Accreditation & Quality Assurance Center. COURSE Syllabus

The University of Jordan. Accreditation & Quality Assurance Center. COURSE Syllabus The University of Jordan Accreditation & Quality Assurance Center COURSE Syllabus 1 Course title Principles of Genetics and molecular biology 2 Course number 0501217 3 Credit hours (theory, practical)

More information

Lecture 2: mrna localisation and decay in cells and in tissues

Lecture 2: mrna localisation and decay in cells and in tissues Lecture 2: mrna localisation and decay in cells and in tissues Prof. Ilan Davis, Department of Biochemistry. Senior Research Fellow, Jesus College ilan.davis@bioch.ox.ac.uk http://www.ilandavis.com References

More information

Course Descriptions Biology

Course Descriptions Biology Course Descriptions Biology BIOL 1010 (F/S) Human Anatomy and Physiology I. An introductory study of the structure and function of the human organ systems including the nervous, sensory, muscular, skeletal,

More information

Undergraduate Curriculum in Biology

Undergraduate Curriculum in Biology Fall Courses *114: Principles of Biology *116: Introduction to Anatomy and Physiology I 302: Human Learning and the Brain (o, DS) 336: Aquatic Biology (p/e) 339: Aquatic Biology Lab (L) 351: Principles

More information

CHAPTER 2 THE CHEMICAL BASIS OF LIFE

CHAPTER 2 THE CHEMICAL BASIS OF LIFE CHAPTER 2 THE CHEMICAL BASIS OF LIFE CHAPTER OVERVIEW This chapter introduces very basic concepts of chemistry, emphasizing the structure of atoms and how they combine (form bonds). The types of bonds,

More information

Analysis of non-olfactory sensory pathways that are necessary for the olfactory associative learning of the Drosophila mushroom body

Analysis of non-olfactory sensory pathways that are necessary for the olfactory associative learning of the Drosophila mushroom body 15 12601 B 2009 2011 21300117 Analysis of non-olfactory sensory pathways that are necessary for the olfactory associative learning of the Drosophila mushroom body ITO, Kei 00311192 The mushroom body is

More information

PIMS/Fields/CRM Graduate Math Modelling in Industry Workshop. Winnipeg, MB. Project Descriptions

PIMS/Fields/CRM Graduate Math Modelling in Industry Workshop. Winnipeg, MB. Project Descriptions PIMS/Fields/CRM 2017 Graduate Math Modelling in Industry Workshop Winnipeg, MB Project Descriptions Project 1: Reconciling potential and effective air travel data Mentor: Dr. Julien Arino Description:

More information

What Organelle Makes Proteins According To The Instructions Given By Dna

What Organelle Makes Proteins According To The Instructions Given By Dna What Organelle Makes Proteins According To The Instructions Given By Dna This is because it contains the information needed to make proteins. assemble enzymes and other proteins according to the directions

More information

Chemical Exchange and Ligand Binding

Chemical Exchange and Ligand Binding Chemical Exchange and Ligand Binding NMR time scale Fast exchange for binding constants Slow exchange for tight binding Single vs. multiple binding mode Calcium binding process of calcium binding proteins

More information

Enzyme Enzymes are proteins that act as biological catalysts. Enzymes accelerate, or catalyze, chemical reactions. The molecules at the beginning of

Enzyme Enzymes are proteins that act as biological catalysts. Enzymes accelerate, or catalyze, chemical reactions. The molecules at the beginning of Enzyme Enzyme Enzymes are proteins that act as biological catalysts. Enzymes accelerate, or catalyze, chemical reactions. The molecules at the beginning of the process are called substrates and the enzyme

More information

Protein Folding In Vitro*

Protein Folding In Vitro* Protein Folding In Vitro* Biochemistry 412 February 29, 2008 [*Note: includes computational (in silico) studies] Fersht & Daggett (2002) Cell 108, 573. Some folding-related facts about proteins: Many small,

More information