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SBOC-2020

Syllabus

Biomedical Engineering 580.248

Systems Biology of the Cell

Spring 2020

(2 credits, EN)

URL

  • Main Lecture: See Blackboard
  • Discussion Sections: See Blackboard

Perusall Code

Syllabus with dates

Description

Systems Biology of the Cell (580.429 SB3) is a half-semester course required of all BME majors. Progress in biomedicine requires understanding how individual cellular components function together. Cell and tissue engineers can exploit this knowledge for regenerative medicine. Basic researchers need to understand how failures of individual components, for example due to mutation, lead to disease. This course provides the fundamental tools that you will need to develop and apply quantitative models of cellular systems, including protein signal transduction, gene regulation, metabolism, and large-scale network science.

Instructor

Prof. Joel S. Bader, joel.bader at jhu.edu, www.baderzone.org

Office: Wyman 407; Miller Research Building 319

Office hours: Tuesday and Thursday after lecture

Teaching Assistants

  • Tejasvi Desai
  • Wen Jian
  • Jessica Kasamoto
  • Michael Lan

Responsibilities:

  • Help students learn the material.
  • Lead Discussion Sections. Discussions should cover questions about future HW, solutions to previous HW, and preparation and solutions for exams.
  • Provide main lecture when required.
  • Hold office hours.
  • Proofread notes, homeworks, quizzes, and exams.
  • Print, proctor, and grade single-sided quizzes and exams.
  • Produce answer keys for homeworks, quizzes, and exams.
  • Wrangle graders for homeworks.
  • Return graded work during Discussion Section, not main lecture.
  • Print single-sided exams, repeated because double-sided does not provide sufficient space for answers. Students often require the back of the page for additional work space.

Meetings

Lectures: Tuesday and Thursday, 10:30 – 11:45 AM,  Zoom and Arellano Theater

Sections

  1. Friday 11 – 11:50 AM, Gilman 119
  2. Friday 12 – 12:50 PM, Hodson 216
  3. Friday 3 – 3:50 PM, Hodson 216
  4. Friday 4:30 – 5:20 PM, Hodson 216
  5. Friday 9 – 9:50 AM, Hodson 216

TA Office Hours

  • To be announced

Coffee Breaks

  • To be scheduled

Textbook

The textbook is available through this website under password control.

Homeworks

Homework assignments appear at the end of book chapters.

Quizzes

  • Quizzes may be scheduled but are unlikely.

Exams

  • One midterm.
  • One final exam.
  • An equation page will be provided for each exam. Exams are closed book, closed notes, no electronics. Only pencils, pens, and paper.
  • Here is the equation sheet: sboc-equationsheet-2019

Course Improvements

  • 2013: first edition of PDF collected hand-written notes
  • 2016: first edition of LaTeX course textbook
  • 2017: homework assignments integrated into textbook chapters
  • 2018: selected chapters for a new half-semester course
  • 2020: Remote instruction

On-line material

Signal processing by the HOG MAP kinase pathway, Hersen et al. 2008 PNAS. PNAS-2008-Hersen-7165-70.

Square wave (SM2):

Response:

Caffeine Signaling Involvement of DARPP-32 phosphorylation in the stimulant action of caffeine. Maria Lindskog et al. 2002 Nature

Caffeine News and Views commentary Vaugeois 2002 Nature

Structural basis of DNA recognition: Glucocorticoid receptor zinc finger, Fos-Jun leucine zipper heterodimer with NFAT1, NFKB p50/p65 beta sheet immunoglobulin fold

Eric Davidson’s gene regulatory network model for sea urchin embryonic development Isabelle S. Peter, Emmanuel Faure, Eric H. Davidson. Predictive computation of genomic logic processing functions in embryonic development. PNAS 2012.

Toggle switch. Nature 403, 339-342 (20 January 2000) | doi:10.1038/35002131; Construction of a genetic toggle switch in Escherichia coli. Timothy S. Gardner (then helped found Amyris), Charles R. Cantor & James J. Collins

A synthetic oscillatory network of transcriptional regulators Michael B. Elowitz & Stanislas Leibler. Nature 403, 335-338 (20 January 2000)
Video from the Elowitz website.

Youtube repressilator

Edge detector. Jeffrey J. Tabor, Howard M. Salis, Zachary Booth Simpson, Aaron A. Chevalier, Anselm Levskaya, Edward M. Marcotte, Christopher A. Voigt, Andrew D. Ellington, A Synthetic Genetic Edge Detection Program, Cell, Volume 137, Issue 7, 26 June 2009, Pages 1272-1281, ISSN 0092-8674, http://dx.doi.org/10.1016/j.cell.2009.04.048.

A fast, robust and tunable synthetic gene oscillator. Stricker J, Cookson S, Bennett MR, Mather WH, Tsimring LS, Hasty J. Nature. 2008 Nov 27;456(7221):516-9. doi: 10.1038/nature07389. Epub 2008 Oct 29. PubMed PMID: 18971928.

Synchronized clocks. A synchronized quorum of genetic clocks. Nature 463, 326-330 (21 January 2010). Tal Danino, Octavio Mondragón-Palomino, Lev Tsimring & Jeff Hasty

Li GW, Xie XS. Central dogma at the single-molecule level in living cells. Nature. 2011 Jul 20;475(7356):308-15. doi: 10.1038/nature10315. Review. PubMed PMID: 21776076; PubMed Central PMCID: PMC3600414.

Taniguchi Y, Choi PJ, Li GW, Chen H, Babu M, Hearn J, Emili A, Xie XS. Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. Science. 2010 Jul 30;329(5991):533-8. doi: 10.1126/science.1188308. Erratum in: Science. 2011 Oct 28;334(6055):453. PubMed PMID: 20671182; PubMed Central PMCID: PMC2922915.

Eldar A, Elowitz MB. Functional roles for noise in genetic circuits. Nature. 2010 Sep 9;467(7312):167-73. doi: 10.1038/nature09326. Review. PubMed PMID: 20829787.

Prerequisites

Calculus 1/2 (AS.101.106/AS.101.107)

Linear Algebra and Differential Equations (AS.101.201/AS.101.302 or EN.550.291)

Introduction to Probability and Statistics (EN.550.310)

Introduction to Programming (facility with numerical programming, simulation, and exploratory data analysis in a language of your choice)

Cellular and Molecular Biology (EN.580.221)

Signals, Systems, and Control (EN.580.222)

All prerequisites may be satisfied by an equivalent course or by the instructor’s permission.

Online Resources

… are on this page. Please login to Blackboard to upload homeworks and for grade center.

Course Objectives

  1. Understand the mathematics behind linear systems theory, including spectral transforms and linear operators. Apply linear systems theory to predict cellular behavior close to equilibrium.
  2. Understand what constraints cause cells to behave non-linearly, and how non-linearity affects cellular response, including cooperativity.
  3. Understand why non-deterministic behavior is important in biology. Develop and apply mathematical models to describe equilibrium fluctuations. Understand how equilibrium fluctuations and correlations predict non-equilibrium response. Understand quantitatively how stochastic phenomena are essential for patterning specific tissues.
  4. Understand tempero-spatial dynamics that are driven by diffusion. Understand the mathematics behind the diffusion equation. Develop a physical understanding of the relationship between time and distance in diffusive motion. Understand different methods by which diffusive processes create tissue-scale spatial patterns in development.
  5. (Bonus material in the textbook but not part of the half-semester course.) Use networks as a model to unify studies of complex systems of genes, cells, and organisms. Understand concepts of network percolation and giant component and their relevance to disease and information spread. Understand how diffusion creates a distance metric for networks. Understand the relationship between graph diffusion and graph clustering. Understand the meaning of small-world and scale-free when applied to networks. Understand the representation of metabolism as a reaction network. Apply optimization methods to predict how cells optimize their internal state for the environment.

Course Topics

  1. Cells as linear systems. Linear systems theory. Spectral transforms. Reverse engineering linear systems. Protein signal transduction.
  2. Cells as non-linear systems. Thresholds and ultra-sensitivity. Analog-digital converters. Information theory and gene transcription. Coupled dynamics of transcription and translation. Amplifiers, logic gates, feedback control, oscillators.
  3. Cells as stochastic systems. Non-deterministic behavior. Noise in transcription and translation. Delta-Notch patterning.
  4. Cells as spatial systems. Spatial patterning of tissues. Morphogen diffusion. Diffusion kernels.
  5. (Not in the half-semester course.) Networks of genes, cells, and organisms. Disease propagation on a network. Small-world and scale-free networks. Motifs. Clustering. Metabolic networks and metabolic optimization.

Course Expectations & Grading

Each homework and quiz is generally worth 10 points. In-class exams are worth about 40-50 points, and the final exam will be worth about 80-100 points. Course grades will be determined by summing the total points and dividing by the total possible points minus 10. This allows each student to drop one assignment without a grading penalty. This also permits students to miss quizzes for travel to BMES and other conferences, medical school and graduate school interviews, and other events.

Homework assignments are generally due by upload to Blackboard by 11:59 PM on the date due, usually Friday. Late homeworks are not accepted.

Quizzes will be announced at least one main lecture in advance and will be given during the main lecture at the end of the period.

Exam dates are on the syllabus. Usually a single make-up exam date will be scheduled for each exam.

If you must be absent for an academic or professional reason, including BMES or other conferences, medical school or graduate school interviews, or other on-site interviews, please speak to me ahead of time. You must speak to me ahead of time if an absence conflicts with a quiz or exam date.

If you are absent for a non-academic reason, primarily health-related, please have the Dean of Students email me on your behalf.

Ethics

The strength of the university depends on academic and personal integrity. In this course, you must be honest and truthful. Ethical violations include cheating on quizzes and exams, plagiarism, reuse of assignments, improper use of the Internet and electronic devices, unauthorized collaboration, alteration of graded assignments, forgery and falsification, lying, facilitating academic dishonesty, and unfair competition.

In addition, the specific ethics guidelines for this course are:

  • Homework: students are permitted to work in groups and to use external resources in preparing homework assignments for this course. Each student must turn in a separate physical or electronic copy of each homework, however, to assist with study and record keeping.
  • Study materials: all study materials are generally permitted. Advance copies of current-year quiz and exam questions are not permitted, however. Students taking exams at different times, particularly for make-up exams, may not share information.
  • Quizzes, exams, and the final: only blank paper, pens, and pencils are permitted. Electronic devices, including calculators, phones, and computers, are strictly forbidden. Equation sheets, if necessary, will be provided in the exam itself.

Report any violations you witness to the instructor.

You can find more information about university misconduct policies on
the web at these sites:

Students with Disabilities

Any student with a disability who may need accommodations in this class must obtain an accommodation letter from Student Disability Services, 385 Garland, (410)
516-4720, studentdisabilityservices@jhu.edu.

Students requiring extra time for exams will be permitted to take exams at the SDS Testing Center. Exam times will be selected to overlap with the main lecture if possible, either starting early or finishing late.

A note-taker may be assigned to the course if required.

ABET Outcomes

  • Ability to apply mathematics, science and engineering principles (a).
  • Ability to design and conduct experiments, analyze and interpret data (b).
  • Ability to design a system, component, or process to meet desired needs (c).
  • Ability to function on multidisciplinary teams (d).
  • Ability to identify, formulate and solve engineering problems (e).
  • Understanding of professional and ethical responsibility (f).
  • Ability to communicate effectively (g).
  • The broad education necessary to understand the impact of
    engineering solutions in a global and societal context (h).
  • Recognition of the need for and an ability to engage in life-long learning (i).
  • Knowledge of contemporary issues (j).
  • Ability to use the techniques, skills and modern engineering
    tools necessary for engineering practice (k).
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