Prof. Isaac BARJIS
LEARNING OBJECTIVES Upon completion of the course, students will be able to demonstrate:
LEARNING OBJECTIVES Upon completion of the course, students will be able to demonstrate:
Mastery of basic techniques used in the modeling of biomolecular systems;
Fluency in translating biological ideas into mathematical models and mathematical meaning into their respective biological expressions;
Ability to analyze performance and scalability in MD simulations.
ASSESSMENT OF SPECIFIC LEARNING OUTCOMES
LEARNING OUTCOMES ASSESSMENT
Differentiate between stochastic, discrete and continues models
Evaluation of narrative in the research paper, short answer quizzes, and exam questions.
65 Critically evaluate biological process and be
able to model and analyse a given biological process.
Evaluation of narrative in the project design, essay type biweekly take home assignment , and exam questions
Use www to predict protein 3-D structure Semester long research project where students will pick a specific sequence from the protein family (available at www) and model the structure of that sequence using the techniques and tools you acquired during the course (tools are available at www).
Critically evaluate challenges faced in prediction of protein structures
Essay type biweekly take home assignment, short answer quizzes and exams. Evaluation of data and the narrative in the research paper Learn rules for efficient design and modeling
of biological process/system biology
Essay type biweekly take home assignment and evaluation of research project.
Critically analyze and interpret data obtained from a model
Conduct a literature survey using refereed journals and other sources of scientific information and evaluate their reliability.
Incorporate the concepts taught in the lecture into bi-weekly assignments and semester long project.
Ability to write a research paper following a peer reviewed journal format
Evaluation of the assignments and project using rubric; Essay type biweekly take home assignment.
Formulate and plan a project report and write research paper using appropriate experimental data, correct scientific language, spelling and grammar; written in a clear, concise, logical and accurate manner,
Evaluation of Essay type biweekly take home assignment and semester long project using rubric.
TOPICAL LECTURE OUTLINE
Week Lecture
1 Introduction. What is a model? Why are models useful? Modeling approaches and pitfalls.
2 The modeling process: Mathematical methods; Computer models and automata theory; representation of system biology as a model.
66 3 Discrete Models
4 Continuous Models
Exam 1
5 Molecular Mechanical Force Field: Quantum mechanics; Empirical force field;
statistical potential (flexible); molecular mechanics 6
Statistical Potentials: Knowledge based potential; potential of mean force;
atomic potential; protein-protein binding potential; protein –DNA statistical binding potential
7
Conformational Analysis: conformation search; systematic search (grid search); random search; clustering; search of global minimum
Exam 2 8
Computer simulation: Time averages and ensemble averages; calculation of simple thermodynamic properties (energy, heat capacity, pressure, temperature); practical aspect of computer simulations; predict boundary conditions;
9 Monte Carlo simulation: introduction; canonical ensemble; simple Monte Carlo; Metropolis method; models used in polymers
10
• Molecular Dynamics Simulation: Overview; effect of time step on properties;
setting up and running simulation; equilibration and production; time dependent properties; problem with cutoffs
11
Structure Modeling: Protein structure; Secondary structure prediction; protein folding;
Exam 3
12 Structure Modeling: Protein folding and unfolding; Tertiary structure prediction; Homology modeling; fold recognition
13 Protein interactions: Interaction modeling (docking); docking procedure; need for refinement; residual-based potential;
14 Computational drug design
15 Exam 4 (Final Exam)
GRADING PROCEDURE:
5. 4 exams = 60% (each exam will be 15 % of final grade) 6. Project* = 20 %
7. Weekly and biweekly assignments = 10%
8. Participation*** = 10%
*Project:
This is a semester long project. At the beginning of the semester each student will pick a protein family from the list of available protein families. Then the student will use www to obtain the sequence and other information of given protein. By the end of the semester, the student should be able to model the structure of that sequence using the techniques and tools they acquired during the course and complete a full report on the particular protein family. Students will use
67 internet resources as well as computational tools covered in class to cover some of the following areas:
Protein stability
Conformational changes
Protein structure prediction
Protein interaction prediction
Structure-based function prediction
Molecular dynamics simulations
Monte Carlo simulations
Below is a list of topics/steps final project should contain. Students are supposed to follow all of those steps to complete the project. Each of the steps depends on the previous ones, for example alignment you are going to use to accomplish homology modeling has to be in correlation with the secondary structure prediction and fold recognition, i.e. step 3 should rely on steps 1 and 2.
1. Secondary structure prediction 2. Fold recognition
3. Homology modeling 4. Docking
5. Structure based function prediction
***Participation
Participation is key to making the experience of everyone a pleasant one. However participation does not just mean that student should be present, but it means that the student should:
Reviews all course sections and completes all weekly and biweekly assignments on a timely basis,
Ask questions about the topic and evaluate the topic presentations.
Actively and interactively participate in each lecture’s discussion in the classroom and online. This requirement applies to students whether they are taking the course online or face to face.
68 CURRICULUM PROPOSAL – NEW COURSES AND PROGRAMS
LIBRARY RESOURCES & INFORMATION LITERACY Please complete this form for all new courses/programs and major changes to existing courses/programs. The information you provide will assist the library in planning for new acquisitions; this information will not affect course or program proposals either positively or negatively.
Consult with library faculty subject selectors early in the planning of course proposals. This will ensure enough time to allocate budgets if materials need to be purchased.
Find the library faculty subject selector for your department here:
http://library.citytech.cuny.edu/about/faculty/subject.php Course proposer: please complete boxes 1-5.
Library faculty subject selector: please complete box 6.
#1
Title of proposal
MOLECULAR MODELING IN BIOLOGY
Department/Program
Department of Biological Sciences Program in Biomedical Informatics Department Chairperson/Coordinator
Dr. Walied Samarrai
Expected date course(s) will be offered Fall of 2013
# of students 20
Proposed by Isaac Barjis
[email protected] (718)260-5285
Date 09/07/11
#2
Brief description of course(s) and/or program
This course covers the applications of computer modeling and simulation to problems involving biological macromolecules. The targeted areas are in protein structure modeling, structure-based drug design, drug screening, cheminformatics, and intermolecular interactions and binding. Students will learn the theory and algorithms underlying a variety of simulation techniques.
Prerequisites: BIO 3350
#3
Are City Tech library resources sufficient for course assignments? Please elaborate.
New books on healthcare database should be obtained
69 3. Molecular modeling. by Andrew R. Leach. Prentice Hall. 2nd ed. (2001)
4. Modeling Biological Systems: Principles and applications, by Haefner James W, Springer Publisher, 2nd ed. 2005.
#4
Are additional resources needed for course assignments? No Books / journals
Electronic books
Databases and other electronic resources Multimedia (DVDs, CDs, CD-ROMs, etc.) Other
Please include author, title, publisher, edition, date and price.
#5
Library faculty focus on strengthening students' information literacy skills in finding, evaluating, and ethically using information. We are available to collaborate with instructors regarding development of assignments, and to provide customized information literacy instruction and research guides for your course.
Do you plan to consult with the library faculty subject specialist for your area?
Please give details.
Yes – a project presentation would require literature and www search.
#6
Library Faculty Subject Selector___ Songqian Lu ____________________
Comments and Recommendations
The proposal for Mathematical Modeling of Biomolecular Systems and the related library resources have been reviewed.
The requested books for this new course will be acquired by the library.
City Tech library in recent years has expanded its electronic collections. The library encourages students and instructors take advantage of the rich databases and e-book collections for their learning and teaching needs.
The library faculty will be available to work with instructors and to provide information literacy instruction and customized research workshop to students.
Date: January 20, 2012.
70 Section AIV: New Courses
CHANCELLOR’S REPORT FORM FOR NEW COURSES AIV.1. Department: BIOLOGICAL SCIENCES
Course Number: MED 3910
Title: INTERNSHIP/RESEARCH IN BIOMEDICAL INFORMATICS Hours: total of 225 field hours, spread throughout the semester Credits: 5 credits
Prerequisites: MED 4229, BIO 3352, enrollment in the Biomedical Informatics Program with minimum GPA of 2.5 in required program courses, and permission of program coordinator.
Corequisites: none
Course Description: An internship/research course that exposes majors to the practice of medical informatics and molecular bioinformatics in commercial, research, and medical settings.
Rationale: Training in Biomedical Informatics, the proposed BS program, is not complete without a demonstrated application of the knowledge, skills, and values accumulated throughout the 4 years of undergraduate study. This course is the venue for this demonstration. Through this internship/research course, students will have an opportunity to examine the kinds of career opportunities available to them, and evaluate them in terms of their own interests. Students will gain practical experience in the growing field, whether in an internship or research setting, in an intensive exposure to real-world environments. This experience will give an advantage to our students as they seek employment or higher degrees after graduation. Finally, the requirement to write a report and make an oral presentation at the end of the course should reinforce general education skills that are critical in today’s job market.
71 NEW COURSE PROPOSAL
INTERNSHIP/RESEARCH IN BIOMEDICAL INFORMATICS Prepared By: Prof. Armando D. Solis
NEW YORK CITY COLLEGE OF TECHNOLOGY
The City University Of New York
School of Arts and Sciences Biological Sciences Department
Course Information
Course title: Internship/Research in Biomedical Informatics Course code: MED 3910
Credit Hours: 5 credit hours
225 field hours total, spread throughout the semester or during the summer (for summer internships).
Prerequisites: MED 4229, BIO 3352, enrollment in the Biomedical Informatics Program with minimum GPA of 2.5 in required program courses, and permission of program coordinator.
Text: Selected by course coordinator and/or project supervisor to support chosen project.
Course Summary: An internship/research course that exposes majors to the practice of medical informatics and molecular bioinformatics in commercial, research, and medical settings.
Grading Procedure
Research plan 15%
Student journal &
midterm progress report 20%
Supervisor evaluation 30%
Written report 20%
Oral presentation 15%
Proposer Information
Name: Armando D. Solis, Ph.D.
Phone: (718) 260-5894
Email: [email protected]
72