IQB Ph.D. Curriculum

The Quantitative Biomedicine curriculum is intended to provide the foundation upon which to build a personalized education and research path in any of the myriad of areas in Quantitative Biomedicine. The interdisciplinary curriculum is custom-designed to provide a knowledge base that will promote the student's scientific and research goals, with the intent of enabling the student to work on some projects collaboratively with scientists of different backgrounds.

Among the special course and workshop offerings are:

  1. Courses that address such areas as mathematical and computational techniques in biology, structural biology, bioinformatics, statistics, quantitative modeling in biology, data mining and pattern recognition, biophysics, and physical biochemistry
  2. Transition courses that will provide a valuable educational introduction for students from: A number of interdisciplinary seminar series, workshops, and visitor programs focused on current developments at the frontiers of biomedical research
    1. the quantitative sciences, with little or no previous background in the biological sciences, to relevant areas of chemistry, biochemistry, and biology
    2. the biological sciences, with little or no previous background in the more quantitative sciences, to relevant areas of mathematics, statistics, physics, and computer science
  3. Annual Winter and Summer Interdisciplinary Quantitative Biology Boot Camps designed to augment the education for students coming from all areas of science. The boot camps are immersive one- or two-week programs offered between semesters that provide broad introductory exposure to the language and the experimental/theoretical underpinnings of molecular biology, macromolecular biochemistry/biophysics, structural biology, computational biology, systems biology, and bioinformatics. The topics of the boot camps vary to address diverse current areas of inquiry, consisting of lectures on fundamental aspects of biology, a broad range of collaborative hands-on practical exercises, tours of some of Rutgers' (and, in some cases, outside) state-of-the-art facilities for interrogating biological phenomena, daily career training sessions, fun activities for relaxing at multiple points each day, and a culminating symposium or presentation organized and provided by the students.
  4. Outside courses may be taken at numerous other universities that are part of the inter-university doctoral consortium. Rutgers credits are used to pay for these courses.

The course requirements are as follows (detailed further in the QB Handbook).

Year 1

Semester 1: 1 course from each Track (A, B, C) and the Seminar in Quantitative Biomedicine 
 
TRACK A: Physics and Chemistry of Living Matter       
Biophysical Chemistry I  16:160:537  (3 cr)  Put all credit info in parentheses; same with in Handbook
Computational Chemistry 16:160:579:04  (3 cr)  
 
TRACK B: Data, Computation, and Statistics
1. A Computer Science Master’s level course or the equivalent (by arrangement with the Graduate Program Director or Associate Director in QB)
Introduction to Artificial Intelligence  16:198:520  (3 cr)
Python Methodologies  16:137:552  (3 cr) 
2. A Statistics course:
A course in Statistics, by arrangement with the Graduate Program Director in Statistics and Biostatistics
Or
Bayesian Analysis  16:215:571  (3 cr)
3. A Bioinformatics course: 
UNDERGRADUATE:
Evolutionary Genetics 01:447:486  (3 cr if do extra project)   
GRADUATE:
Introduction to Biological Databases and Data Archiving 16:848:509  (3 cr)
Clinical Research Informatics  16:137:580  3 cr
Bioinformatics: Tools for Genomic Analysis/Tools for Bioinf. Analysis 16:137:617  (3 cr)
Fundamentals of Analytics and Discovery Informatics  16:137:550  (3 cr)
Bioinformatics 16:765:585:01  (3 cr)
 
TRACK C: Quantitative Modeling in Biology      
Dynamical Models in Biology  16:848:504  (3 cr)
Conversational Mathematical Modeling  11:216:458  (3 cr)       
Mathematical Modeling for Biomedical Engineering  16:125:501  (3 cr)        
An applied math modeling course (by arrangement with the Graduate Program Director or Associate Director in QB)
 
Seminar in Quantitative Biology: 16:848:616:01  (1 cr) . Required a total of 6 times during graduate school.
 
Semester 2: 2 courses from Track A or B or C and 1 course from a different Trackand the Seminar in QB
 
TRACK A: Physics and Chemistry of Living Matter                   
        Physics of Living Matter  16:1848:617:01  (3 cr)
        Biophysical Chemistry II  16:160:538   (3 cr)
 
TRACK B: Data, Computation, and Statistics
1. A Computer Science Master’s level course or the equivalent (by arrangement with the Graduate Program Director or Associate Director in QB)
Introduction to Artificial Intelligence  16:198:520  (3 cr)
Python for Data Science  16:137:603  (3 cr)
2. A Statistics course:
A course in Statistics, by arrangement with the Graduate Program Director in Statistics and Biostatistics
3. A Bioinformatics course: 
UNDERGRADUATE:
Quantitative Biology & Bioinformatics  01:447:302  (3 cr if do extra project)
Computational Genetics of Big Data  01:447:303  (3 cr if do extra project)
Genome Evolution  01:447:352  (3 cr if do extra project)  
Conversational Mathematical Modeling 11:216:458  (3 cr if do extra project)      
Fundamentals of Genomics  11:216:465  (3 cr if do extra project)
GRADUATE:
Microbiology and Human Health - being developed - (3 cr)
Computer Integrated Interventions in Medicine 16:125:623 (3 cr)
Bioinformatics: Tools for Genomic Analysis  16:137:617  (3 cr)  
Fundamentals of Analytics and Discovery Informatics  16:137:550  (3 cr)  
Introduction to Cloud and Big Data Systems  16:137:602  (3 cr)
Tools for Bioinformatic Analysis  16:137:617  (3 cr)
 
TRACK C: Quantitative Modeling in Biology       
Dynamical Models in Biology  16:848:504  (3 cr)  (Note: offered occasionally)
Mathematics of Cancer  01:640:459  (3 cr)  (Note: not always offered; extra work required for graduate credit)
Discreet and Probabilistic Models in Biology  01:640:338  (3 cr) (Note: extra work required for graduate credit)
Mathematical Modeling for Biomedical Engineering  16:125:501  (3 cr)
An applied math modeling course (by arrangement with the Graduate Program Director or Associate Director in QB)
 
Seminar in Quantitative Biology: 16:848:616:01  (1 cr)  
 
   Winter Session of any Year(s) in Graduate School:
Interdisciplinary Quantitative Biology Boot Camp  16:848:615  (2 cr)
 
   Summer Session of any Year(s) in Graduate School:
        Interdisciplinary Quantitative Biology Boot Camp  16:848:615  (2 X 1 cr)
 

 

Year 2

Seminar in Quantitative Biomedicine (2 X 1 cr): 16:848:616:01, Fall and Spring
Topics in Quantitative Biomedicine (2 X 1 cr): being developed, Fall and Spring
Molecular Medicine  16:848:XXX: being developed
Ethical Conduct in Scientific Research: available in most science- or engineering-oriented graduate programs.
Responsible and Ethical Research I: 16:486:501 (0 cr)
Introduction to Research: 16:160:603  (1 cr)
Ethical Scientific Conduct: 16:115:556  (1 cr)   
Specialized electives course(s) (≥1 credit in a relevant area of study):  This may consist of regular courses, mini-courses, or other approved entities.
 
A. Examples of mini-courses in Molecular Biosciences (16:695:622-635):
The Cilium, Organelle of the 21st Century
Cancer and Clinical Oncology
Cancer Genes and Cells
Evolution of Emerging Viruses
Noncoding Regulatory RNA
Toll-Like Receptors in Health and Disease
Molecular Biology of Cancer
P53
Understanding of the Ubiquitin/Proteasome System and its Involvement in Disease
Neural Circuit Microscopy
Pluripotent and Somatic Stem Cells
Regenerative Medicine - Stem Cell Therapy
Neurodevelopmental Disorders
Genetic Systems and Structures
Genetics and Cell Biology of Fertilization
 
B. Examples of regular courses of possible interest:
Fundamentals of Molecular Biosciences  16:695:538  (6 cr)
Experimental Methods in Molecular Biosciences  16:695:539  (2 cr)
Molecular Biology of Cells  16:148:514  (3 cr)
Molecular Biology and Biochemistry  16:115:511/512 and 16:694:407/408  (3 cr)
Biochemistry  16:115: 503 or 504  (4 cr)
Molecular Basis of Physiology  16:761:580  (3 cr)
Genetic Systems and Structures 16:848:617:02  (3 cr)
Human Genetics 16:681:535  (3 cr)
Cancer  01:447:495  (3 cr)
Cell & Molecular Pharmacology: Principles of Drug Action and Targeting  16:718:680  (3 cr)
Drug Delivery: Fundamentals and Applications  16:125:590  (3 cr)
Introduction to Applied Mathematics  01:640:321  (3 cr)
Biocontrol, Modeling and Computation  16:125:572  (3 cr)
Thermal Physics  01:750:351  (3 cr)
Quantum Mechanics and Atomic Physics 01:750:361  (3 cr)
Advanced Topics in Statistical Mechanics and Biological Physics  16:750:677  (3 cr)
Physical Chemistry: Biochemical Systems  01:160:341 or 342  (3 cr)
Concepts in Nanochemistry  16:160:579:01  (3 cr)
Computational Chemistry  16:160:579:04  (3 cr)
Chemical Thermodynamics  16:160:525  (3 cr)
Thermodynamics and Kinetics  16:160:541:01  (3 cr)
Structural Biology, Structural Biophysics and Chemical Biology of Transcription/Structural
Biology/Biophysics  16:160:580  (3 cr)         
Communicating Science  16:718:560  (0 cr)
Graduate Writing  16:355:502 (0 cr)

Year 3

Semester 1 :
Seminar in Quantitative Biology: 16:848:616:01  (1 cr)
Semester 2:
Seminar in Quantitative Biology: 16:848:616:01  (1 cr)