Genetics Courses

• Semester Offered: Fall
• Credits: 3
• Course URL: Canvas

Prerequisites

Genetics 01:447:380 or Genetic Analysis I 01:447:384 and Gen Bio Lab 01:119:117 or 01:119:102 

Course Description

In this course, we examine human health from an evolutionary perspective, exploring the impact that our evolutionary heritage has on modern human diseases, both chronic and infectious. We will learn how the framework of evolutionary biology and modern genetic tools can inform our understanding of issues relevant to clinical and public health. Rather than focus on the immediate mechanisms underlying disease, we will endeavor to understand the ultimate factors that influence susceptibility, such as past natural selection. The course topics are wide-ranging, but particular attention is paid to emerging infectious diseases, as well as non-communicable diseases that may be exacerbated by facets of modern lifestyles. Through lectures, critical analysis of the primary literature and popular science news, and class discussions, participants will learn how evolutionary principles can be practically applied to medicine. Key readings each session will focus on genetic techniques for understanding evolutionary medicine, while additional readings will incorporate perspectives from diverse fields.

Course Syllabus

Fall 2024 (syllabus will be updated soon)

Course Satisfies Learning Goals

Departmental Goals:

1. Integrate the material from multiple courses and research. That is, to think holistically and to see the whole as well as the parts.

2. Use genetic information and ideas to critically analyze published research articles in genetics

 Exams, Assignments, and Grading Policy

TBD

Course Materials

TBD

Course Closed?

If you are a non-Genetics major or if this course is closed, please add your name to request an spn  for the course under the Department of Genetics section of the SPN Request Page.  Please note the system does not notify students unless they can be accommodated in the course. SPNs are distributed throughout the remainder of the semester and through the drop/add period.  If you have any questions, please contact the genetics department at This email address is being protected from spambots. You need JavaScript enabled to view it.. 

Faculty

Dr. Christina Bergey

** All information is subject to change at the discretion of the course coordinator.

• Semester Offered: Spring
• Credits: 3
• Course URL: Canvas

Prerequisites

General Biology 01:119:115/116/117 or AP credits and General Chemistry 01:160:162  or 01:160:-164 or AP credits.

Restrictions

For Genetics Majors or for other majors if there is space.

Course Syllabus

Spring 2025 (Subject to change)

Course Description and Learning Goals

The purpose of this course is to train students in many of the techniques used in modern molecular biology and biochemistry by giving them as much "hands on" experience as possible. In designing this course, we wanted to avoid the problems of lab courses in which the experimental outcome is already known and the aim of the laboratory exercises is to simply reproduce the expected results as closely as possible. We have therefore developed a course in which students will carry out a research project for which the results are unknown.

The project: After some initial training in techniques commonly used in molecular biology, students will start to work on their main research project. The project involves sequencing random clones from a cDNA library. The sequences derived from these experiments will be used to query a database for sequence similarity using the appropriate computer software. When matches are found, students will then search the scientific literature for information on the genes that they have identified. Students have the potential of identifying novel genes. 

Course satisfies the following MBB Dept. Learning Goals:

1. Students should demonstrate an understanding of the knowledge that is needed to begin biomedical research and that is required for post-graduate exams and studies.
2. Students should demonstrate the ability to find and evaluate information about specific biological systems or problems.
3. Students should demonstrate the ability to design experiments and critically analyze data.
4. Students should demonstrate the ability to communicate their research and findings orally through seminar and poster presentations and through written research papers.

Core Curriculum Learning Goals met by this course:

NS e. Understand and apply basic principles and concepts in the physical or biological sciences.
NS f. Explain and be able to assess the relationship among assumptions, method, evidence, arguments, and theory in scientific analysis.

Grading

The Course Grade will be based on the following distribution:

Exams: 40%
Quizzes 40% (10% Chapter Quizzes, 10% Lab Quizzes; 20% Analysis Quizzes)
Assignments (Questions & Homework) 5%
Lab Reports & Sequence Analysis 15%

Course Materials

There is no textbook to buy.  We’ll be using Canvas as our Learning Management System, and all lecture and laboratory notes, figures, videos, assignments, and grades will be posted there.  You will be required to print out the laboratory protocols for each laboratory session and bring them to the lab. 

Students are required to purchase an iClicker brand of personal clickers.  You can buy the original iClicker or the i>Clicker+ instead of the iCLicker2. (Note: We will not be using Web-iClicker) 

Course Closed?  

All students who want to register for the course must obtain a special permission from Dr. Andrew Vershon ( This email address is being protected from spambots. You need JavaScript enabled to view it.). In your e-mail please include your name, and RUID and which lab section you prefer.  

Faculty

Dr. Bryce Nickels
Waksman Institute, Room 335
phone: 445-6852
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Dr. Gabriel Villegas
Nelson Biological Laboratories A311
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Dr. Andrew Vershon (coordinator)
Waksman Institute, Rm 233
Phone: 445-2905
Email:  This email address is being protected from spambots. You need JavaScript enabled to view it.
Office Hours : 2:00-5:00 PM Tuesdays

Laboratory Coordinator:
Dr. Janet Mead
Waksman Institute, Rm 231
Phone: 445-3901
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Office Hours

This course is designed to provide students with a unique, specialized laboratory experience. Thus, course participants are likely to require individualized attention at irregular and unpredictable intervals. In order to accommodate this unusual situation, the instructors have arranged to be as accessible as possible. Faculty are present during the entire laboratory period to answer questions.  

Student Support Services

• Student Success Essentials: https://success.rutgers.edu
• Student Support Services: https://www.rutgers.edu/academics/student-support   
• The Learning Centers: https://rlc.rutgers.edu/  
• Rutgers Libraries: https://www.libraries.rutgers.edu/
• Bias Incident Reporting: https://studentaffairs.rutgers.edu/bias-incident-reporting
• Dean of Students – Student Support Office: https://success.rutgers.edu/resource/dean-students-student-support-office
• Office of Veteran and Military Programs and Services: https://veterans.rutgers.edu  
• Student Health Services: http://health.rutgers.edu/
• Counseling, Alcohol and Other Drug Assistance Program & Psychiatric Services (CAPS):  http://health.rutgers.edu/medical-counseling-services/counseling/
• UWill: free immediate access to teletherapy; you can choose a therapist based on your preferences including issue, gender, language, ethnicity. http://health.rutgers.edu/uwill/
• Office for Violence Prevention and Victim Assistance: vpva.rutgers.edu/
• Office of Disability Services: https://ods.rutgers.edu/
• Basic Needs Assistance (food, housing, and other   essentials):  https://ruoffcampus.rutgers.edu/basic-needs
• Rutgers Student Food Pantry: https://ruoffcampus.rutgers.edu/food-pantry

** All information is subject to change at the discretion of the course coordinator.

• Semester Offered: Fall, Spring
• Credits: 1
• Course URL: Canvas

Prerequisites

General Biology 01:119:115/116/117 and Basic Stats for Research (01:960:401)

Course Syllabus

Fall 2025 Syllabus  

Course Description and Learning Goals

This course is an introduction to the key statistical methods used in drug discovery and development. Students will explore essential test statistics, including t-tests, ANOVA, chi-square tests, and regression analysis, to assess the efficacy of compounds and candidate drug treatments in each phase of the drug discovery process. Example topics will include hypothesis testing, p-values, confidence intervals, and statistical significance in clinical trials. Through data gleaned from published studies and simulated data, students will gain practical skills in evaluating statistical results to support evidence-based decision-making in drug research. By the end of the course, students will be prepared to evaluate experimental data in the pharmaceutical and biomedical industries.

Course Learning Goals

By fully participating in this course, students will be able to:

1. Demonstrate fundamental laboratory techniques relevant to computational analysis of data generated from the different stages of drug discovery.
2. Apply scientific principles to generate experimental data.
3. Analyze experimental data to draw meaningful conclusions; specifically, conclusions from results for statistical hypothesis testing.
4. Communicate scientific findings clearly through written lab reports.
5. Collaborate with peers to troubleshoot challenges and improve experimental outcomes.

Course Satisfies the Following Genetics Dept. Learning Goals:

By fully participating in this course, students will be able to:

1. Apply key genetic concepts to experimental design and data analysis.
2. Integrate knowledge from coursework and research to interpret experimental results.
3. Critically analyze genetic data and relate findings to published research.
4. Communicate scientific results effectively through written lab reports and presentations.

Exams, Assignments, and Grading Policies:

Your success in this computational lab course and your final grade depend on the following assessment components. Each set of components is packaged into a weekly module.

• Assignments (40%)
  • Weekly assignments consist of multiple-choice and open-ended questions. These assignments typically involve computational data analysis drawn from real and simulated experiments. The data are determined based on the stage of drug discovery and the experiment within the stage.
  • The two lowest assignment grades are dropped.
• Quizzes (25%)
  • Semi-weekly quizzes are based on material from the previous two weekly modules.
  • Formats are multiple-choice.
  • The two lowest quiz grades are dropped.
• Final Exam (15%)
  • The final is cumulative, covering all lab/module topics.
  • The format is multiple-choice.
• Discussion Forums (15%)
  • Students will read a news or research article and write a answer post to the professor’s question.
  • A response to at least two other students’ posts is required.
  • The format is text.
• Participation (5%)
  • Semi-weekly participation questions provide feedback on course materials.
  • The format is text.

Course Materials and Technology Requirements:

There is no required text. In each lab you will see Information from websites or slide presentations. 

There are no specific technology requirements other than the ability to access the course Canvas site. When needed, in each module, you will see links to online calculators.

Course Closed?  

If this course is closed, please add your name to request an spn  for the course under the Department of Genetics section of the SPN Request Page.  Please note the system does not notify students unless they can be accommodated in the course. SPNs are distributed throughout the remainder of the semester and through the drop/add period. We ask that if you are provided an spn for a course and choose not to use it, to please notify our offices at This email address is being protected from spambots. You need JavaScript enabled to view it.  so we may provide it to the next student.

Faculty

Dr. Derek Gordon 
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

** All information is subject to change at the discretion of the course coordinator.

• Semester Offered: Fall
• Credits: 3

This  is a computer-lab based course.

All Genetics majors must complete a lab course requirement to fulfill the degree requirements.  The lab course requirement can be satisfied by taking either this course or 01:447:315 or 01:694:214 or 01:694:215 or 01:447:302 or 01:447:303.

Prerequisites

Students must have previously completed (or be concurrently enrolled in) General Biology I (01:119:115) or have placed out of this course (e.g. through AP credit or approved transfer credit).

Course Restrictions

Students must be in their first or second year at Rutgers in an approved Honors program (e.g., the Honors College or the SAS Honors Program) OR receive special permission from the instructor.

Course Description

Honors Computational Genetics is a computer-based laboratory course that introduces students to the use of computational analysis in biological research. This course is for freshman and sophomore Honors students who are thinking of careers at the intersection of life sciences, statistics, and/or computer science, particularly students who are considering majoring in Genetics. The course fulfills the laboratory requirement for the Genetics major.  Prior computer programming or computer science experience is NOT necessary, nor is it expected. 

In the first half of the course, students will receive instruction in introductory computer programming (Python) and the UNIX operating system. In the second half of the course, students will practice using Python and UNIX software packages to analyze genetic and genomic data. Each class consists of a mixture of lecture and computer-based demos and/or exercises, as well as time for students to work on assignments. The course provides the introductory skills needed to conduct basic computational research in the life sciences, including many aspects of computer programming and data analysis.

This course meets guidelines for an honors course specifically by providing close contact with faculty, covering topics with expanded scope and providing exercises that are more in-depth than in traditional courses.

Course Syllabus

Fall 2025 Syllabus

Course Goals

The goals of Honors Computational Genetics reflect the learning goals of the Department of Genetics, and include 1) knowledge specific goals: know the terms, concepts and theories in genetics; 2) integrate the material from multiple courses and research.

Core Curriculum Learning Goals Met by This Course

Info Tech & Research [ITR].  Goal: Employ current technologies to access information, to conduct research, and to communicate findings.

Course Materials

The computer lab has Windows computers. No textbook is required as most of the needed material is made available during class. 

Exams, Assignments, and Grading Policy

Attendance is expected at all classes; in-class demos and exercises are an integral part of this class and it is difficult to make-up work when class is missed. Students are responsible for being aware of all assignment due dates, which are included with each assignment. Changes to due dates or lecture topics are made in class and/or will be posted on the class Canvas website. There are no late submissions. There is no extra credit or make-up work available for this class. The course is graded on the basis of weekly assignments, short quizzes, and Mid-term and Final Exams.  The following grading scale will be used:   90% A   87% B+   80% B   77% C+   70% C. D and F grades will be determined based on the final score distribution at the end of the course.

Computer Use

NetIDs can be used to access the computers in the computer lab for the duration of the course. These student accounts provide individual space for class work. Work can be done outside of the computer lab on a personal computer. Printing is not available during class. 

Course Closed?

If the course is closed, please continue to monitor WebReg for openings.  If you have any questions, please contact the genetics department at This email address is being protected from spambots. You need JavaScript enabled to view it.

Faculty

Dr. Chris Ellison (Course Director)

Nelson B420

Phone: (848) 445-3841

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

** All information is subject to change at the discretion of the course coordinator.