This course is a computer based lab course.
All Genetics majors must complete a lab course requirement to complete 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.
Fall Term Only, Tuesdays and Fridays, 10:20AM-1:00PM
Students must have previously completed General Biology I and II (01:119:115 and 01:119:116) or have placed out of these two courses (e.g., through AP credit or approved transfer credit).
Students must be in their first year at Rutgers in an approved Honors program (e.g., the Honors College or the SAS Honors Program).
Honors computational genetics is a computer-based laboratory course that introduces students to the use of computers in biological research. This course is for freshman 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.
In the first half of the course, students will receive instruction in introductory computer programming (Python). In the second half of the course, students will practice writing code in Python while working on an in-depth computational project in genetics and genomics that incorporates the topics listed for the last 5-6 weeks. 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. Guest investigators will frequently make short presentations (in person or by skype) to provide illustrations of how programming and informatics is critical for their research. 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 (faculty to student ratio of approximately 1 to 5), covering topics with expanded scope and providing exercises that are more in-depth than in traditional courses, and by bringing outside speakers into the classroom.
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 y: Employ current technologies to access information, to conduct research, and to communicate findings.
The computer lab has Windows computers. Class materials and files should be copied after each class to a portable USB flash drive (Windows formatted) to continue working at home. No textbook is required as most of the needed material is made available during class. A useful resource to have on hand if you prefer to have a printed book is:
Think Python eBook (free): http://greenteapress.com/wp/think-python/
Learn Python eBook (free): https://learnpythonthehardway.org/book/
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 Sakai website. There are no late submissions. Most assignments are handed in via the Sakai site. If a class must be missed when an assignment is due, in order to receive credit, the assignment must be uploaded to the Sakai site on time. 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 the Final Exam. The Final Exam is an in-class cumulative exam that accounts for 20% of the final grade. All assignments will be turned in via the Sakai website, following instructions provided by the instructor or the TA. Grades will be calculated based on overall course performance. 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.
A username and password is assigned to use on the computers in the computer lab for the duration of the course. These student accounts provide individual space for class work. The lab computers are Windows computers. Work can be done outside of the computer lab, but everything used in class would need to be installed and setup to mirror the classroom environment as the computer lab accounts and installed programs are not accessible outside the computer lab. Many Rutgers lab computers have software installation restrictions, so personal computers are recommended for work done outside of the computer lab. Printing is not available during class.
If this course is closed, please use the following link to add your name to the wait list: Wait List Sign Up for Fall 2017 Courses.
If you have any questions, please contact the Department of Genetics Undergraduate Education Office in Nelson Biological Laboratories Room B416 or call 848-445-1146.
Dr. Tara Matise (Coordinator)
C-205 Nelson Biological Laboratories
Phone: (848) - 445-3125
Dr. Chris Ellison
** All information is subject to change at the discretion of the course coordinator.