Students and faculty will develop and share professional interests while discussing current trends and developments in bioinformatics and biotechnology. Students will develop and then assess literature reviews.

Prerequisites

• Graduate standing

Paper Presentations and Discussion: Grades will be in-part based on presentations to the class and participation in discussions of the presentations. All discussion sessions will be divided evenly among students during the final lecture of the first week of the semester. If you cannot make the class in which they are assigned, please inform the instructor as soon as possible.

Students are required to speak with the instructor well before their presentation. This is intended to help you give the best possible presentation. Appointments must be at least one week (7 full days) in advance of the presentation date to give you sufficient time. Failure to meet with the instructor far enough in advance to discuss a paper will result in a 50% grade reduction for that presentation. Note that presentations are not necessarily in order by reading letter! Please pay attention to which week your presentations are.

The final grade for a presentation will be determined by the instructor based upon understanding of the paper and ability to convey that understanding to the class through discussion. Presentations are expected to cover the major points of the paper, as discussed with the instructor during the required meeting. Overlap with previous presentations, for the topic and for the student, should also be minimized.

Participation grades will be determined through a combination of attending class on time and for the full session, filling out scoring sheets for presentations, and instructor assessment of student engagement.

During the course, students will form teams to develop their own literature reviews of a relevant topic of interest and evaluate the reviews of other teams. Evaluations will be done by rubrics. Each literature review will go through a development process, with faculty guidance, and individual components to the final grade.

Literature reviews may not be historical reviews or purely clinical. There must be a bioinformatics component.

The final literature review should be 15-20 pages long, double-spaced. Citations will not count for or against the page limit. Excessive quotes and figures/tables are strongly discouraged.

Note that articles marked "[online]" are available from myCourses under Content.

Links

• To be added as identified.

For the first offense, anyone caught plagiarizing or otherwise cheating will receive a 0 (zero) on the assignment/exam, and be referred to the Head of the School of Life Sciences. In the event of a second offense, the student will receive an "F" for the course. If you have any questions about whether or not something constitutes plagiarism and/or cheating, please ask the instructor in advance. Duplicate submissions will also receive a grade of 0 (zero) for the first incident. In the case of especially egregious offenses, the instructor reserves the right to assign a grade of "F" for the course, as per RIT policy.

You are encouraged to work with each other in person and through discussion groups, but must in the end write your own work. Sufficient evidence of cheating on a workshop or homework will be treated the same as for plagiarism or cheating in any other part of the course. The assignments will be automatically checked for cheating.

Also be aware that for this course the use of AI will be cheating. Please see the policy on Aritificial Intelligence use in this syllabus for more information.

Note that the class may receive official communication in person in class, by email, or in the myCourses Discussion group(s). Any and all are considered official communication methods.

The legal use of distributed material is strictly limited to course activities, and not activity outside the course. The use of copyright protected material outside of this RIT course may be prohibited by law.

All course materials are to be considered copyrighted by Dr. Michael V. Osier, all rights reserved. Any distribution of course materials outside of the immediate course purposes, including making material available to anyone not enrolled in the course, will be handled through all appropriate RIT and legal channels.

Unless written permission is granted by the faculty member, or a specific accommodation has been approved by the Disability Services Office, students are prohibited from recording lectures or presentations.

In making a determination about whether to grant a Late Course Withdrawl or Incomplete, the faculty member will consult with members of the RIT administration to gather the facts. At a minimum, the student must have experienced a major event that was not within their control at any point. All RIT and COS policies and procedures will be followed. For an Incomplete, this also means that the student must have been passing the course at the time the Incomplete was requested.

In the event of imminent disruption, such as due to weather, the class will follow the lead of RIT in making a determination of whether to move to online instruction or cancel class for the affected day(s). Changes to the syllabus will be made by Dr. Osier, potentially without student input, to retain the robustness of overall course content.

In order for a letter of recommendation to be written by Dr. Osier, the student must have earned a "A-" or better in any relevant course, have had no major issues (e.g. disciplinary), have a high quality academic record, and be of good character. In addition, the student must email Dr. Osier at least four weeks in advance with program information, a current transcript, a current CV, and a statement of what the student would like Dr. Osier to emphasize. Priority is given to students who ask first. Dr. Osier reserves the right to limit the number of letters of recommendation written given his availability.

Use of Artificial Intelligence (AI) for any purpose not expressly approved by the instructor will be treated as cheating, including any applicable penalties. AI should be used as a tool and not as a replacement for learning. Remember that AI is faulty, and can give incorrect answers. It also reduces your practice of the course material, which will set you behind for later assignments and other courses. So using AI doubles your risk.

As appropriate in this course, we will explore how AI can be used ethically. If you have any questions about whether or not AI usage is approved, please email the instructor or stop into office hours.

Contents last updated 3/19/26

• Changes after the course start will be noted here