Program Description

The Master of Science in Biomedical Data Science (MSBDS) program at the Icahn School of Medicine at Mount Sinai integrates training and education in various aspects of biomedical sciences with machine learning, computer systems, and big data analysis, as well as access to large electronic medical record- linked biomedical repositories. Housed within the Graduate School of Biomedical Sciences, our program offers a unique opportunity for students with a strong quantitative background to hone the skills necessary to enrich—and ultimately to lead—the biomedical workforce of tomorrow.

Our curriculum provides rigorous training in both biomedical sciences, through an intensive semester- long core course, and quantitative data analysis, through innovative required and elective courses. The 30-credit MBDS program consists of two core options (Biomedical Sciences or Systems Neuroscience & Cellular and Molecular Neuroscience ), five required additional courses, two mandatory training sessions in research conduct and rigor, electives, and a capstone research project. Electives can include choices in our exciting biomedical innovation and entrepreneurship curriculum. Our goal is to motivate students to devise innovative approaches to challenging biomedical problems in order to revolutionize personalized medicine and healthcare.

Program Website: https://icahn.mssm.edu/education/masters/data-science

Program Email: datasciencemasters@mssm.edu

All students will need to meet the following degree requirements in order to successfully earn the MSBDS degree:

• Complete a minimum of 30 graduate credits

• Complete the Core Curriculum with an average grade of B (3.0) or higher

• Must achieve an average GPA of at least a 3.0.

• Submit a written capstone project document

• Successfully present the capstone project

• Complete and submit the Degree Completion Status & Commencement Form

• Complete and submit the Student Checkout Form

This chapter covers the MS in Biomedical Data Science Program. Students can find the following information in this section.

• Program Information

• Program Requirements

  • Curricular Requirements

  • Requirements to Graduate

  • Standards for Maintaining Satisfactory Progress

• Curriculum

• Advising

• Capstone Project

It is crucial that students, Advisory Committees, and/or Program Directors monitor the students’ progress throughout the duration of their academic training. Continued financial support is contingent upon maintaining satisfactory progress at all times. Additionally, failure to achieve and maintain satisfactory progress, after counseling is sought from the Program, Advisory Committee and/or Dean of the Graduate School, can result in academic probation and ultimately, dismissal from the Program.

MSBDS students maintain satisfactory progress by:

• Maintaining matriculation on a full-time basis unless permission granted by the program co-directors

• Maintaining a minimum semester GPA of 3.0

• Maintaining a cumulative GPA of 3.0 for the core courses

• Meeting with program leadership at least once per term

• Actively working with a capstone advisor to develop and complete a capstone project

Core Curriculum

All students must complete one of the core curriculum courses below. Only the Fall term core courses are required.

1. Biomedical Sciences (BMS) Core

   • Fall Semester: BSR1012 Biomedical Sciences Fall (6 credits)

2. Neuroscience Core

• Fall Semester BSR1706 Neuro Core 1: Systems Neuroscience (3 credits) Fall Semester BSR1705 Neuro Core 2: Cellular and Molecular Neuroscience (3 credits)

Other Required Coursework

• Computer Systems: The computer systems course is split into 3 separate 1 credit courses. The courses are offered in a specific sequence during the fall term. Each course will be graded separately.

  • BDS1005 Computer Systems: UNIX/LINUX Fundamentals (1 credit)

  • BDS1006 Computer Systems: Architectures & Applications in Scientific Computing (1 credit)

  • BDS1007 Computer Systems: Introduction to Scientific Programming in Python 3 (1 credit)

• BDS2005 Introduction to Algorithms: It is highly recommended students take the Introduction to Scientific Programming in Python 3 before taking this course

• BDS3002 Machine Learning for Biomedical Data Science (3 credits)

Mandatory Training Sessions

Students must take the following two additional mandatory training requisites:

• BSR1021 Responsible Conduct of Research - 0.5 credit

• BSR1022 Rigor and Reproducibility - 0 .5 credit

Elective Credits

• Students must take 2.5 - 5 elective credits in order to do complementary coursework in areas of greatest interest to them.

Capstone Research Project

For their capstone research project, students take 3 to 9 credits and may choose from one of the following biomedical data science research areas:

• computational genomics

• computational biophysics

• systems pharmacology

• biomedical engineering

• imaging and visualization

• biostatistics

• clinical epidemiology

• clinical trials

• environmental medicine

• public health

• health systems design

• health information technology

This section covers the following program requirements:

The Master of Science in Biomedical Data Science (MBDS) program is a unique opportunity for students with a strong quantitative background to apply computational biology and data science techniques to biomedical problems. The 30-credit program includes successfully completing the following requirements:

First Year

• Students must select one of two core courses:

  • BSR1012: Biomedical Sciences – 6 credits – Fall

  • BSR1706: Neuro Core 1 - 3 credits – Fall BSR1705: Neuro Core 2 - 3 credits - Fall

• BDS1005 Computer Systems: UNIX/LINUX Fundamentals – 1 credit – Fall

• BDS1006 Computer Systems: Architectures & Applications in Scientific Computing - 1 credit - Fall

• BDS1007 Computer Systems: Intro to Scientific Programming in Python 3 - 1 credit - Fall

• BSR1021 Responsible Conduct of Research - 0.5 credit – Fall

• BSR1022 Rigor and Reproducibility – 0.5 credit – Spring

• BDS2005 Introduction to Algorithms – 3 credits – Spring

• BDS3002 Machine Learning for Biomedical Data Science - 3 credits - Spring

• Electives - Students complete their credit requirements with electives

Year 2

• BDS9001 Biomedical Data Science Capstone Project – 3-9 credits

• Electives - Students complete their credit requirements with electives

Milestones

• Selecting a lab – During the first term, research mentors will be invited to present their research to the first year students. As a result students are encouraged to contact the research mentor to discuss joining the lab and work on a capstone project. Students are also encouraged to contact research mentors who did not present. Students are expected to join a lab by the end of the first term.

• Research Agreement Form – Once a student and a research mentor has agreed on joining a lab, students will need to submit the Research Agreement Form.

• Capstone Document – Students will submit a written document for their capstone project to the program Co-Directors 1 week prior to the capstone presentation

• Capstone Presentation – Students will present their capstone project to the MSBDS Co-Directors during their last term before graduating. The members required for attendance will be the MSBDS Co-Directors and the research mentor.

During the first term students will have the program course directors as their advisors. Students will search for a lab to join throughout the term. The program manager will monitor to make sure the student is taking the required coursework. Once matched in the lab, the research mentor will become the student’s Capstone Advisor and work directly with the student to develop the capstone project and provide guidance throughout.

For the capstone project the student will join a lab and train directly with the research mentor. The project should apply Biomedical Data Science techniques learned while in the MSBDS program. Students will work directly with their Capstone Advisor to develop the subject of the capstone project. Students must submit a written capstone document and give an oral presentation of the project to the program co-directors and the capstone advisor. It is recommended the student have the capstone advisor review the written document before submission.

The Written Document

The document should be reviewed by the capstone advisor prior to orally presenting the project to the program co-directors. The following structure and guidelines are suggested:

Title and Capstone Advisor

Acknowledgements

Abstract: Provide a summary of your capstone project. Present the major elements of the work in a condensed form.

Introduction: Provide a critical review of the literature that is most pertinent to the work performed. It is important in this section to develop the rationale for the work performed. It should make obvious the basis of the questions addressed by the work. It should describe the basis for the approach taken to answer these questions. It should also provide insight into the relation of the thesis to the current state of knowledge in the field. Critical evaluation of the literature is a necessity. Finally, the introduction should clearly state a hypothesis that will be tested by the studies.

Methods: Describe the primary techniques used. Do not repeat details of published methods. This is not intended to be a recipe book of the methods used. Instead it is a general overview of the procedures used and details of elements that are specific to the work.

Results: Describe what has been accomplished, accompanied by appropriate figures and tables.

Discussion: Examine the results, explain their significance, and answer the question posed in the Introduction. Place the findings in the context of what is currently known in the field, demonstrating how the understanding of the field is extended by the work.

Conclusion/Summary: Summarize and state the significance of the results.

References: In the text, cite all references in the name-and-year system (e.g. Strong and Jones, 1991). The reference list should be arranged alphabetically by the last name of the first author in a standard format with titles. The student should consult standard reference publications for appropriate citation styles.

Oral Presentation

• When the student is ready to orally present the capstone project, the student will work with the program manager to set the day and time.

• Students must send the program directors a copy of the written document 1 week prior to presentation date.

• The presentation will last approximately 60 minutes with the first half will have the student presenting, then a short Q & A with the audience and about 20-25 minute discussion with the student, the capstone advisor, and the program directors.

Capstone Deadlines

Students should submit their written capstone document and orally present their project during the last term before graduation. Please see deadline dates for graduation below.

Required Forms

• Research Agreement Form – To be submitted when students join a lab during 1st year