Programs

Cheminformatics

M.S. in Cheminformatics
M.S. Requirements

The Master of Science in Chemical Informatics prepares students with a background in chemistry, life sciences, or software engineering to specialize in cheminformatics. This professional degree culminates in a capstone research project.

PREREQUISITES

Prospective students for graduate study in chemical informatics will be expected to have a strong background in either informatics/computer science or chemistry (or a related science), with some knowledge of the other field. During their time in the master’s program, students are strongly encouraged to take elective courses that will fill any gaps in their knowledge of these disciplines.

COURSES

The 36 credit hours required for the M.S. in Chemical Informatics include required courses, electives, and a capstone.

Required Courses (12 credits)

  • INFO I571 Chemical Information Technology (3 cr.)
  • INFO I572 Computational Chemistry and Molecular Modeling (3 cr.)
  • INFO I609 Advanced Seminar I in Informatics (Cheminformatics) (3 cr.)
  • INFO I709 Advanced Seminar II in Informatics (Cheminformatics) (3 cr.)

Elective Courses (18 credits)

Electives are to be chosen with prior approval of a graduate advisor based on the student’s interests and experience. All electives should be relevant to some aspect of cheminformatics, and may be selected from courses in the School of Informatics and Computing or in other Indiana University colleges, schools, and divisions.

We strongly encourage students to consider the following courses. In particular, students who are interested in careers in industry should consider applying for an industry-focused internship, either outside the school (I798) or inside (G599), in either their first or second summer.

  • INFO G599 Thesis Research
  • INFO I519 Introduction to Bioinformatics
  • INFO I529 Machine Learning in Bioinformatics
  • INFO I553 Independent Study in Chemical Informatics (may be taken several times)
  • INFO I798 Professional Practicum/Internship
  • CSCI B561 Advanced Database Concepts
  • CSCI P573 Introduction to Scientific Computing
  • CHEM C483 Biological Chemistry
  • SLIS S511 Database Design
  • SLIS S517 Web Programming
  • SLIS S636 Semantic Web
  • STAT S501 Statistical Methods I
  • STAT S503 Statistical Methods IIB
  • STAT S520 Introduction to Statistics
  • STAT S626 Bayesian Theory & Data Analysis

Capstone (6 credits)

All M.S. students must complete a capstone course—a mini–research project related to cheminformatics—in their second year.

Academic Bulletins

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