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Find us
help@cbd.cmu.edu
Computational Biology Department Computational Biology Department
  • About Us
    • Leadership
    • What is Computational Biology?
    • Computational Biology Careers Website
    • List of Educational Programs in Computational Biology
    • The Hillman Center
    • History
    • CBD at a Glance
    • News and Events
      • News
      • Calendar
      • Departmental Seminars
      • Meetings
  • Education
    • Ph.D. in Computational Biology
    • M.S. in Computational Biology
    • Undergraduate Program in Computational Biology
      • Why Major in Computational Biology?
      • Degree Requirements
      • Sample Course Sequence for Computational Biology Majors
      • Guidelines for Transfer into SCS
      • Visit Us
    • Minor in Computational Biology
    • Courses Offered
      • Undergraduate Courses Offered
      • Graduate Courses Offered
      • Course Profiles
        • 02-201/601 Programming for Scientists
        • 02-250 Introduction to Computational Biology
        • 02-261 Quantitative Cell and Molecular Biology Laboratory
        • 02-402/702 Computational Biology Seminar
        • 02-425/725 Computational Methods for Proteogenomics and Metabolomics
        • 02-450/750 Automation of Biological Research: Robotics and Machine Learning
        • 02-500 Undergraduate Research in Computational Biology
        • 02-510/710 Computational Genomics
        • 02-602 Professional Issues in Computational Biology
        • 02-604 Fundamentals of Bioinformatics
        • 02-613 Algorithms and Advanced Data Structures
        • 02-700 M.S. Research
        • 02-701 CPCB Course / Current Topics in Computational Biology
        • 02-715 Advanced Topics in Computational Genomics
        • 02-760 Laboratory Methods for Computational Biologists
        • 02-801 Computational Biology Internship
        • 02-900 Ph.D. Thesis Research
  • Research
    • Software
    • Faculty Research Pages
    • Computational Biology Technical Reports
    • White Papers
  • People
    • Faculty
      • Voting Faculty
      • Affiliated Faculty
      • Visiting Faculty
      • Adjunct Faculty
    • Staff
    • Fellows and Special Faculty
      • The Lane Fellows Program
      • Current Lane Fellows
      • Past Lane Fellows
      • Postdoctoral Fellows
      • Past Postdoctoral Fellows
      • Special Faculty
    • Alumni
      • Ph.D. Graduates
      • Alumni Profiles
  • Join Us!
    • Life in Pittsburgh
      • Neighborhoods Near Carnegie Mellon University
      • Things to Do in Pittsburgh
    • Positions Available
    • Apply to Ph.D. Program
    • Apply to MSCB
    • Apply to Undergraduate Program
    • Apply to be a Lane Fellow

02-604 Fundamentals of Bioinformatics

02-604 COURSE PROFILE

Return to Courses Offered

Course Level Graduate
Units 12
Special Permission Required? (If yes, see “Notes:) No
Frequency Offered Spring
Course Relevance (who should take this course?) This course is designed for first-year MS students in computational biology or students from other disciplines who desire a broad introduction to some of the most fundamental algorithmic approaches in analyzing the large datasets generated from experiments in molecular biology.
Key Topics

Identifying replication origins in bacterial genomesRandomized algorithms for motif finding in DNA sequences

Graph-based algorithms for genome assembly

Brute-force algorithms for antibiotic analysis

Dynamic programming algorithms for sequence alignment

Combinatorial algorithms for genome rearrangement analyses

Evolutionary tree construction algorithms

Clustering algorithms for gene expression analyses

Combinatorial pattern matching algorithms applied to DNA read mapping

Hidden Markov models for comparing rapidly mutating genetic sequences

Statistical analysis for computational proteomics

Background Knowledge A solid background in introductory programming (such as that provided by 02-601) is essential.  Some knowledge of basic algorithms and data structures is also helpful.  Background biology knowledge is not needed.
Assessment Structure Comprehension quizzes. (10% of grade)Weekly write up and participation (10% of grade)
Programming assignments. (40% of grade)
Bioinformatics Software challenges. (10% of grade)
Midterm. (10% of grade)
Final exam (20% of grade)
Most Recent Syllabus  http://compeau.cbd.cmu.edu/wp-content/uploads/2018/01/syllabus_604.pdf
Sample Lecture Recordings  http://youtube.com/user/bioinfalgorithms
Learning Resources The course companion can be found at http://bioinformaticsalgorithms.com
Department Website https://cbd.cmu.edu
College Website https://cs.cmu.edu
Updated January 2018

 

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