Carnegie Mellon University

27 courses displayed.

02-601 Programming for Scientists

Provides a practical introduction to programming for students with little or no prior programming experience who are interested in science. Fundamental scientific algorithms will be introduced, and extensive programming assignments will be based on analytical tasks that…
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02-602 Professional Issues in Computational Biology

This course gives Master’s in Computational Biology students an opportunity to develop the professional skills necessary for a successful career in computational biology. This two-semester required course will include assistance with elevator…
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02-604 Fundamentals of Bioinformatics

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…
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02-605 Professional Issues in Automated Science

This course gives Master’s in Automated Science students an exposure to the ethical and professional issues which are unique to the field of automated science. This course will also include opportunities to connect with industry professional with an interest in…
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02-613 Algorithms and Advanced Data Structures

This course is for students not in the computer science major or minor who are interested in advanced data structures. Key Topics: Run time analysis Divide-and-conquer algorithms Dynamic programming algorithms Network flow algorithms Linear and integer…
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02-680 Essential Mathematics and Statistics Scientists

This course rigorously introduces fundamental topics in mathematics and statistics to first-year master’s students.  It directly prepares students for 02-620 (Machine Learning for Scientists) and  gives students the…
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02-700 M.S. Research

This course is for M.S. students who wish to do supervised research for academic credit with a Computational Biology faculty member. Interested students should first contact the Professor with whom they would like to work. If there is mutual interest, the Professor will…
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02-701 CPCB Course/Current Topics in Computational Biology

The course consists of weekly presentations by students and faculty on current topics in computational biology. This course is only for current CPCB Ph.D students

02-703 Special Topics in Bioinformatics and Computational Biology

This is a mini Special Topics course taught on an occasional basis to cover different topics in computational biology.

02-710 Computational Genomics

Course Relevance:  Graduate students in computational biology and graduate students who have interest in algorithm techniques in computational genomics. Background Knowledge:  Machine learning methods, probabilistic modeling, programming. Key…
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02-711 Computational Molecular Biology and Genomics

An advanced introduction to computational molecular biology, using an applied algorithms approach. The first part of the course will cover established algorithmic methods, including pairwise sequence alignment and dynamic programming, multiple sequence alignment, fast…
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02-712 Computational Methods for Biological Modeling and Simulation

This is a required class for Masters in Computational Biology students and available as an elective for graduate students and advanced undergraduates. It is intended for graduates and advanced undergraduates with either biological or computational backgrounds who are…
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02-715 Advanced Topics in Computational Genomics

Research in biology and medicine is undergoing a revolution due to the availability of high-throughput technology for probing various aspects of a cell at a genome-wide scale. The next-generation sequencing technology is allowing researchers to inexpensively generate a…
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02-716 Cross-Species Systems Modeling

Model organisms have longed played an important role in basic science studies and in the pharmaceutical industry. These organisms, ranging from yeast to worms to flies, share many processes that are similar to those active in humans which have made these and other animals…
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02-717 Algorithms in Nature

Computer systems and biological processes often rely on networks of interacting entities to reach joint decisions, coordinate and respond to inputs. There are many similarities in the goals and strategies of biological and computational systems which suggest that each can…
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02-718 Computational Medicine

Modern medical research increasingly relies on the analysis of large patient datasets to enhance our understanding of human diseases. This course will focus on the computational problems that arise from studies of human diseases and the translation of research to the…
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02-719 Genomics and Epigenetics of the Brain

This course will provide an introduction to genomics, epigenetics, and their application to problems in neuroscience. The rapid advances in single cell sequencing and other genomic technologies are revolutionizing how neuroscience research is conducted,…
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02-721 Algorithms for Computational Biology

Some of the most interesting algorithmic challenges in Biology and Bioengineering arise from the modeling, simulation, and engineering of biological macromolecules at, or near atomic resolution.  This course covers a variety of algorithms used to study and…
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02-722 Advanced Algorithms for Computational Structural Biology

This is a seminar-style course on the current literature in computational structural biology. Topics will include algorithms for designing drugs and proteins, as well as protein structure prediction and simulation. Students will be expected to read and discuss papers and…
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02-731 Modeling Evolution

Some of the most serious public health problems we face today, from drug-resistant bacteria, to cancer, all arise from a fundamental property of living systems—their ability to evolve. Since Darwin’s theory of natural selection was first proposed, we…
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02-740 Bioimage Informatics

With the rapid advance of bioimaging techniques and fast accumulation of bioimage data, computational bioimage analysis and modeling are playing an increasingly important role in understanding of complex biological systems. The goals of this course are to provide students…
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02-750 Automation of Scientific Research

Automated science and engineering combines Robotics, Machine Learning, and Artificial Intelligence to accelerate the pace of discovery and rational design. This course introduces students to the Machine Learning and Artificial Intelligence algorithms that enable this…
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02-760 Laboratory Methods for Computational Biologists

Computational biologists frequently focus on analyzing and modeling large amounts of biological data, often from high-throughput assays or diverse sources. It is therefore critical that students training in computational biology be familiar with the paradigms and methods…
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02-761 Laboratory Methods for Automated Biology I

This is a graduate level laboratory-based course designed to teach technical and biological laboratory skills used to design and execute automated biological experiments. Students will learn the principles, experimental paradigms, and techniques for automating biological…
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02-762 Laboratory Methods for Automated Biology II

This laboratory course provides a continuation and extension of experiences in 02-761. Instruction will consist of lectures and laboratory experience using multi-purpose laboratory robotics. During weekly laboratory time, students will complete and integrate parts of two…
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02-801 Computational Biology Internship

This course is for students participating in an internship or co-op.  This course is only for current CPCB Ph.D. students

02-900 Ph.D. Thesis Research

This course is for students enrolled in the Ph.D. program working on research.

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