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CS320 Algorithms: theory and practice
CS646 Machine learning in bioinformatics
Spring 2011
Welcome to CS320.
Welcome to CS646.
We will design, implement, and analyse algorithms and advanced data structures.
CS646 is an advanced machine learning course focused on applications in the field of bioinformatics.
We will study the design, implementation and analysis of algorithms and advanced data structures.
We will design, implement, and analyse algorithms and advanced data structures.
CS320 Algorithms theory and practice
Announcements:
CS320 Algorithms: theory and practice
Announcements
Design, implementation and efficiency analysis of algorithms and advanced data structures.
We will study the design, implementation and analysis of algorithms and advanced data structures.
CS580 - programming for the life sciences
CS320 Algorithms theory and practice
1/24/10: There will be a weekly lab meeting on mondays at 1pm at room 425. Bring your laptops.
1/11/10: The course was moved to room 425 in the computer science building
Welcome to CS320.
Biology is becoming more and more a quantitative science, requiring the analysis of large amounts of data. While off-the-shelf programs are available for a large variety of computational tasks faced by practitioners in the life sciences, one sometimes needs to extract data, or manipulate the data in some way that is not provided by available software. The ability to write programs is empowering, removing a researcher’s dependence on having software that precisely matches his or her needs. Programming will be presented using python which is a simple and easy to learn programming language, with programming problems that are inspired by the types of problems encountered in analyzing biological data, e.g. sequence or gene expression data.
In addition to learning how to program, students will learn to think algorithmically. Many biologists use programs such as BLAST or GenScan without understanding how the underlying algorithm works. The course will present algorithms such as sorting algorithms, and algorithms for tasks such as motif finding, and will develop students’ algorithmic thinking so they can better understand the programs they use.
Design, implementation and efficiency analysis of algorithms and advanced data structures.
1/24/10: There will be a weekly lab meeting on mondays at 1pm at room 425.
1/24/10: There will be a weekly lab meeting on mondays at 1pm at room 425. Bring your laptops.
Announcements:
Announcements:
1/24/10: There will be a weekly lab meeting on mondays at 1pm at room 425.
The course was moved to room 425 in the computer science building
1/11/10: The course was moved to room 425 in the computer science building
Announcements:
Announcements:
Description
Description
Announcements: The course was moved to room 425 in the computer science building
Description
Announcements:
The course was moved to room 425 in the computer science building
Description
Many biologists use programs such as BLAST or GenScan without understanding how the underlying algorithm works. The course will present algorithms such as sorting algorithms, and algorithms for tasks such as motif finding, and will develop students’ algorithmic thinking so they can better understand the programs they use (lack of understanding can lead to mis-use).
Many biologists use programs such as BLAST or GenScan without understanding how the underlying algorithm works. The course will present algorithms such as sorting algorithms, and algorithms for tasks such as motif finding, and will develop students’ algorithmic thinking so they can better understand the programs they use.
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CS580 - programming for the life sciences
Announcements: The course was moved to room 425 in the computer science building
Description
Biology is becoming more and more a quantitative science, requiring the analysis of large amounts of data. While off-the-shelf programs are available for a large variety of computational tasks faced by practitioners in the life sciences, one sometimes needs to extract data, or manipulate the data in some way that is not provided by available software. The ability to write programs is empowering, removing a researcher’s dependence on having software that precisely matches his or her needs. Programming will be presented using python which is a simple and easy to learn programming language, with programming problems that are inspired by the types of problems encountered in analyzing biological data, e.g. sequence or gene expression data.
In addition to learning how to program, students will learn to think algorithmically. Many biologists use programs such as BLAST or GenScan without understanding how the underlying algorithm works. The course will present algorithms such as sorting algorithms, and algorithms for tasks such as motif finding, and will develop students’ algorithmic thinking so they can better understand the programs they use (lack of understanding can lead to mis-use).