Difference between revisions of "CS 618"
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| − | This page will contain the course syllabus and plan for CS 618 Computational Biology (run also as CS 459 Topics in CS for undergrads) for the summer of 2024. For now, it contains a list of topics that we will look at. The basic plan is to look at a number of projects that I have worked on in the past, and to look at key tools and algorithms used in computational biology and bioinformatics. The top 3 goals for the course - (1) being able to use programming, tools, etc. to work on biology-related projects and data, (2) understanding some of the key algorithms, statistics, etc. used in this area, and (3) understanding as much of the biology as we can, in particular related to where the data comes from, what it means, etc. And tying all of these together will be working on some projects. | + | This page will contain the course syllabus and plan for CS 618 Computational Biology (run also as CS 459 Topics in CS for undergrads) for the summer of 2024. For now, it contains a list of topics that we will look at. The basic plan is to look at a number of projects that I have worked on in the past, and to look at key tools and algorithms used in computational biology and bioinformatics. |
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| + | The top 3 goals for the course - (1) being able to use programming, tools, etc. to work on biology-related projects and data, (2) understanding some of the key algorithms, statistics, etc. used in this area, and (3) understanding as much of the biology as we can, in particular related to where the data comes from, what it means, etc. And tying all of these together will be working on some projects. | ||
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| + | Note - this page will be added to as I prepare for the course, but this is hopefully enough for you to know if you want to take the course or not. | ||
=Programming/Tools= | =Programming/Tools= | ||
Revision as of 02:07, 18 April 2024
This page will contain the course syllabus and plan for CS 618 Computational Biology (run also as CS 459 Topics in CS for undergrads) for the summer of 2024. For now, it contains a list of topics that we will look at. The basic plan is to look at a number of projects that I have worked on in the past, and to look at key tools and algorithms used in computational biology and bioinformatics.
The top 3 goals for the course - (1) being able to use programming, tools, etc. to work on biology-related projects and data, (2) understanding some of the key algorithms, statistics, etc. used in this area, and (3) understanding as much of the biology as we can, in particular related to where the data comes from, what it means, etc. And tying all of these together will be working on some projects.
Note - this page will be added to as I prepare for the course, but this is hopefully enough for you to know if you want to take the course or not.
Programming/Tools
R programming, including commonly used packages.
Python programming, including commonly used packages.
Other programming - javascript/node, bash.
Software/tools - BLAST, NCBI.
Algorithms/Statistics
Statistics
Clustering techniques
Sequence alignment algorithms
Biology
Central dogma of genetics
Biological data - different types of assays, etc. - how the data is produced, what the data looks like, etc.
Projects
Gene expression - determining key genes from gene expression datasets. Project is in R, uses Shiny, Datatables, ShinyProxy, Docker. Poster - https://cs.indstate.edu/info/posters/bd4isu2022-bartlett.pdf
Protein topology prediction - finding potential transmembrane proteins in genomes. Project is in Python, uses Javascript, NCBI, BLAST. Poster - https://cs.indstate.edu/info/posters/bd4isu2022-hoffman.pdf
Transcription factors - finding mutations to disable a transcription factor while still preserving others. Project is in Python, R, and/or C. Poster - https://cs.indstate.edu/info/posters/bd4isu2020-bennett.pdf
Gene expression - determining key genes in a particular dataset from fish. Poster - https://cs.indstate.edu/info/posters/bd4isu2021-gosnell.pdf
Mass spectrometry data - keeping a database of mass spec data and searching through databases for new samples. Potential new project.
