Difference between revisions of "CS 618"

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This page will contain the course syllabus and plan for CS 618 Computational Biology 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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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.
  
=Projects=
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=Programming/Tools=
'''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
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'''R programming''', including commonly used packages.
  
'''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
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'''Python programming''', including commonly used packages.
  
'''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
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'''Other programming''' - javascript/node, bash.
  
'''Gene expression''' - determining key genes in a particular dataset from fish. Poster - https://cs.indstate.edu/info/posters/bd4isu2021-gosnell.pdf
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'''Software/tools''' - BLAST, NCBI.
  
'''Mass spectrometry data''' - keeping a database of mass spec data and searching through databases for new samples. Potential new project.
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=Algorithms/Statistics=
 +
'''Statistics'''
  
=Topics/Concepts=
 
 
'''Clustering techniques'''
 
'''Clustering techniques'''
  
'''Statistics'''
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'''Sequence alignment algorithms'''
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 +
=Biology=
  
 
'''Central dogma of genetics'''
 
'''Central dogma of genetics'''
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'''Biological data''' - different types of assays, etc. - how the data is produced, what the data looks like, etc.
 
'''Biological data''' - different types of assays, etc. - how the data is produced, what the data looks like, etc.
  
'''Sequence alignment algorithms'''
+
=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.
  
 
=Resources=
 
=Resources=
  
 
[[Bioinformatics]]
 
[[Bioinformatics]]

Revision as of 02:06, 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.

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.

Resources

Bioinformatics