Difference between revisions of "BCH394P BCH364C 2024"
From Marcotte Lab
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== Lectures & Handouts == | == Lectures & Handouts == | ||
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'''Apr 18 - 25, 2024 - Final Project Presentations''' | '''Apr 18 - 25, 2024 - Final Project Presentations''' | ||
* Welcome to the end of the course! You made it! The last 3 days will be presentations of your class projects. | * Welcome to the end of the course! You made it! The last 3 days will be presentations of your class projects. | ||
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* [https://sites.google.com/view/bioinformaticsprojectjustin/references You discovered an antibody, now what?, by Justin Lerma] | * [https://sites.google.com/view/bioinformaticsprojectjustin/references You discovered an antibody, now what?, by Justin Lerma] | ||
* [https://sites.google.com/view/bch394p-project/home Predicting ISGylation Sites with Machine Learning Models, Xu Zhao] | * [https://sites.google.com/view/bch394p-project/home Predicting ISGylation Sites with Machine Learning Models, Xu Zhao] | ||
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'''April 16, 2024 - Synthetic Biology, highly compressed''' | '''April 16, 2024 - Synthetic Biology, highly compressed''' | ||
* '''Reminder: All projects are due by 10PM, April 12'''. Turn them in as a URL to the web site you created, sent by email to the TA AND PROFESSOR. | * '''Reminder: All projects are due by 10PM, April 12'''. Turn them in as a URL to the web site you created, sent by email to the TA AND PROFESSOR. | ||
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* [http://www.marcottelab.org/users/BCH394P_364C_2024/nbt.2510.pdf A nice example of digital logic] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/nbt.2510.pdf A nice example of digital logic] | ||
[https://colossal.com/ Food for thought] | [https://colossal.com/ Food for thought] | ||
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'''Apr 11, 2024 - Deep learning''' | '''Apr 11, 2024 - Deep learning''' | ||
* Guest speaker: [https://scholar.google.com/citations?hl=en&user=AOYsDhsAAAAJ&view_op=list_works&sortby=pubdate Dr. Claire McWhite], who is a Lewis-Sigler Fellow at Princeton where she develops protein language models using deep learning. She previously completed her B.S. at Rice University, interned at the National Cancer Institute, earned her Ph.D. at UT Austin working extensively in computational biology and proteomics, and appeared as a contestant in [http://bahfest.com/houston2017/ BahFest]. | * Guest speaker: [https://scholar.google.com/citations?hl=en&user=AOYsDhsAAAAJ&view_op=list_works&sortby=pubdate Dr. Claire McWhite], who is a Lewis-Sigler Fellow at Princeton where she develops protein language models using deep learning. She previously completed her B.S. at Rice University, interned at the National Cancer Institute, earned her Ph.D. at UT Austin working extensively in computational biology and proteomics, and appeared as a contestant in [http://bahfest.com/houston2017/ BahFest]. | ||
* [http://www.marcottelab.org/users/BCH394P_364C_2024/ClaireMcWhite-BCH394p-364c_2024.pdf Today's slides] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/ClaireMcWhite-BCH394p-364c_2024.pdf Today's slides] | ||
* [https://www.youtube.com/watch?v=CfAL_cL3SGQ Why neural networks aren't neural networks] | * [https://www.youtube.com/watch?v=CfAL_cL3SGQ Why neural networks aren't neural networks] | ||
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'''Apr 9, 2024 - Networks''' | '''Apr 9, 2024 - Networks''' | ||
* [http://www.marcottelab.org/users/BCH394P_364C_2024/BCH394P-364C_Networks_Spring2024.pdf Today's slides] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/BCH394P-364C_Networks_Spring2024.pdf Today's slides] | ||
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* [http://www.marcottelab.org/paper-pdfs/JProteomics_GBAReview_2010.pdf Review of predicting gene function and phenotype from protein networks] | * [http://www.marcottelab.org/paper-pdfs/JProteomics_GBAReview_2010.pdf Review of predicting gene function and phenotype from protein networks] | ||
* [http://www.marcottelab.org/users/BCH394P_364C_2024/NBTPrimer-NetworkVisualization.pdf Primer on visualizing networks] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/NBTPrimer-NetworkVisualization.pdf Primer on visualizing networks] | ||
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'''Apr 4, 2024 - Principal Component Analysis (& the curious case of European genotypes)''' | '''Apr 4, 2024 - Principal Component Analysis (& the curious case of European genotypes)''' | ||
* [http://www.marcottelab.org/users/BCH394P_364C_2024/BCH394P-364C_PCA_Spring2024.pdf Today's slides] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/BCH394P-364C_PCA_Spring2024.pdf Today's slides] | ||
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* Science Signaling (more specifically, Neil R. Clark and Avi Ma’ayan!) had a nice introduction to PCA that I've reposted [http://www.marcottelab.org/users/BCH394P_364C_2024/IntroToPCA.pdf here] (with [http://www.marcottelab.org/users/BCH394P_364C_2024/2001967Slides-FINAL.ppt slides]) | * Science Signaling (more specifically, Neil R. Clark and Avi Ma’ayan!) had a nice introduction to PCA that I've reposted [http://www.marcottelab.org/users/BCH394P_364C_2024/IntroToPCA.pdf here] (with [http://www.marcottelab.org/users/BCH394P_364C_2024/2001967Slides-FINAL.ppt slides]) | ||
* Python code for [http://sebastianraschka.com/Articles/2015_pca_in_3_steps.html performing PCA yourself]. This example gives a great intro to several important numerical/statistical/data mining packages in Python, including pandas and numpy. | * Python code for [http://sebastianraschka.com/Articles/2015_pca_in_3_steps.html performing PCA yourself]. This example gives a great intro to several important numerical/statistical/data mining packages in Python, including pandas and numpy. | ||
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'''Apr 2, 2024 - Classifiers''' | '''Apr 2, 2024 - Classifiers''' | ||
* [https://twitter.com/JedMSP/status/1247920130941538304 A topical tSNE visualization] | * [https://twitter.com/JedMSP/status/1247920130941538304 A topical tSNE visualization] | ||
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* For those of you interesting in trying out classifiers on your own, here's the best stand-alone open software for do-it-yourself classifiers and data mining: [http://www.cs.waikato.ac.nz/ml/weka/ Weka]. There is a great introduction to using Weka in this book chapter [http://link.springer.com/protocol/10.1007/978-1-4939-3578-9_17 Introducing Machine Learning Concepts with WEKA], as well as the very accessible Weka-produced book [http://www.cs.waikato.ac.nz/ml/weka/book.html Data Mining: Practical Machine Learning Tools and Techniques]. | * For those of you interesting in trying out classifiers on your own, here's the best stand-alone open software for do-it-yourself classifiers and data mining: [http://www.cs.waikato.ac.nz/ml/weka/ Weka]. There is a great introduction to using Weka in this book chapter [http://link.springer.com/protocol/10.1007/978-1-4939-3578-9_17 Introducing Machine Learning Concepts with WEKA], as well as the very accessible Weka-produced book [http://www.cs.waikato.ac.nz/ml/weka/book.html Data Mining: Practical Machine Learning Tools and Techniques]. | ||
* & to do this directly in Python, there's a really excellent library of simple, easy-to-use, classification, regression, machine learning and data mining tools called [https://scikit-learn.org/stable/ scikit-learn]. I highly recommend using scikit-learn in combination with the [https://pandas.pydata.org/ pandas library], which makes it easy to work with large, tabular datasets. Here's [https://www.youtube.com/watch?v=PcvsOaixUh8 a helpful pandas tutorial] to get you started. | * & to do this directly in Python, there's a really excellent library of simple, easy-to-use, classification, regression, machine learning and data mining tools called [https://scikit-learn.org/stable/ scikit-learn]. I highly recommend using scikit-learn in combination with the [https://pandas.pydata.org/ pandas library], which makes it easy to work with large, tabular datasets. Here's [https://www.youtube.com/watch?v=PcvsOaixUh8 a helpful pandas tutorial] to get you started. | ||
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'''Mar 28, 2024 - Proteomics''' | '''Mar 28, 2024 - Proteomics''' | ||
* Guest speaker: [https://scholar.google.com/citations?hl=en&user=vnlxkVwAAAAJ&view_op=list_works Dr. Peter Faull], who earned his Ph.D. at the University of Edinburgh and subsequently served as Head of Proteomics at the MRC UK Clinical Sciences Centre and as a senior lab research scientist at the Francis Crick Institute in London before joining us at UT, where he now serves as Principal Proteomics Scientist in the [https://research.utexas.edu/cbrs/cores/bms/ UT Biological Mass Spectrometry core]. | * Guest speaker: [https://scholar.google.com/citations?hl=en&user=vnlxkVwAAAAJ&view_op=list_works Dr. Peter Faull], who earned his Ph.D. at the University of Edinburgh and subsequently served as Head of Proteomics at the MRC UK Clinical Sciences Centre and as a senior lab research scientist at the Francis Crick Institute in London before joining us at UT, where he now serves as Principal Proteomics Scientist in the [https://research.utexas.edu/cbrs/cores/bms/ UT Biological Mass Spectrometry core]. | ||
| − | + | * [http://www.marcottelab.org/users/BCH394P_364C_2024/IntroToProteomics2-03-24-2024.pdf Today's slides] | |
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'''Mar 26, 2024 - 3D Protein Structure Modeling''' | '''Mar 26, 2024 - 3D Protein Structure Modeling''' | ||
* '''Reminder: Your project topic is due today, and Problem Set #3 is due tomorrow.''' | * '''Reminder: Your project topic is due today, and Problem Set #3 is due tomorrow.''' | ||
* Guest speaker: [https://sites.cns.utexas.edu/zhanglab/bio Prof. Y. Jessie Zhang], an expert on RNA polymerase, its post-translational modifications, and their effects on eukaryotic transcription. She combines experimental structure determination by X-ray crystallography with computational structure prediction using techniques like AlphaFold, and will talk about protein 3D structure modeling and prediction. | * Guest speaker: [https://sites.cns.utexas.edu/zhanglab/bio Prof. Y. Jessie Zhang], an expert on RNA polymerase, its post-translational modifications, and their effects on eukaryotic transcription. She combines experimental structure determination by X-ray crystallography with computational structure prediction using techniques like AlphaFold, and will talk about protein 3D structure modeling and prediction. | ||
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* 3D macromolecular structural modeling software: [https://www.cgl.ucsf.edu/chimerax/ UCSF ChimeraX], the [https://www.rosettacommons.org/software Rosetta] software suite, and [http://www.marcottelab.org/users/BCH394P_364C_2024/RosettaReview.pdf an overview] of what it can do for you, and last but not least: [https://alphafold.ebi.ac.uk/ AlphaFold predicted structures] and the [https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb AlphaFold colab] where you can run your own structure predictions. | * 3D macromolecular structural modeling software: [https://www.cgl.ucsf.edu/chimerax/ UCSF ChimeraX], the [https://www.rosettacommons.org/software Rosetta] software suite, and [http://www.marcottelab.org/users/BCH394P_364C_2024/RosettaReview.pdf an overview] of what it can do for you, and last but not least: [https://alphafold.ebi.ac.uk/ AlphaFold predicted structures] and the [https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb AlphaFold colab] where you can run your own structure predictions. | ||
* & a few other useful 3D structure tools: The [http://www.rcsb.org/ Protein Data Bank], [https://salilab.org/modeller/ MODELLER], and [http://www.pymol.org/ Pymol] | * & a few other useful 3D structure tools: The [http://www.rcsb.org/ Protein Data Bank], [https://salilab.org/modeller/ MODELLER], and [http://www.pymol.org/ Pymol] | ||
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'''Mar 21, 2024 - Clustering II''' | '''Mar 21, 2024 - Clustering II''' | ||
* We'll be continuing the slides from last time | * We'll be continuing the slides from last time | ||
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* [http://www.marcottelab.org/users/BCH394P_364C_2024/tSNE.pdf t-SNE] and [https://umap-learn.readthedocs.io/en/latest/how_umap_works.html UMAP] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/tSNE.pdf t-SNE] and [https://umap-learn.readthedocs.io/en/latest/how_umap_works.html UMAP] | ||
** Links to various applications of t-SNE: [https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding 1], [http://lvdmaaten.github.io/tsne/ 2], [https://www.youtube.com/watch?v=RJVL80Gg3lA 3], [http://distill.pub/2016/misread-tsne/ 4]. You can run t-SNE and UMAP on the [http://projector.tensorflow.org/ following web site]. | ** Links to various applications of t-SNE: [https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding 1], [http://lvdmaaten.github.io/tsne/ 2], [https://www.youtube.com/watch?v=RJVL80Gg3lA 3], [http://distill.pub/2016/misread-tsne/ 4]. You can run t-SNE and UMAP on the [http://projector.tensorflow.org/ following web site]. | ||
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'''Mar 19, 2024 - Functional Genomics & Data Mining - Clustering I''' | '''Mar 19, 2024 - Functional Genomics & Data Mining - Clustering I''' | ||
* '''Due March 21 by email to the TA+Instructor''' - One to two (full) paragraphs describing your plans for a final project, along with the names of your collaborators. Please limit to no more than 3 per group, please. It's also fine to do this independently, if you prefer. (Do you have a particular skill/interest/exciting dataset you need help analyzing? There is a class_projects channel on the slack where you can ask around for partners.) This assignment (planning out your project) will account for 5 points out of your 25 total points for your course project. Here are a few examples of final projects from previous years: [https://sites.google.com/view/bioinformaticsproject/introduction-and-goals?authuser=0 1] [https://sites.google.com/view/bch394ssy/home 2] [https://sites.google.com/view/bch394p-project/home 3] [https://sites.google.com/site/modelingpyrosequencingerror/ 4] [http://sites.google.com/site/pathtarandmore/ 5] [http://sites.google.com/site/zlutexas/Home/project-for-ch391l 6] [https://sites.google.com/view/subcellularloc/projects 7] [https://sites.google.com/utexas.edu/voigt-final-project/home?authuser=0 8] [https://sites.google.com/site/ch391lchipseq/ 9] [https://sites.google.com/utexas.edu/oishika-das-bioinformatics-pro/home 10] [https://sites.google.com/site/biogridviewer/home 11] [https://sites.google.com/a/utexas.edu/immunoglobulin-team/home 12] [https://metabolicnetworkpathways.wordpress.com/ 13] [https://sites.google.com/a/utexas.edu/quantum-tunneling-on-enzymatic-kinetics/home 14]<br> | * '''Due March 21 by email to the TA+Instructor''' - One to two (full) paragraphs describing your plans for a final project, along with the names of your collaborators. Please limit to no more than 3 per group, please. It's also fine to do this independently, if you prefer. (Do you have a particular skill/interest/exciting dataset you need help analyzing? There is a class_projects channel on the slack where you can ask around for partners.) This assignment (planning out your project) will account for 5 points out of your 25 total points for your course project. Here are a few examples of final projects from previous years: [https://sites.google.com/view/bioinformaticsproject/introduction-and-goals?authuser=0 1] [https://sites.google.com/view/bch394ssy/home 2] [https://sites.google.com/view/bch394p-project/home 3] [https://sites.google.com/site/modelingpyrosequencingerror/ 4] [http://sites.google.com/site/pathtarandmore/ 5] [http://sites.google.com/site/zlutexas/Home/project-for-ch391l 6] [https://sites.google.com/view/subcellularloc/projects 7] [https://sites.google.com/utexas.edu/voigt-final-project/home?authuser=0 8] [https://sites.google.com/site/ch391lchipseq/ 9] [https://sites.google.com/utexas.edu/oishika-das-bioinformatics-pro/home 10] [https://sites.google.com/site/biogridviewer/home 11] [https://sites.google.com/a/utexas.edu/immunoglobulin-team/home 12] [https://metabolicnetworkpathways.wordpress.com/ 13] [https://sites.google.com/a/utexas.edu/quantum-tunneling-on-enzymatic-kinetics/home 14]<br> | ||
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* [http://www.marcottelab.org/users/BCH394P_364C_2024/Bcelllymphoma.pdf B cell lymphomas] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/Bcelllymphoma.pdf B cell lymphomas] | ||
* [http://en.wikipedia.org/wiki/RNA-Seq RNA-Seq] | * [http://en.wikipedia.org/wiki/RNA-Seq RNA-Seq] | ||
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'''Mar 12,14, 2024 - SPRING BREAK''' | '''Mar 12,14, 2024 - SPRING BREAK''' | ||
* Don't forget to turn in the proposal for your course project by '''March 21st''' and finish HW3 by '''March 22nd'''. | * Don't forget to turn in the proposal for your course project by '''March 21st''' and finish HW3 by '''March 22nd'''. | ||
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'''Mar 7, 2024 - Motifs''' | '''Mar 7, 2024 - Motifs''' | ||
* We'll talk about motif finding today. | * We'll talk about motif finding today. | ||
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* [http://www.rcsb.org/pdb/explore/explore.do?structureId=1L1M The biochemical basis of a particular motif] | * [http://www.rcsb.org/pdb/explore/explore.do?structureId=1L1M The biochemical basis of a particular motif] | ||
* [http://www.marcottelab.org/users/BCH394P_364C_2024/GibbsSampling.pdf Gibbs Sampling] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/GibbsSampling.pdf Gibbs Sampling] | ||
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'''Mar 5, 2024 - NGS analysis best practices''' | '''Mar 5, 2024 - NGS analysis best practices''' | ||
* Homework #3 (worth 10% of your final course grade) has been assigned on Rosalind and is '''due by 10:00PM March 9'''. In past years, we've run into problems with Rosalind timing out before Meme completes although it usually runs eventually, so be warned you may have to try it a couple of times. Meme also runs faster using the "zero to one" or "one" occurrence per sequence option, rather than the "any number of repeats" option. | * Homework #3 (worth 10% of your final course grade) has been assigned on Rosalind and is '''due by 10:00PM March 9'''. In past years, we've run into problems with Rosalind timing out before Meme completes although it usually runs eventually, so be warned you may have to try it a couple of times. Meme also runs faster using the "zero to one" or "one" occurrence per sequence option, rather than the "any number of repeats" option. | ||
* Guest speaker: [https://www.linkedin.com/in/anna-battenhouse-abba1/ Anna Battenhouse] from the [https://research.utexas.edu/cbrs/ Center for Biomedical Research Support], where she maintains the [https://wikis.utexas.edu/display/RCTFusers Biomedical Research Computing Facility]. | * Guest speaker: [https://www.linkedin.com/in/anna-battenhouse-abba1/ Anna Battenhouse] from the [https://research.utexas.edu/cbrs/ Center for Biomedical Research Support], where she maintains the [https://wikis.utexas.edu/display/RCTFusers Biomedical Research Computing Facility]. | ||
* [http://www.marcottelab.org/users/BCH394P_364C_2024/2024-02-NGS_IntroForEdM.pdf Today's slides] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/2024-02-NGS_IntroForEdM.pdf Today's slides] | ||
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'''Feb 29, 2024 - Genome Assembly/Mapping II'''<br> | '''Feb 29, 2024 - Genome Assembly/Mapping II'''<br> | ||
* We're finishing up the slides from last time. Note that we give short shrift to read mapping/alignment algorithms, of which there are now [https://en.wikipedia.org/wiki/List_of_sequence_alignment_software#Short-Read_Sequence_Alignment a very long list]. Here's an interesting discussion by Lior Pachter of the [https://liorpachter.wordpress.com/2015/11/01/what-is-a-read-mapping/ major developments in that field.] | * We're finishing up the slides from last time. Note that we give short shrift to read mapping/alignment algorithms, of which there are now [https://en.wikipedia.org/wiki/List_of_sequence_alignment_software#Short-Read_Sequence_Alignment a very long list]. Here's an interesting discussion by Lior Pachter of the [https://liorpachter.wordpress.com/2015/11/01/what-is-a-read-mapping/ major developments in that field.] | ||
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* Two notable advances in genome assembly: [http://www.marcottelab.org/users/BCH394P_364C_2024/StringGraphAssembly.pdf String Graphs] and more recently, [http://www.marcottelab.org/users/BCH394P_364C_2024/MultiplexDeBruijnGraphs.pdf multiplexed De Bruijn graphs]. Both have been used to assemble a [http://www.marcottelab.org/users/BCH394P_364C_2024/CompleteHumanGenomeSequence.pdf fully complete human genome sequence] (check out the [https://www.biorxiv.org/content/biorxiv/early/2021/05/27/2021.05.26.445798/F2.large.jpg?width=800&height=600&carousel=1 beautiful string graph visualizations] of the final assemblies, which capture gapless telomere-to-telomere assemblies for all 22 | * Two notable advances in genome assembly: [http://www.marcottelab.org/users/BCH394P_364C_2024/StringGraphAssembly.pdf String Graphs] and more recently, [http://www.marcottelab.org/users/BCH394P_364C_2024/MultiplexDeBruijnGraphs.pdf multiplexed De Bruijn graphs]. Both have been used to assemble a [http://www.marcottelab.org/users/BCH394P_364C_2024/CompleteHumanGenomeSequence.pdf fully complete human genome sequence] (check out the [https://www.biorxiv.org/content/biorxiv/early/2021/05/27/2021.05.26.445798/F2.large.jpg?width=800&height=600&carousel=1 beautiful string graph visualizations] of the final assemblies, which capture gapless telomere-to-telomere assemblies for all 22 | ||
human autosomes and Chromosome X) | human autosomes and Chromosome X) | ||
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'''Feb 27, 2024 - Genome Assembly''' | '''Feb 27, 2024 - Genome Assembly''' | ||
* Science news of the day: [https://www.cell.com/molecular-cell/fulltext/S1097-2765(23)00075-8 New evidence for very short human ORFs coding for real microproteins & peptides] | * Science news of the day: [https://www.cell.com/molecular-cell/fulltext/S1097-2765(23)00075-8 New evidence for very short human ORFs coding for real microproteins & peptides] | ||
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* [http://www.marcottelab.org/users/BCH394P_364C_2024/BCH394P-364C-GenomeAssembly_Spring2024.pdf Today's slides] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/BCH394P-364C-GenomeAssembly_Spring2024.pdf Today's slides] | ||
* [http://www.marcottelab.org/users/BCH394P_364C_2024/DeBruijnPrimer.pdf DeBruijn Primer] and [http://www.marcottelab.org/users/BCH394P_364C_2024/DeBruijnSupplement.pdf Supplement] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/DeBruijnPrimer.pdf DeBruijn Primer] and [http://www.marcottelab.org/users/BCH394P_364C_2024/DeBruijnSupplement.pdf Supplement] | ||
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'''Feb 26, 2024''' - Apologies, no office hours today. Feel free to reach out by email or attend the TA office hours this week. | '''Feb 26, 2024''' - Apologies, no office hours today. Feel free to reach out by email or attend the TA office hours this week. | ||
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'''PROBLEM SET #2 ANNOUNCEMENT''' | '''PROBLEM SET #2 ANNOUNCEMENT''' | ||
* If you would like a few examples of proteins annotated with their transmembrane and soluble regions (according to UniProt) to help troubleshoot your homework, here are some [http://www.marcottelab.org/images/5/5a/Annotated_peptides.txt example yeast protein sequences]. | * If you would like a few examples of proteins annotated with their transmembrane and soluble regions (according to UniProt) to help troubleshoot your homework, here are some [http://www.marcottelab.org/images/5/5a/Annotated_peptides.txt example yeast protein sequences]. | ||
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'''Feb 22, 2024 - Gene finding II''' | '''Feb 22, 2024 - Gene finding II''' | ||
* [https://research.utexas.edu/cbrs/classes/short-courses/spring-2024-semester/ Short classes at UT] start this week in genome sequencing, proteomics, and bioinformatics | * [https://research.utexas.edu/cbrs/classes/short-courses/spring-2024-semester/ Short classes at UT] start this week in genome sequencing, proteomics, and bioinformatics | ||
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* Reposting this so it doesn't fall through the cracks: [http://www.marcottelab.org/users/BCH394P_364C_2024/2019StateOfGeneAnnotation.pdf The current state of gene annotation] | * Reposting this so it doesn't fall through the cracks: [http://www.marcottelab.org/users/BCH394P_364C_2024/2019StateOfGeneAnnotation.pdf The current state of gene annotation] | ||
* [https://news.usc.edu/16163/he-s-got-algorithm/ Why do we call it the Viterbi algorithm?] | * [https://news.usc.edu/16163/he-s-got-algorithm/ Why do we call it the Viterbi algorithm?] | ||
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'''Feb 20, 2024 - Gene finding''' | '''Feb 20, 2024 - Gene finding''' | ||
* Happy Valentine's Day! | * Happy Valentine's Day! | ||
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* [http://www.marcottelab.org/users/BCH394P_364C_2024/EukGeneAnnotation.pdf Eukaryotic gene finding], [http://www.marcottelab.org/users/BCH394P_364C_2024/GeneMark.hmm.pdf GeneMark.hmm], and [http://www.marcottelab.org/users/BCH394P_364C_2024/BurgeKarlin-main.pdf GENSCAN] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/EukGeneAnnotation.pdf Eukaryotic gene finding], [http://www.marcottelab.org/users/BCH394P_364C_2024/GeneMark.hmm.pdf GeneMark.hmm], and [http://www.marcottelab.org/users/BCH394P_364C_2024/BurgeKarlin-main.pdf GENSCAN] | ||
* [http://www.marcottelab.org/users/BCH394P_364C_2024/SplicingAI-jaganathan2019.pdf Deep learning for splice set identification] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/SplicingAI-jaganathan2019.pdf Deep learning for splice set identification] | ||
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'''Feb 15, 2024 - HMMs II''' | '''Feb 15, 2024 - HMMs II''' | ||
* Science news of the day: [https://doi.org/10.1101/2024.01.24.525373 a fun preprint] illustrating the scale of efforts to identify protein families. This one clustered "19 billion sequences in 18 days on 27 high performance computing nodes, using 250,000 CPU hours in total". In all, they found 544 million sequence families (clusters) capturing ~94% of all known proteins, giving a sense of the overall size of the universe of proteins. | * Science news of the day: [https://doi.org/10.1101/2024.01.24.525373 a fun preprint] illustrating the scale of efforts to identify protein families. This one clustered "19 billion sequences in 18 days on 27 high performance computing nodes, using 250,000 CPU hours in total". In all, they found 544 million sequence families (clusters) capturing ~94% of all known proteins, giving a sense of the overall size of the universe of proteins. | ||
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* Link to [http://setosa.io/blog/2014/07/26/markov-chains/ a great interactive visualization of Markov chains], by Victor Powell & Lewis Lehe. It's worth checking out to build some intuition. They correctly point out that [https://en.wikipedia.org/wiki/PageRank Google's PageRank algorithm] is based on Markov chains. There, the ranking of pages in a web search relates to how random walks across linked web pages spend more time on some pages than on others. | * Link to [http://setosa.io/blog/2014/07/26/markov-chains/ a great interactive visualization of Markov chains], by Victor Powell & Lewis Lehe. It's worth checking out to build some intuition. They correctly point out that [https://en.wikipedia.org/wiki/PageRank Google's PageRank algorithm] is based on Markov chains. There, the ranking of pages in a web search relates to how random walks across linked web pages spend more time on some pages than on others. | ||
* A non-biological example of using log odds ratios & Bayesian stats [https://priceonomics.com/how-statistics-solved-a-175-year-old-mystery-about/ to learn the authors of the Federalist Papers]. In a related example, [https://arstechnica.com/science/2024/02/lost-and-found-code-breakers-decipher-50-letters-of-mary-queen-of-scots/ researchers just decoded >50 coded letters from a French archive] and discovered they were lost correspondence from Mary, Queen of Scots, before she was executed in 1587 for treason against Elizabeth I. The researchers used an approach closely related to computing log odds ratios of 5-mer frequencies between putative decoded texts and known free text to figure out the correct ciphers. If you're curious, you can read about it in [https://www.tandfonline.com/doi/full/10.1080/01611194.2022.2160677 Appendix A of their paper] | * A non-biological example of using log odds ratios & Bayesian stats [https://priceonomics.com/how-statistics-solved-a-175-year-old-mystery-about/ to learn the authors of the Federalist Papers]. In a related example, [https://arstechnica.com/science/2024/02/lost-and-found-code-breakers-decipher-50-letters-of-mary-queen-of-scots/ researchers just decoded >50 coded letters from a French archive] and discovered they were lost correspondence from Mary, Queen of Scots, before she was executed in 1587 for treason against Elizabeth I. The researchers used an approach closely related to computing log odds ratios of 5-mer frequencies between putative decoded texts and known free text to figure out the correct ciphers. If you're curious, you can read about it in [https://www.tandfonline.com/doi/full/10.1080/01611194.2022.2160677 Appendix A of their paper] | ||
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'''Feb 13, 2024 - Hidden Markov Models''' | '''Feb 13, 2024 - Hidden Markov Models''' | ||
* Don't forget: Rosalind Homework #2 (worth 10% of your final course grade) is '''due by 10 PM February 8'''. Note: choose one of the two protein translation problems and see the update below on the IUPAC code example. | * Don't forget: Rosalind Homework #2 (worth 10% of your final course grade) is '''due by 10 PM February 8'''. Note: choose one of the two protein translation problems and see the update below on the IUPAC code example. | ||
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* [http://www.marcottelab.org/users/BCH394P_364C_2024/NBTPrimer-HMMs.pdf HMM primer] and [http://www.marcottelab.org/users/BCH394P_364C_2024/NBTPrimer-Bayes.pdf Bayesian statistics primer #1], [http://www.marcottelab.org/users/BCH394P_364C_2024/BayesPrimer-NatMethods.pdf Bayesian statistics primer #2], [http://en.wikipedia.org/wiki/Bayes'_theorem Wiki Bayes] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/NBTPrimer-HMMs.pdf HMM primer] and [http://www.marcottelab.org/users/BCH394P_364C_2024/NBTPrimer-Bayes.pdf Bayesian statistics primer #1], [http://www.marcottelab.org/users/BCH394P_364C_2024/BayesPrimer-NatMethods.pdf Bayesian statistics primer #2], [http://en.wikipedia.org/wiki/Bayes'_theorem Wiki Bayes] | ||
* Care to practice your [http://en.wikipedia.org/wiki/Regular_expression regular expressions]? (In [https://www.tutorialspoint.com/python3/python_reg_expressions.htm python?] & a [https://www.pcwdld.com/python-regex-cheat-sheet Python regexp cheat sheet]) | * Care to practice your [http://en.wikipedia.org/wiki/Regular_expression regular expressions]? (In [https://www.tutorialspoint.com/python3/python_reg_expressions.htm python?] & a [https://www.pcwdld.com/python-regex-cheat-sheet Python regexp cheat sheet]) | ||
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'''ROSALIND ANNOUNCEMENT''' | '''ROSALIND ANNOUNCEMENT''' | ||
* It looks like some people are struggling with the Rosalind problem titled ''Protein Translation''. As an alternative option, I've assigned a problem titled ''Translating RNA into Protein''. Choose one; you'll get credit regardless of which of them you do. Also, it looks like the problem titled "Complementing a Strand of DNA" uses a now out-of-date call for IUPAC codes in the Programming Shortcut. Just delete the "from Bio.Alphabet import IUPAC" line & delete the ", IUPAC.unambiguous_dna" portion of the Seq() functions and it should work fine. | * It looks like some people are struggling with the Rosalind problem titled ''Protein Translation''. As an alternative option, I've assigned a problem titled ''Translating RNA into Protein''. Choose one; you'll get credit regardless of which of them you do. Also, it looks like the problem titled "Complementing a Strand of DNA" uses a now out-of-date call for IUPAC codes in the Programming Shortcut. Just delete the "from Bio.Alphabet import IUPAC" line & delete the ", IUPAC.unambiguous_dna" portion of the Seq() functions and it should work fine. | ||
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'''Feb 8, 2024 - We'll have a guest lecture from your TA Matt McGuffie on advancing your Python data analysis skills''' | '''Feb 8, 2024 - We'll have a guest lecture from your TA Matt McGuffie on advancing your Python data analysis skills''' | ||
* '''WEATHER WARNING #2: Change of plans!''' UT has now officially canceled in-person classes, but more to the point, >100,000 people have lost power in Austin today. We're going to cancel the live zoom class tomorrow, and Matt will instead record the lecture and upload it to Canvas for viewing. | * '''WEATHER WARNING #2: Change of plans!''' UT has now officially canceled in-person classes, but more to the point, >100,000 people have lost power in Austin today. We're going to cancel the live zoom class tomorrow, and Matt will instead record the lecture and upload it to Canvas for viewing. | ||
* Matt is an expert in the bioinformatic analyses of plasmid sequences and developed the popular [http://plannotate.barricklab.org/ pLannotate tool] to annotate and visualize plasmid features, based on a large database of genetic parts and protein sequences. Funny enough, he first described an early version of pLannotate as his project for this class back in 2019. He'll be introducing several useful Python libraries, including the Pandas package for handling large tables and a data visualization library for plotting data. | * Matt is an expert in the bioinformatic analyses of plasmid sequences and developed the popular [http://plannotate.barricklab.org/ pLannotate tool] to annotate and visualize plasmid features, based on a large database of genetic parts and protein sequences. Funny enough, he first described an early version of pLannotate as his project for this class back in 2019. He'll be introducing several useful Python libraries, including the Pandas package for handling large tables and a data visualization library for plotting data. | ||
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'''Jan 6, 2024 - Biological databases''' | '''Jan 6, 2024 - Biological databases''' | ||
* WEATHER WARNING: UT just announced a campus closure for the morning, so for those of you that are able to attend online, I'll plan to hold it at the normal time on the class zoom channel (link available on Canvas). However, for those that can't make it, don't stress! We'll record the lecture and post the video to Canvas so that you can watch it later. Note: the next Rosalind homework is assigned below. | * WEATHER WARNING: UT just announced a campus closure for the morning, so for those of you that are able to attend online, I'll plan to hold it at the normal time on the class zoom channel (link available on Canvas). However, for those that can't make it, don't stress! We'll record the lecture and post the video to Canvas so that you can watch it later. Note: the next Rosalind homework is assigned below. | ||
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* Just a note that we'll be seeing ever more statistics as go on. Here's a [http://www.marcottelab.org/users/BCH394P_364C_2024/StatisticsPrimer.pdf good primer] from [https://stat.utexas.edu/people/lauren-ancel-meyers Prof. Lauren Ancel Myers] (who leads the [https://covid-19.tacc.utexas.edu/ UT Austin COVID-19 Modeling Consortium]) to refresh/explain basic concepts. | * Just a note that we'll be seeing ever more statistics as go on. Here's a [http://www.marcottelab.org/users/BCH394P_364C_2024/StatisticsPrimer.pdf good primer] from [https://stat.utexas.edu/people/lauren-ancel-meyers Prof. Lauren Ancel Myers] (who leads the [https://covid-19.tacc.utexas.edu/ UT Austin COVID-19 Modeling Consortium]) to refresh/explain basic concepts. | ||
* Finally, here's great opportunity to hone your Python skills a bit more: The UT CBRS cores will offer [https://research.utexas.edu/cbrs/classes/short-courses/spring-2024-semester/ short courses] in Python, Unix, and Python for Data Sciences starting in March. | * Finally, here's great opportunity to hone your Python skills a bit more: The UT CBRS cores will offer [https://research.utexas.edu/cbrs/classes/short-courses/spring-2024-semester/ short courses] in Python, Unix, and Python for Data Sciences starting in March. | ||
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'''Feb 1, 2024 - BLAST''' | '''Feb 1, 2024 - BLAST''' | ||
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* [http://www.marcottelab.org/users/BCH394P_364C_2024/BCH394P-364C-BLAST-Spring2024.pdf Our slides today] are modified from a paper on [http://dx.doi.org/10.1371/journal.pbio.1001014 Teaching BLAST] by Cheryl Kerfeld & Kathleen Scott. | * [http://www.marcottelab.org/users/BCH394P_364C_2024/BCH394P-364C-BLAST-Spring2024.pdf Our slides today] are modified from a paper on [http://dx.doi.org/10.1371/journal.pbio.1001014 Teaching BLAST] by Cheryl Kerfeld & Kathleen Scott. | ||
* [http://www.marcottelab.org/users/BCH394P_364C_2024/BLAST.pdf The original BLAST paper] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/BLAST.pdf The original BLAST paper] | ||
* [http://www.marcottelab.org/paper-pdfs/jmb-lgl.pdf The protein homology graph paper]. Just for fun, here's a [http://www.marcottelab.org/users/BCH394P_364C_2024/PHGinMoMA.png stylized version] of this plot that we exhibited in the engaging [https://www.moma.org/calendar/exhibitions/58 Design and the Elastic Mind] show at New York's Museum of Modern Art, now in their permanent collection. | * [http://www.marcottelab.org/paper-pdfs/jmb-lgl.pdf The protein homology graph paper]. Just for fun, here's a [http://www.marcottelab.org/users/BCH394P_364C_2024/PHGinMoMA.png stylized version] of this plot that we exhibited in the engaging [https://www.moma.org/calendar/exhibitions/58 Design and the Elastic Mind] show at New York's Museum of Modern Art, now in their permanent collection. | ||
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'''Jan 30, 2024 - Sequence Alignment II''' | '''Jan 30, 2024 - Sequence Alignment II''' | ||
* We'll be finishing up slides from last time. | * We'll be finishing up slides from last time. | ||
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* [http://www.marcottelab.org/users/BCH394P_364C_2024/GALPAS.xls An example of dynamic programming using Excel], created by [https://hoffmanlab.org/ Michael Hoffman] (a former U Texas undergraduate, now U Toronto professor, who took a prior incarnation of this class) | * [http://www.marcottelab.org/users/BCH394P_364C_2024/GALPAS.xls An example of dynamic programming using Excel], created by [https://hoffmanlab.org/ Michael Hoffman] (a former U Texas undergraduate, now U Toronto professor, who took a prior incarnation of this class) | ||
* A few examples of proteins with internally repetitive sequences: [http://www.pdb.org/pdb/explore/explore.do?structureId=1QYY 1], [http://www.pdb.org/pdb/explore/explore.do?structureId=2BEX 2], [http://www.pdb.org/pdb/explore/explore.do?structureId=1BKV 3] | * A few examples of proteins with internally repetitive sequences: [http://www.pdb.org/pdb/explore/explore.do?structureId=1QYY 1], [http://www.pdb.org/pdb/explore/explore.do?structureId=2BEX 2], [http://www.pdb.org/pdb/explore/explore.do?structureId=1BKV 3] | ||
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'''Jan 25, 2024 - Sequence Alignment I''' | '''Jan 25, 2024 - Sequence Alignment I''' | ||
* Science news of the day, relevant to our discussion of ChatGPT last class: CNET & other news sources used it to write articles; [https://gizmodo.com/cnet-ai-chatgpt-news-robot-1849996151 this Gizmodo story] reports that "the AI-program fabricates information and bungles facts like nobody’s business" and CNET "has been forced to issue multiple, major corrections". So, if you do opt to try ChatGPT to help with Python, be sure to check (and then double-check) everything. | * Science news of the day, relevant to our discussion of ChatGPT last class: CNET & other news sources used it to write articles; [https://gizmodo.com/cnet-ai-chatgpt-news-robot-1849996151 this Gizmodo story] reports that "the AI-program fabricates information and bungles facts like nobody’s business" and CNET "has been forced to issue multiple, major corrections". So, if you do opt to try ChatGPT to help with Python, be sure to check (and then double-check) everything. | ||
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* [http://www.marcottelab.org/users/BCH394P_364C_2024/BLOSUM62Miscalculations.pdf BLOSUM miscalculations improve performance] | * [http://www.marcottelab.org/users/BCH394P_364C_2024/BLOSUM62Miscalculations.pdf BLOSUM miscalculations improve performance] | ||
* There is a good discussion of the alignment algorithms and different scoring schemes [http://www.bioinformaticsonline.org/ch/ch03/supp-all.html here] | * There is a good discussion of the alignment algorithms and different scoring schemes [http://www.bioinformaticsonline.org/ch/ch03/supp-all.html here] | ||
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'''Jan 23, 2024 - Intro to Python II''' | '''Jan 23, 2024 - Intro to Python II''' | ||
* Reminder that today will be part 2 of the "Python boot camp" for those of you with little to no previous Python coding experience. We'll be finishing the slides from last time, plus Rosalind help & programming Q/A. | * Reminder that today will be part 2 of the "Python boot camp" for those of you with little to no previous Python coding experience. We'll be finishing the slides from last time, plus Rosalind help & programming Q/A. | ||
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* We'll talk a bit about [https://chat.openai.com/ ChatGPT] today for co-programming | * We'll talk a bit about [https://chat.openai.com/ ChatGPT] today for co-programming | ||
* Another strong recommendation (really) to the Python newbies to download Eric Matthes's GREAT, free [https://github.com/ehmatthes/pcc/releases/download/v1.0.0/beginners_python_cheat_sheet_pcc_all.pdf Python command cheat sheets] that he provides to accompany his [https://nostarch.com/pythoncrashcourse2e Python Crash Course] book. | * Another strong recommendation (really) to the Python newbies to download Eric Matthes's GREAT, free [https://github.com/ehmatthes/pcc/releases/download/v1.0.0/beginners_python_cheat_sheet_pcc_all.pdf Python command cheat sheets] that he provides to accompany his [https://nostarch.com/pythoncrashcourse2e Python Crash Course] book. | ||
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'''Jan 18, 2024 - Intro to Python''' | '''Jan 18, 2024 - Intro to Python''' | ||
* STANDARD REMINDER: My email inbox is always fairly backlogged (e.g., my median time between non-spam emails was 11 minutes when I measured it some time ago, and it's gotten much worse since then), so please copy the TA on all emails to help us make sure they get taken care of. | * STANDARD REMINDER: My email inbox is always fairly backlogged (e.g., my median time between non-spam emails was 11 minutes when I measured it some time ago, and it's gotten much worse since then), so please copy the TA on all emails to help us make sure they get taken care of. | ||
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* Don't forget that the Rosalind assignments are due by 10 PM January 24. Please do start if you haven't already, or you won't have time to get help if you have any issues installing Python. | * Don't forget that the Rosalind assignments are due by 10 PM January 24. Please do start if you haven't already, or you won't have time to get help if you have any issues installing Python. | ||
* Python 2 vs 3? Bioinformatics researchers [http://astrofrog.github.io/blog/2015/05/09/2015-survey-results/ held out for 2 until quite recently], but [https://careerkarma.com/blog/python-2-vs-python-3/ the shift to 3 is pretty clear now]. We'll use Python 3 (the latest version in Anaconda is 3.9, but any recent version will be fine), but Rosalind and some materials are only available in Python 2.7, so we'll generally try to be version agnostic for compatibility. Use whichever you wish, but be aware that support for Python 2.7 has officially been stopped. For beginners, the [http://www.practicepython.org/blog/2017/02/09/python2-and-3.html differences are quite minimal] and are [https://www.guru99.com/python-2-vs-python-3.html summarized in a table here]. There's also a great [https://python-future.org/compatible_idioms.html cheat sheet here] for writing code compatible with both versions. | * Python 2 vs 3? Bioinformatics researchers [http://astrofrog.github.io/blog/2015/05/09/2015-survey-results/ held out for 2 until quite recently], but [https://careerkarma.com/blog/python-2-vs-python-3/ the shift to 3 is pretty clear now]. We'll use Python 3 (the latest version in Anaconda is 3.9, but any recent version will be fine), but Rosalind and some materials are only available in Python 2.7, so we'll generally try to be version agnostic for compatibility. Use whichever you wish, but be aware that support for Python 2.7 has officially been stopped. For beginners, the [http://www.practicepython.org/blog/2017/02/09/python2-and-3.html differences are quite minimal] and are [https://www.guru99.com/python-2-vs-python-3.html summarized in a table here]. There's also a great [https://python-future.org/compatible_idioms.html cheat sheet here] for writing code compatible with both versions. | ||
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Revision as of 18:17, 11 January 2024
BCH394P/BCH364C Systems Biology & Bioinformatics
Course unique #: 54430/54305
Lectures: Tues/Thurs 11 – 12:30 PM WEL 2.110
Instructor: Edward Marcotte, marcotte @ utexas.edu
- Office hours: Mon 4 – 5 PM on the class Zoom channel (available on Canvas)
TA: Vicki Deng, dengv @ utexas.edu
- TA Office hours: Tues 1 - 2 PM / Fri 12 - 1 PM in MBB 3.204 or by appointment on Zoom
Class Canvas site: https://utexas.instructure.com/courses/1379402
Lectures & Handouts
Jan 16, 2024 - Introduction
- Today's slides
- We'll be conducting homework using the online environment Rosalind. Go ahead and register on the site, and enroll specifically for BCH394P/364C (Spring 2024) Systems Biology/Bioinformatics using this link. Homework #1 (worth 10% of your final course grade) has already been assigned on Rosalind and is due by 10:00PM January 24.
Here are some online Python resources that you might find useful:
- First and foremost, and very, very useful if you're a complete Python newbie: Eric Matthes's Python Crash Course book. He made some GREAT, free Python command cheat sheets to support the book.
- Practical Python, worth checking out!
- If you have any basic experience at all in other programming languages, Google offered an extremely good, 2-day intro course to Python (albeit version 2) that is now available on Youtube.
- Khan Academy has archived their older intro videos on Python here (again, version 2)
Syllabus & course outline
An introduction to systems biology and bioinformatics, emphasizing quantitative analysis of high-throughput biological data, and covering typical data, data analysis, and computer algorithms. Topics will include introductory probability and statistics, basics of Python programming, protein and nucleic acid sequence analysis, genome sequencing and assembly, proteomics, synthetic biology, analysis of large-scale gene expression data, data clustering, biological pattern recognition, and gene and protein networks.
Open to graduate students and upper division undergrads (with permission) in natural sciences and engineering.
Prerequisites: Basic familiarity with molecular biology, statistics & computing, but realistically, it is expected that students will have extremely varied backgrounds. Undergraduates have additional prerequisites, as listed in the catalog.
Note that this is not a course on practical sequence analysis or using web-based tools. Although we will use a number of these to help illustrate points, the focus of the course will be on learning the underlying algorithms, exploratory data analyses, and their applications, esp. in high-throughput biology. By the end of the course, students will know the fundamentals of important algorithms in bioinformatics and systems biology, will be able to design and implement computational studies in biology, and will have performed an element of original computational biology research.
Most of the lectures will be from research articles and slides posted online, with some material from the...
Optional text (for sequence analysis): Biological sequence analysis, by R. Durbin, S. Eddy, A. Krogh, G. Mitchison (Cambridge University Press),
For biologists rusty on their stats, The Cartoon Guide to Statistics (Gonick/Smith) is very good. A reasonable online resource for beginners is Statistics Done Wrong. A truly excellent stats book with a free download is An Introduction to Statistical Learning, by James, Witten, Hastie, Tibshirani, and Taylor, and is accompanied by many supporting Python examples and applications.
Two other online probability & stats references: #1, #2 (which has some lovely visualizations)
No exams will be given. Grades will be based on online homework (counting 30% of the grade), 3 problem sets (given every 2-3 weeks and counting 15% each towards the final grade) and an independent course project (25% of the final grade), which can be collaborative (1-3 students/project). The course project will consist of a research project on a bioinformatics topic chosen by the student (with approval by the instructor) containing an element of independent computational biology research (e.g. calculation, programming, database analysis, etc.). This will be turned in as a link to a web page. The final project is due by 10 PM, April 17, 2024. The last 3 classes will be spent presenting your projects to each other. (The presentation will account for 5/25 points of the project grade.)
If at some point, we have to go into coronavirus lockdown, that portion of the class will be web-based. We will hold lectures by Zoom during the normally scheduled class time. Log in to the UT Canvas class page for the link, or, if you are auditing, email the TA and we will send the link by return email. Slides will be posted before class so you can follow along with the material. We'll record the lectures & post the recordings afterward on Canvas so any of you who might be in other time zones or otherwise be unable to make class will have the opportunity to watch them. Note that the recordings will only be available on Canvas and are reserved only for students in this class for educational purposes and are protected under FERPA. The recordings should not be shared outside the class in any form. Violation of this restriction could lead to Student Misconduct proceedings.
Online homework will be assigned and evaluated using the free bioinformatics web resource Rosalind.
All projects and homework will be turned in electronically and time-stamped. No makeup work will be given. Instead, all students have 5 days of free “late time” (for the entire semester, NOT per project, and counting weekends/holidays). For projects turned in late, days will be deducted from the 5-day total (or what remains of it) by the number of days late (in 1-day increments, rounding up, i.e. 10 minutes late = 1 day deducted). Once the full 5 days have been used up, assignments will be penalized 10 percent per day late (rounding up), i.e., a 50-point assignment turned in 1.5 days late would be penalized 20%, or 10 points.
Homework, problem sets, and the project total to a possible 100 points. There will be no curving of grades, nor will grades be rounded up. We’ll use the plus/minus grading system, so: A= 92 and above, A-=90 to 91.99, etc. Just for clarity's sake, here are the cutoffs for the grades: 92% = A, 90% = A- < 92%, 88% = B+ < 90%, 82% = B < 88%, 80% = B- < 82%, 78% = C+ < 80%, 72% = C < 78%, 70% = C- < 72%, 68% = D+ < 70%, 62% = D < 68%, 60% = D- < 62%, F < 60%.
Students are welcome to discuss ideas and problems with each other, but all programs, Rosalind homework, problem sets, and written solutions should be performed independently (except for the final collaborative project). Students are expected to follow the UT honor code. Cheating, plagiarism, copying, & reuse of prior homework, projects, or programs from CourseHero, Github, or any other sources are all strictly forbidden and constitute breaches of academic integrity and cause for dismissal with a failing grade, possibly expulsion (UT's academic integrity policy). In particular, no materials used in this class, including, but not limited to, lecture hand-outs, videos, assessments (papers, projects, homework assignments), in-class materials, review sheets, and additional problem sets, may be shared online or with anyone outside of the class unless you have the instructor’s explicit, written permission. Any materials found online (e.g. in CourseHero) that are associated with you, or any suspected unauthorized sharing of materials, will be reported to Student Conduct and Academic Integrity in the Office of the Dean of Students. These reports can result in sanctions, including failure in the course.
The use of artificial intelligence tools (such as ChatGPT or Github co-pilot) in this class shall be permitted on a limited basis for programming assignments. You are also welcome to seek my prior-approval to use AI writing tools on any assignment. In either instance, AI writing tools should be used with caution and proper citation, as the use of AI should be properly attributed. Using AI writing tools without my permission or authorization, or failing to properly cite AI even where permitted, shall constitute a violation of UT Austin’s Institutional Rules on academic integrity.
The final project website is due by 10 PM April 17, 2024
- How to make a website for the final project
- Google Site: https://sites.google.com/new
- You might also consider streamlit, which lets you generate websites on the fly direct from Python
