Difference between revisions of "BCH394P BCH364C 2019"

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'''April 25, 2019 - Synthetic Biology I'''
 
'''April 25, 2019 - Synthetic Biology I'''
 
* '''Reminder: All projects are due by midnight, April 25'''.  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 midnight, April 25'''.  Turn them in as a URL to the web site you created, sent by email to the TA AND PROFESSOR.   
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_SyntheticBio_Spring2018.pdf Today's slides]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_SyntheticBio_Spring2019.pdf Today's slides]
 
A collection of further reading, if you're so inclined:
 
A collection of further reading, if you're so inclined:
* [http://www.marcottelab.org/users/BCH339N_2018/MinimalMycoplasma.pdf Minimal Mycoplasma]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/MinimalMycoplasma.pdf Minimal Mycoplasma]
* [http://www.marcottelab.org/users/BCH339N_2018/GenomeTransplantation.pdf Genome Transplantation]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/GenomeTransplantation.pdf Genome Transplantation]
* [http://www.marcottelab.org/users/BCH339N_2018/JCVI-1.0.pdf JCVI-1.0]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/JCVI-1.0.pdf JCVI-1.0]
* [http://www.marcottelab.org/users/BCH339N_2018/OneStepAssemblyInYeast.pdf One step genome assembly in yeast]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/OneStepAssemblyInYeast.pdf One step genome assembly in yeast]
* [http://www.marcottelab.org/users/BCH339N_2018/StrainsFromYeastGenomicClones.pdf New cells from yeast genomic clones]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/StrainsFromYeastGenomicClones.pdf New cells from yeast genomic clones]
* [http://www.marcottelab.org/users/BCH339N_2018/NewCellFromChemicalGenome.pdf A new cell from a chemically synthesized genome], [http://www.marcottelab.org/users/BCH339N_2018/NewCellFromChemicalGenome.SOM.pdf SOM]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/NewCellFromChemicalGenome.pdf A new cell from a chemically synthesized genome], [http://www.marcottelab.org/users/BCH394P_364C_2019/NewCellFromChemicalGenome.SOM.pdf SOM]
* [http://www.marcottelab.org/users/BCH339N_2018/YeastSynthCsome.pdf 1/2 a synthetic yeast chromosome] and [http://syntheticyeast.org/ Build-A-Genome]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/YeastSynthCsome.pdf 1/2 a synthetic yeast chromosome] and [http://syntheticyeast.org/ Build-A-Genome]
*  [http://www.marcottelab.org/users/BCH339N_2018/Science-2014-Annaluru-55-8.pdf Entire synthetic yeast chromosome]  
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*  [http://www.marcottelab.org/users/BCH394P_364C_2019/Science-2014-Annaluru-55-8.pdf Entire synthetic yeast chromosome]  
 
* [http://science.sciencemag.org/content/355/6329/1040.long Sc 2.0, as of 2017], with the [http://science.sciencemag.org/content/355/6329/1038 computational genome design]
 
* [http://science.sciencemag.org/content/355/6329/1040.long Sc 2.0, as of 2017], with the [http://science.sciencemag.org/content/355/6329/1038 computational genome design]
 
* [http://en.wikipedia.org/wiki/Gillespie_algorithm The Gillespie algorithm]
 
* [http://en.wikipedia.org/wiki/Gillespie_algorithm The Gillespie algorithm]
 
* [https://www.igem.org/Main_Page iGEM], and an example part ([http://parts.igem.org/Featured_Parts:Light_Sensor the light sensor])
 
* [https://www.igem.org/Main_Page iGEM], and an example part ([http://parts.igem.org/Featured_Parts:Light_Sensor the light sensor])
 
* [http://www.popsci.com/diy/article/2013-08/grow-photo Take your own coliroids]
 
* [http://www.popsci.com/diy/article/2013-08/grow-photo Take your own coliroids]
* [http://www.marcottelab.org/users/BCH339N_2018/repressilator.pdf The infamous repressilator]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/repressilator.pdf The infamous repressilator]
* [http://www.marcottelab.org/users/BCH339N_2018/BacterialPhotography.pdf Bacterial photography], and [http://www.marcottelab.org/users/BIO337_2014/UTiGEM2012.pdf UT's 2012 iGEM entry]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/BacterialPhotography.pdf Bacterial photography], and [http://www.marcottelab.org/users/BIO337_2014/UTiGEM2012.pdf UT's 2012 iGEM entry]
* [http://www.marcottelab.org/users/BCH339N_2018/EdgeDetector.pdf Edge detector]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/EdgeDetector.pdf Edge detector]
* [http://www.marcottelab.org/users/BCH339N_2018/nbt.2510.pdf A nice example of digital logic]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/nbt.2510.pdf A nice example of digital logic]
 
* An example of metabolic engineering: [http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12051.html yeast making anti-malarial drugs]
 
* An example of metabolic engineering: [http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12051.html yeast making anti-malarial drugs]
 
[http://www.popsci.com/woolly-mammoth-dna-brought-life-elephant-cells Food for thought]
 
[http://www.popsci.com/woolly-mammoth-dna-brought-life-elephant-cells Food for thought]
  
 
'''April 23, 2019 - Phenologs'''
 
'''April 23, 2019 - Phenologs'''
* '''Remember: The final project web page is due by midnight April 25, 2018, turned in as a URL emailed to the TA+Professor.  Please indicate in the email if you are willing to let us post the project to the course web site.'''  
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* '''Remember: The final project web page is due by midnight April 29, 2019, turned in as a URL emailed to the TA+Professor.  Please indicate in the email if you are willing to let us post the project to the course web site.'''  
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_Phenologs_Spring2018.pdf Today's slides]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_Phenologs_Spring2019.pdf Today's slides]
 
* [http://www.marcottelab.org/paper-pdfs/PNAS_Phenologs_2010.pdf Phenologs] and the [http://www.marcottelab.org/paper-pdfs/PLoSBiology_TBZ_2012.pdf drug discovery story] we'll discuss in class. This is a fun example of the power of opportunistic data mining aka [http://researchparasite.com/ "research parasitism"] in biomedical research.
 
* [http://www.marcottelab.org/paper-pdfs/PNAS_Phenologs_2010.pdf Phenologs] and the [http://www.marcottelab.org/paper-pdfs/PLoSBiology_TBZ_2012.pdf drug discovery story] we'll discuss in class. This is a fun example of the power of opportunistic data mining aka [http://researchparasite.com/ "research parasitism"] in biomedical research.
 
* Search for phenologs [http://www.phenologs.org/ here].  You can get started by rediscovering the plant model of Waardenburg syndrome.  Search among the known diseases for "Waardenburg", or enter the human genes linked to Waardenburg (Entrez gene IDs 4286, 5077, 6591, 7299) to get a feel for how this works. Also, here's [http://www.nytimes.com/2010/04/27/science/27gene.html?_r=0 Carl Zimmer's NYT article] about phenologs and the scientific process.
 
* Search for phenologs [http://www.phenologs.org/ here].  You can get started by rediscovering the plant model of Waardenburg syndrome.  Search among the known diseases for "Waardenburg", or enter the human genes linked to Waardenburg (Entrez gene IDs 4286, 5077, 6591, 7299) to get a feel for how this works. Also, here's [http://www.nytimes.com/2010/04/27/science/27gene.html?_r=0 Carl Zimmer's NYT article] about phenologs and the scientific process.
 
Tools for finding orthologs:<br>
 
Tools for finding orthologs:<br>
* One good tool for discovering orthologs is [http://inparanoid.sbc.su.se/cgi-bin/index.cgi InParanoid].  Note: InParanoid annotation lags a bit, so you'll need to find the [http://www.ensembl.org/index.html Ensembl] protein id, or try a text search for the common name. Or, just link there from [http://www.uniprot.org/ Uniprot]. InParanoid tends towards higher recall, lower precision for finding orthologs. Approaches with higher precision include [http://omabrowser.org/oma/home/ OMA] (introduced in [http://www.marcottelab.org/users/BCH339N_2018/OMA.pdf this paper]), [http://phylomedb.org/ PhylomeDB], and [http://eggnogdb.embl.de/#/app/home EggNOG]
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* One good tool for discovering orthologs is [http://inparanoid.sbc.su.se/cgi-bin/index.cgi InParanoid].  Note: InParanoid annotation lags a bit, so you'll need to find the [http://www.ensembl.org/index.html Ensembl] protein id, or try a text search for the common name. Or, just link there from [http://www.uniprot.org/ Uniprot]. InParanoid tends towards higher recall, lower precision for finding orthologs. Approaches with higher precision include [http://omabrowser.org/oma/home/ OMA] (introduced in [http://www.marcottelab.org/users/BCH394P_364C_2019/OMA.pdf this paper]), [http://phylomedb.org/ PhylomeDB], and [http://eggnogdb.embl.de/#/app/home EggNOG]
* [http://www.marcottelab.org/users/BCH339N_2018/Sonnhammer2002TiG.pdf All your ortholog definition questions answered!]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/Sonnhammer2002TiG.pdf All your ortholog definition questions answered!]
  
 
'''April 18, 2019 - Networks II'''
 
'''April 18, 2019 - Networks II'''
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'''Apr 11, 2019 - Networks'''
 
'''Apr 11, 2019 - Networks'''
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_Networks_Spring2018.pdf Today's slides]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_Networks_Spring2019.pdf Today's slides]
* Metabolic networks: [http://ca.expasy.org/cgi-bin/show_thumbnails.pl The wall chart] (it's interactive. For example, can you find enolase?), the current state of the [http://www.marcottelab.org/users/BCH339N_2018/HumanMetabolicReactionNetwork-2013.pdf human metabolic reaction network], a review of [http://www.marcottelab.org/users/BCH339N_2018/ChiPSeqReview.pdf mapping transcriptional networks by Chip-SEQ] (with the current record holder in this regard held by [https://www.encodeproject.org/ ENCODE]), and a recent review of [http://www.marcottelab.org/users/BCH339N_2018/PPIsAndDiseaseReview.pdf protein interaction mapping in humans] and how it is informing disease genetics.
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* Metabolic networks: [http://ca.expasy.org/cgi-bin/show_thumbnails.pl The wall chart] (it's interactive. For example, can you find enolase?), the current state of the [http://www.marcottelab.org/users/BCH394P_364C_2019/HumanMetabolicReactionNetwork-2013.pdf human metabolic reaction network], a review of [http://www.marcottelab.org/users/BCH394P_364C_2019/ChiPSeqReview.pdf mapping transcriptional networks by Chip-SEQ] (with the current record holder in this regard held by [https://www.encodeproject.org/ ENCODE]), and a recent review of [http://www.marcottelab.org/users/BCH394P_364C_2019/PPIsAndDiseaseReview.pdf protein interaction mapping in humans] and how it is informing disease genetics.
 
* Useful gene network resources include:
 
* Useful gene network resources include:
 
** [http://www.reactome.org/ Reactome]), which we've seen before, links human genes according to reactions and pathways, and also calculated functional linkages from various high-throughput data.
 
** [http://www.reactome.org/ Reactome]), which we've seen before, links human genes according to reactions and pathways, and also calculated functional linkages from various high-throughput data.
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** The best interactive tool for network visualization is [http://www.cytoscape.org/ Cytoscape]. You can download and install it locally on your computer, then visualize and annotated any gene network, such as are output by the network tools linked above.  There is also a web-based network viewer that can be incorporated into your own pages (e.g., as used in [http://www.inetbio.org/yeastnet/ YeastNet]).  Here's an example file to visualize, the [http://proteincomplexes.org/static/downloads/human_protein_complex_map.cys latest version] of the [http://proteincomplexes.org/ human protein complex map].
 
** The best interactive tool for network visualization is [http://www.cytoscape.org/ Cytoscape]. You can download and install it locally on your computer, then visualize and annotated any gene network, such as are output by the network tools linked above.  There is also a web-based network viewer that can be incorporated into your own pages (e.g., as used in [http://www.inetbio.org/yeastnet/ YeastNet]).  Here's an example file to visualize, the [http://proteincomplexes.org/static/downloads/human_protein_complex_map.cys latest version] of the [http://proteincomplexes.org/ human protein complex map].
 
Reading:<br>
 
Reading:<br>
* [http://www.marcottelab.org/users/BCH339N_2018/YeastSGA-2016.pdf The Yeast SGA map]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/YeastSGA-2016.pdf The Yeast SGA map]
 
* [http://www.marcottelab.org/paper-pdfs/ng-fraser-review.pdf Functional networks]
 
* [http://www.marcottelab.org/paper-pdfs/ng-fraser-review.pdf Functional 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/paper-pdfs/JProteomics_GBAReview_2010.pdf Review of predicting gene function and phenotype from protein networks]
* [http://www.marcottelab.org/users/BCH339N_2018/NBTPrimer-NetworkVisualization.pdf Primer on visualizing networks]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/NBTPrimer-NetworkVisualization.pdf Primer on visualizing networks]
  
 
'''Apr 9, 2019 - Principal Component Analysis (& the curious case of European genotypes)'''
 
'''Apr 9, 2019 - Principal Component Analysis (& the curious case of European genotypes)'''
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_PCA_Spring2018.pdf Today's slides]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_PCA_Spring2019.pdf Today's slides]
* [http://www.marcottelab.org/users/BCH339N_2018/EuropeanGenesPCA.pdf European men, their genomes, and their geography]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/EuropeanGenesPCA.pdf European men, their genomes, and their geography]
 
* [http://projector.tensorflow.org/ The tSNE interactive visualization tool also performs PCA]
 
* [http://projector.tensorflow.org/ The tSNE interactive visualization tool also performs PCA]
 
* Relevant to today's discussion for his eponymous distance measure: [http://en.wikipedia.org/wiki/Prasanta_Chandra_Mahalanobis Mahalanobis]
 
* Relevant to today's discussion for his eponymous distance measure: [http://en.wikipedia.org/wiki/Prasanta_Chandra_Mahalanobis Mahalanobis]
 
A smattering of links on PCA:<br>
 
A smattering of links on PCA:<br>
* [http://www.marcottelab.org/users/BCH339N_2018/NBT_primer_PCA.pdf NBT Primer on PCA]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/NBT_primer_PCA.pdf NBT Primer on PCA]
* [http://www.marcottelab.org/users/BCH339N_2018/PrincipalComponentAnalysis.docx A PCA overview (.docx format)] & the [http://horicky.blogspot.com/2009/11/principal-component-analysis.html original post]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/PrincipalComponentAnalysis.docx A PCA overview (.docx format)] & the [http://horicky.blogspot.com/2009/11/principal-component-analysis.html original post]
* Science Signaling (more specifically, Neil R. Clark and Avi Ma’ayan!) had a [http://stke.sciencemag.org/cgi/content/full/sigtrans;4/190/tr3/DC1 nice introduction to PCA] that I've reposted [http://www.marcottelab.org/users/BCH339N_2018/IntroToPCA.pdf here] (with [http://www.marcottelab.org/users/BCH339N_2018/2001967Slides-FINAL.ppt slides])
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* Science Signaling (more specifically, Neil R. Clark and Avi Ma’ayan!) had a [http://stke.sciencemag.org/cgi/content/full/sigtrans;4/190/tr3/DC1 nice introduction to PCA] that I've reposted [http://www.marcottelab.org/users/BCH394P_364C_2019/IntroToPCA.pdf here] (with [http://www.marcottelab.org/users/BCH394P_364C_2019/2001967Slides-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.
  
 
'''Apr 4, 2019 - Classifiers I'''
 
'''Apr 4, 2019 - Classifiers I'''
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_Classifiers_Spring2018.pdf Today's slides]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_Classifiers_Spring2019.pdf Today's slides]
* [http://www.marcottelab.org/users/BCH339N_2018/MachineLearningReview.pdf A nice recent review explaining Support Vector Machines and k-NN classifiers]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/MachineLearningReview.pdf A nice recent review explaining Support Vector Machines and k-NN classifiers]
* [http://www.marcottelab.org/users/BCH339N_2018/AMLALLclassification.pdf Classifying leukemias]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/AMLALLclassification.pdf Classifying leukemias]
 
* For those of you interesting in trying out classifiers on your own, here's the best 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 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].
  
 
'''Apr 2, 2019 - 3D Protein Structure Modeling'''
 
'''Apr 2, 2019 - 3D Protein Structure Modeling'''
 
* Guest speaker: [https://scholar.google.com/citations?hl=en&user=zJ8L0GcAAAAJ&view_op=list_works Dr. Kevin Drew], formerly of New York University and now at the UT Center for Systems and Synthetic Biology
 
* Guest speaker: [https://scholar.google.com/citations?hl=en&user=zJ8L0GcAAAAJ&view_op=list_works Dr. Kevin Drew], formerly of New York University and now at the UT Center for Systems and Synthetic Biology
* [http://www.marcottelab.org/users/BCH339N_2018/structbio_lecture_BCH339N_2018.pptx Today's slides]<br>
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/structbio_lecture_BCH394P_364C_2019.pptx Today's slides]<br>
* The [https://www.rosettacommons.org/software Rosetta] software suite for 3D protein modeling, and [http://www.marcottelab.org/users/BCH339N_2018/RosettaOverview.pdf what it can do for you]
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* The [https://www.rosettacommons.org/software Rosetta] software suite for 3D protein modeling, and [http://www.marcottelab.org/users/BCH394P_364C_2019/RosettaOverview.pdf what it can do for you]
 
* The [http://www.rcsb.org/pdb/ Protein Data Bank], [http://toolkit.tuebingen.mpg.de/hhpred HHPRED], [https://salilab.org/modeller/ MODELLER], and [http://www.pymol.org/ Pymol]
 
* The [http://www.rcsb.org/pdb/ Protein Data Bank], [http://toolkit.tuebingen.mpg.de/hhpred HHPRED], [https://salilab.org/modeller/ MODELLER], and [http://www.pymol.org/ Pymol]
  
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* Fun article: [http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2002050 All biology is computational biology]
 
* Fun article: [http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2002050 All biology is computational biology]
 
* We're finishing up the slides from Mar.  20.<br>
 
* We're finishing up the slides from Mar.  20.<br>
* [http://www.marcottelab.org/users/BCH339N_2018/FuzzyK-Means.pdf Fuzzy k-means]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/FuzzyK-Means.pdf Fuzzy k-means]
* [http://www.marcottelab.org/users/BCH339N_2018/SOM-geneexpression.pdf SOM gene expression]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/SOM-geneexpression.pdf SOM gene expression]
 
** Links to various applications of SOMs: [http://en.wikipedia.org/wiki/Self-organizing_map 1], [http://vizier.u-strasbg.fr/kohonen.htx 2], [http://wn.com/Self_Organizing_Maps_Application 3]. You can run SOMs on the [http://www.math.le.ac.uk/people/ag153/homepage/PCA_SOM/PCA_SOM.html following web site]. You can also run SOM clustering with the [http://bonsai.hgc.jp/~mdehoon/software/cluster Open Source Clustering package] with the '-s' option, or GUI option (here's the [http://bonsai.hgc.jp/~mdehoon/software/cluster/manual/SOM.html#SOM manual]). (FYI, it also supports PCA). If you are not happy with Cluster's SOM function, the statistical package R also provides a package for calculating SOMs (http://cran.r-project.org/web/packages/som/index.html).  
 
** Links to various applications of SOMs: [http://en.wikipedia.org/wiki/Self-organizing_map 1], [http://vizier.u-strasbg.fr/kohonen.htx 2], [http://wn.com/Self_Organizing_Maps_Application 3]. You can run SOMs on the [http://www.math.le.ac.uk/people/ag153/homepage/PCA_SOM/PCA_SOM.html following web site]. You can also run SOM clustering with the [http://bonsai.hgc.jp/~mdehoon/software/cluster Open Source Clustering package] with the '-s' option, or GUI option (here's the [http://bonsai.hgc.jp/~mdehoon/software/cluster/manual/SOM.html#SOM manual]). (FYI, it also supports PCA). If you are not happy with Cluster's SOM function, the statistical package R also provides a package for calculating SOMs (http://cran.r-project.org/web/packages/som/index.html).  
* [http://www.marcottelab.org/users/BCH339N_2018/tSNE.pdf t-SNE]
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* [http://www.marcottelab.org/users/BCH394P_364C_2019/tSNE.pdf t-SNE]
 
** 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 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 on the [http://projector.tensorflow.org/ following web site].  
  
[http://www.marcottelab.org/users/BCH339N_2018/ProblemSet3_2018.pdf '''Problem Set 3], due before midnight Apr. 10, 2018'''.  You will need the following software and datasets:<br>
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[http://www.marcottelab.org/users/BCH394P_364C_2019/ProblemSet3_2019.pdf '''Problem Set 3], due before midnight Apr. 16, 2019'''.  You will need the following software and datasets:<br>
 
* The clustering software is available [https://software.broadinstitute.org/morpheus/ here]. There is an alternative package [http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm here] that you can download and install on your local computer if you prefer.<br>  
 
* The clustering software is available [https://software.broadinstitute.org/morpheus/ here]. There is an alternative package [http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm here] that you can download and install on your local computer if you prefer.<br>  
* [http://www.marcottelab.org/users/BCH339N_2018/yeast_aaseqs Yeast protein sequences]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/yeast_aaseqs Yeast protein sequences]
* [http://www.marcottelab.org/users/BCH339N_2018/yeast_phyloprofiles2.txt Yeast protein phylogenetic profiles]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/yeast_phyloprofiles2.txt Yeast protein phylogenetic profiles]
* [http://www.marcottelab.org/users/BCH339N_2018/yeast_cofractionationdata.txt Yeast protein fractionation/mass spectrometry profiles].  These additionally have common gene names (LocusID_commonname_location) which may help with the interpretation. These data come from [http://www.marcottelab.org/paper-pdfs/Nature_AnimalComplexes_2015.pdf this paper].
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/yeast_cofractionationdata.txt Yeast protein fractionation/mass spectrometry profiles].  These additionally have common gene names (LocusID_commonname_location) which may help with the interpretation. These data come from [http://www.marcottelab.org/paper-pdfs/Nature_AnimalComplexes_2015.pdf this paper].
  
 
'''Mar 26, 2019 - Functional Genomics & Data Mining - Clustering I'''
 
'''Mar 26, 2019 - Functional Genomics & Data Mining - Clustering I'''
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_LargeScaleExperiments_Spring2018.pdf Today's slides]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_LargeScaleExperiments_Spring2019.pdf Today's slides]
 
* [http://en.wikipedia.org/wiki/Cluster_analysis Clustering]
 
* [http://en.wikipedia.org/wiki/Cluster_analysis Clustering]
* [http://www.marcottelab.org/users/BCH339N_2018/NBTPrimer-MicroarrayClustering.pdf Primer on clustering]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/NBTPrimer-MicroarrayClustering.pdf Primer on clustering]
* [http://www.marcottelab.org/users/BCH339N_2018/K-means-Example.ppt K-means example (.ppt)]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/K-means-Example.ppt K-means example (.ppt)]
* [http://www.marcottelab.org/users/BCH339N_2018/Bcelllymphoma.pdf B cell lymphomas]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/Bcelllymphoma.pdf B cell lymphomas]
* [http://www.marcottelab.org/users/BCH339N_2018/nature_review_2000.pdf Review of phylogenetic profiles]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/nature_review_2000.pdf Review of phylogenetic profiles]
 
* [http://en.wikipedia.org/wiki/RNA-Seq RNA-Seq]
 
* [http://en.wikipedia.org/wiki/RNA-Seq RNA-Seq]
  
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'''Mar 14, 2019 - Motifs'''
 
'''Mar 14, 2019 - Motifs'''
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_Motifs_Spring2018.pdf Today's slides]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_Motifs_Spring2019.pdf Today's slides]
 
* '''Due March 19 by email''' - One to two (full) paragraphs describing your plans for a final project, along with the names of your collaborators.  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: [http://sites.google.com/site/ch391fall08finaloconnellwang/?pageDeleted=%2Fa-monte-carlo-simulation-of-protein-polymerization-in-budding-yeast 1], [http://sites.google.com/site/polyomamirnatargeting/ 2], [http://sites.google.com/site/pathtarandmore/ 3], [http://sites.google.com/site/zlutexas/Home/project-for-ch391l 4], [https://sites.google.com/site/structureandevolutionofaprd4/home 5] [https://sites.google.com/site/modelingpyrosequencingerror/ 6]  [https://sites.google.com/site/bioinformaticsch391lproject/ 7] [https://sites.google.com/site/emilo83/home 8] [https://sites.google.com/site/ch391lchipseq/ 9] [https://sites.google.com/site/arabmybgrant/ 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 19 by email''' - One to two (full) paragraphs describing your plans for a final project, along with the names of your collaborators.  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: [http://sites.google.com/site/ch391fall08finaloconnellwang/?pageDeleted=%2Fa-monte-carlo-simulation-of-protein-polymerization-in-budding-yeast 1], [http://sites.google.com/site/polyomamirnatargeting/ 2], [http://sites.google.com/site/pathtarandmore/ 3], [http://sites.google.com/site/zlutexas/Home/project-for-ch391l 4], [https://sites.google.com/site/structureandevolutionofaprd4/home 5] [https://sites.google.com/site/modelingpyrosequencingerror/ 6]  [https://sites.google.com/site/bioinformaticsch391lproject/ 7] [https://sites.google.com/site/emilo83/home 8] [https://sites.google.com/site/ch391lchipseq/ 9] [https://sites.google.com/site/arabmybgrant/ 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>  
* [http://www.marcottelab.org/users/BCH339N_2018/nbt0406-423-primer-whataremotifs.pdf NBT Primer - What are motifs?]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/nbt0406-423-primer-whataremotifs.pdf NBT Primer - What are motifs?]
* [http://www.marcottelab.org/users/BCH339N_2018/nbt0806-959-primer-howdoesmotifdiscoverywork.pdf NBT Primer - How does motif discovery work?]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/nbt0806-959-primer-howdoesmotifdiscoverywork.pdf NBT Primer - How does motif discovery work?]
 
* [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/BCH339N_2018/GibbsSampling.pdf Gibbs Sampling]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/GibbsSampling.pdf Gibbs Sampling]
* FYI, The nanopore sequencing run we started in class ran for a day and collected >9000 basecalled reads, with average lengths of several thousand nucleotides. Our longest read was almost 70 kb! <s>We'll clean up the data and post it to the course web site so that some of you can use it for projects, if desired.</s>  Here are the nanopore reads if you'd like to play with them.  There are 3 fastq files, each gzipped and ~10-30GB in size:  [http://www.marcottelab.org/users/BCH339N_2018/fastq_runid_fbea4bea7410dfda4bf285ff8f07fef0c49a6b4f_0.fastq.gz 0], [http://www.marcottelab.org/users/BCH339N_2018/fastq_runid_fbea4bea7410dfda4bf285ff8f07fef0c49a6b4f_1.fastq.gz 1], [http://www.marcottelab.org/users/BCH339N_2018/fastq_runid_fbea4bea7410dfda4bf285ff8f07fef0c49a6b4f_2.fastq.gz 2]
+
* FYI, The nanopore sequencing run we started in class ran for a day and collected >9000 basecalled reads, with average lengths of several thousand nucleotides. Our longest read was almost 70 kb! <s>We'll clean up the data and post it to the course web site so that some of you can use it for projects, if desired.</s>  Here are the nanopore reads if you'd like to play with them.  There are 3 fastq files, each gzipped and ~10-30GB in size:  [http://www.marcottelab.org/users/BCH394P_364C_2019/fastq_runid_fbea4bea7410dfda4bf285ff8f07fef0c49a6b4f_0.fastq.gz 0], [http://www.marcottelab.org/users/BCH394P_364C_2019/fastq_runid_fbea4bea7410dfda4bf285ff8f07fef0c49a6b4f_1.fastq.gz 1], [http://www.marcottelab.org/users/BCH394P_364C_2019/fastq_runid_fbea4bea7410dfda4bf285ff8f07fef0c49a6b4f_2.fastq.gz 2]
  
 
'''Mar 12, 2019 - Live Demo: Next-next-...-generation Sequencing (NGS) by nanopore'''
 
'''Mar 12, 2019 - Live Demo: Next-next-...-generation Sequencing (NGS) by nanopore'''
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'''Mar 7, 2019 - Genomes II'''<br>
 
'''Mar 7, 2019 - Genomes II'''<br>
 
* We're finishing up the slides from Mar. 5. 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 Mar. 5. 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.]
* The [http://www.marcottelab.org/users/BCH339N_2018/BWApaper.pdf BWA paper] gives a clear introduction to how the Burrows–Wheeler transform can be used to construct an index.
+
* The [http://www.marcottelab.org/users/BCH394P_364C_2019/BWApaper.pdf BWA paper] gives a clear introduction to how the Burrows–Wheeler transform can be used to construct an index.
  
 
'''Mar 5, 2019 - Genome Assembly'''
 
'''Mar 5, 2019 - Genome Assembly'''
 
* Follow up from the last lecture: [https://www.biorxiv.org/content/early/2018/02/09/262964 1/3 of known E. coli operons were just extended by at least 1 gene]
 
* Follow up from the last lecture: [https://www.biorxiv.org/content/early/2018/02/09/262964 1/3 of known E. coli operons were just extended by at least 1 gene]
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_GenomeAssembly_Spring2018.pdf Today's slides]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_GenomeAssembly_Spring2019.pdf Today's slides]
 
* A gentle reminder that Problem Set 2 is '''due by 11:59PM March 5'''<br>
 
* A gentle reminder that Problem Set 2 is '''due by 11:59PM March 5'''<br>
* [http://www.marcottelab.org/users/BCH339N_2018/DeBruijnPrimer.pdf DeBruijn Primer] and [http://www.marcottelab.org/users/BCH339N_2018/DeBruijnSupplement.pdf Supplement]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/DeBruijnPrimer.pdf DeBruijn Primer] and [http://www.marcottelab.org/users/BCH394P_364C_2019/DeBruijnSupplement.pdf Supplement]
 
* Here are a few explanations of using the BWT for indexing: [http://blog.avadis-ngs.com/2012/04/elegant-exact-string-match-using-bwt-2/ 1] [http://www.di.unipi.it/~ferragin/Libraries/fmindexV2/index.html 2]
 
* Here are a few explanations of using the BWT for indexing: [http://blog.avadis-ngs.com/2012/04/elegant-exact-string-match-using-bwt-2/ 1] [http://www.di.unipi.it/~ferragin/Libraries/fmindexV2/index.html 2]
 
* 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].
  
 
'''Feb 28, 2019 - Gene finding II'''
 
'''Feb 28, 2019 - Gene finding II'''
* We're finishing up the slides from Feb. 26, then moving on into [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_GenomeAssembly_Spring2018.pdf Genome Assembly]
+
* We're finishing up the slides from Feb. 26, then moving on into [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_GenomeAssembly_Spring2019.pdf Genome Assembly]
  
 
'''Feb 26, 2019 - Gene finding'''
 
'''Feb 26, 2019 - Gene finding'''
* We'll finish slides from Feb 21, then start [http://www.marcottelab.org/users/BCH339N_2018/BCH339N-GeneFinding-Spring2018.pdf today's slides on gene finding]
+
* We'll finish slides from Feb 21, then start [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C-GeneFinding-Spring2019.pdf today's slides on gene finding]
 
* [http://genome.ucsc.edu/cgi-bin/hgTracks?db=hg38&lastVirtModeType=default&lastVirtModeExtraState=&virtModeType=default&virtMode=0&nonVirtPosition=&position=chr11%3A61755389-61788517&hgsid=477602291_ccTRfcOcZIQHnMkBKGzbQLBRc6HL The UCSC genome browser]
 
* [http://genome.ucsc.edu/cgi-bin/hgTracks?db=hg38&lastVirtModeType=default&lastVirtModeExtraState=&virtModeType=default&virtMode=0&nonVirtPosition=&position=chr11%3A61755389-61788517&hgsid=477602291_ccTRfcOcZIQHnMkBKGzbQLBRc6HL The UCSC genome browser]
Problem Set 2, due before midnight Mar. 5, 2018:<br>
+
Problem Set 2, due before midnight Mar. 11, 2019:<br>
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N_ProblemSet2_Spring2018.pdf '''Problem Set 2'''].   
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C_ProblemSet2_Spring2019.pdf '''Problem Set 2'''].   
* You'll need these 3 files: [http://www.marcottelab.org/users/BCH339N_2018/state_sequences State sequences], [http://www.marcottelab.org/users/BCH339N_2018/soluble_sequences Soluble sequences], [http://www.marcottelab.org/users/BCH339N_2018/transmembrane_sequences Transmembrane sequences]
+
* You'll need these 3 files: [http://www.marcottelab.org/users/BCH394P_364C_2019/state_sequences State sequences], [http://www.marcottelab.org/users/BCH394P_364C_2019/soluble_sequences Soluble sequences], [http://www.marcottelab.org/users/BCH394P_364C_2019/transmembrane_sequences Transmembrane sequences]
 
Reading:<br>
 
Reading:<br>
* [http://www.marcottelab.org/users/BCH339N_2018/EukGeneAnnotation.pdf Eukaryotic gene finding], [http://www.marcottelab.org/users/BCH339N_2018/GeneMark.hmm.pdf GeneMark.hmm], and [http://www.marcottelab.org/users/BCH339N_2018/BurgeKarlin-main.pdf GENSCAN]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/EukGeneAnnotation.pdf Eukaryotic gene finding], [http://www.marcottelab.org/users/BCH394P_364C_2019/GeneMark.hmm.pdf GeneMark.hmm], and [http://www.marcottelab.org/users/BCH394P_364C_2019/BurgeKarlin-main.pdf GENSCAN]
  
 
'''Feb 21, 2019 - HMMs II'''
 
'''Feb 21, 2019 - HMMs II'''
 
* We're finishing up the slides from Feb. 19.  
 
* We're finishing up the slides from Feb. 19.  
* News of the day: (1) A group in San Diego [https://www.rchsd.org/about-us/newsroom/press-releases/new-guinness-world-records-title-set-for-fastest-genetic-diagnosis/ was just recognized by the Guinness Book of World Records] for sequencing a newborn infant's genome and diagnosing a genetic disease in <20 hours. The particular sequencing platform they used [https://www.illumina.com/systems/sequencing-platforms/novaseq.html claims a throughput of 6 Tb and 20 B reads in < 2 days].  (2) Relevant to today's lecture, [https://arstechnica.com/science/2018/01/pocket-sized-dna-reader-used-to-scan-entire-human-genome-sequence/ researchers at Nottingham University reported sequencing and assembling a near-complete human genome using a nanopore sequencer].  The data interpretation relied heavily on hidden Markov models.  [http://www.marcottelab.org/users/BCH339N_2018/MinionHumanGenome.pdf Here's the paper].
+
* News of the day: (1) A group in San Diego [https://www.rchsd.org/about-us/newsroom/press-releases/new-guinness-world-records-title-set-for-fastest-genetic-diagnosis/ was just recognized by the Guinness Book of World Records] for sequencing a newborn infant's genome and diagnosing a genetic disease in <20 hours. The particular sequencing platform they used [https://www.illumina.com/systems/sequencing-platforms/novaseq.html claims a throughput of 6 Tb and 20 B reads in < 2 days].  (2) Relevant to today's lecture, [https://arstechnica.com/science/2018/01/pocket-sized-dna-reader-used-to-scan-entire-human-genome-sequence/ researchers at Nottingham University reported sequencing and assembling a near-complete human genome using a nanopore sequencer].  The data interpretation relied heavily on hidden Markov models.  [http://www.marcottelab.org/users/BCH394P_364C_2019/MinionHumanGenome.pdf Here's the paper].
  
 
'''Feb 19, 2019 - Hidden Markov Models'''
 
'''Feb 19, 2019 - Hidden Markov Models'''
 
* Don't forget: Homework #2 (worth 10% of your final course grade) is due on Rosalind '''by 11:59PM February 19'''.
 
* Don't forget: Homework #2 (worth 10% of your final course grade) is due on Rosalind '''by 11:59PM February 19'''.
 
* Linking out to [http://www.uniprot.org/ UniProt], discussed last time
 
* Linking out to [http://www.uniprot.org/ UniProt], discussed last time
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N-HMMs-Spring2018.pdf Today's slides]<br>
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C-HMMs-Spring2019.pdf Today's slides]<br>
 
Reading:<br>
 
Reading:<br>
* [http://www.marcottelab.org/users/BCH339N_2018/NBTPrimer-HMMs.pdf HMM primer] and [http://www.marcottelab.org/users/BCH339N_2018/NBTPrimer-Bayes.pdf Bayesian statistics primer #1], [http://www.marcottelab.org/users/BCH339N_2018/BayesPrimer-NatMethods.pdf Bayesian statistics primer #2], [http://en.wikipedia.org/wiki/Bayes'_theorem Wiki Bayes]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/NBTPrimer-HMMs.pdf HMM primer] and [http://www.marcottelab.org/users/BCH394P_364C_2019/NBTPrimer-Bayes.pdf Bayesian statistics primer #1], [http://www.marcottelab.org/users/BCH394P_364C_2019/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 [http://www.tutorialspoint.com/python/python_reg_expressions.htm python?])
 
* Care to practice your [http://en.wikipedia.org/wiki/Regular_expression regular expressions]? (In [http://www.tutorialspoint.com/python/python_reg_expressions.htm python?])
  
 
'''Feb 14, 2019 - Biological databases'''
 
'''Feb 14, 2019 - Biological databases'''
* Just a note that we'll be seeing ever more statistics as go on. Here's a [http://www.marcottelab.org/users/BCH339N_2018/StatisticsPrimer.pdf good primer] from [http://www.bio.utexas.edu/research/meyers/LaurenM/index.html Prof. Lauren Myers] 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_2019/StatisticsPrimer.pdf good primer] from [http://www.bio.utexas.edu/research/meyers/LaurenM/index.html Prof. Lauren Myers] to refresh/explain basic concepts.
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N-BiologicalDatabases-Spring2018.pdf Today's slides]<br>
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/BCH394P-364C-BiologicalDatabases-Spring2019.pdf Today's slides]<br>
  
 
'''Feb 12, 2019 - BLAST'''
 
'''Feb 12, 2019 - BLAST'''
 
* Homework #2 (worth 10% of your final course grade) has been assigned on Rosalind and is '''due by 11:59PM February 19'''.
 
* Homework #2 (worth 10% of your final course grade) has been assigned on Rosalind and is '''due by 11:59PM February 19'''.
* [http://www.marcottelab.org/users/BCH339N_2018/BCH339N-BLAST-Spring2018.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_2019/BCH394P-364C-BLAST-Spring2019.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/BCH339N_2018/BLAST.pdf The original BLAST paper]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/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 link to a [http://www.moma.org/interactives/exhibitions/2008/elasticmind/#/211/ stylized version] we exhibited in the engaging [http://www.moma.org/interactives/exhibitions/2008/elasticmind/ Design and the Elastic Mind] show at New York's Museum of Modern Art.  
 
* [http://www.marcottelab.org/paper-pdfs/jmb-lgl.pdf The protein homology graph paper]. Just for fun, here's a link to a [http://www.moma.org/interactives/exhibitions/2008/elasticmind/#/211/ stylized version] we exhibited in the engaging [http://www.moma.org/interactives/exhibitions/2008/elasticmind/ Design and the Elastic Mind] show at New York's Museum of Modern Art.  
  
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* [http://www.marcottelab.org/users/BCH339N_2018/BioinformaticsClass_sp2018.pdf Today's slides]<br>
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/BioinformaticsClass_sp2018.pdf Today's slides]<br>
 
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* News of the day: [https://www.sciencealert.com/naked-mole-rats-nonageing-gompertz-law-longevity-calico Naked mole rats apparently don't age!?!]
 
* News of the day: [https://www.sciencealert.com/naked-mole-rats-nonageing-gompertz-law-longevity-calico Naked mole rats apparently don't age!?!]
 
* We're finishing up the slides from Jan. 25.  
 
* We're finishing up the slides from Jan. 25.  
* [http://www.marcottelab.org/users/BCH339N_2018/NBTPrimer-DynamicProgramming.pdf Dynamic programming primer]
+
* [http://www.marcottelab.org/users/BCH394P_364C_2019/NBTPrimer-DynamicProgramming.pdf Dynamic programming primer]
* [http://www.marcottelab.org/users/BCH339N_2018/GALPAS.xls An example of dynamic programming using Excel], created by [http://www.thepmcf.ca/News-Media/Blog/The-PMCF-Blog/January-2014/Meet-Michael-Hoffman 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_2019/GALPAS.xls An example of dynamic programming using Excel], created by [http://www.thepmcf.ca/News-Media/Blog/The-PMCF-Blog/January-2014/Meet-Michael-Hoffman 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]
  

Revision as of 15:57, 20 January 2019

BCH394P/BCH364C Systems Biology & Bioinformatics

Course unique #: 54044/53945
Lectures: Tues/Thurs 11 – 12:30 PM in JGB 2.202
Instructor: Edward Marcotte, marcotte @ icmb.utexas.edu

  • Office hours: Wed 11 AM – 12 noon in MBB 3.148BA

TA: Caitie McCaffery, clmccafferty @ utexas.edu

  • TA Office hours: Mon 11-12/Fri 2-3 in NHB 3.400B atrium (or MBB 3.128B) Phone: 512-232-3919

Lectures & Handouts

Jan 24, 2019 - Intro to Python

  • REMINDER: My email inbox is always fairly backlogged (e.g., my median time between non-spam emails was 11 minutes when I measured last year), so please copy the TA on any emails to me to make sure they get taken care of.
  • Today's slides
  • Python primer
  • E. coli genome
  • Python 2 vs 3?. For compatibility with Rosalind and other materials, we'll use version 2.7. The current plan is for Python 2.7 support to be halted in 2020, but there is some hope (wishful thinking?) that Python 4 will be backwards compatible, unlike Python 3. Regardless, you're welcome to use whichever version you prefer, but we'll use 2.7 for all class explanations in the interests of simplicity and consistency. For beginners, the differences are quite minimal.

Jan 22, 2019 - Introduction

  • Today's slides
  • Some warm-up videos to get you started on Python (2 not 3, unless you pay for an upgrade): Code Academy's Python coding for beginners
  • We'll be conducting homework using the online environment Rosalind. Go ahead and register on the site, and enroll specifically for BCH394P-BCH364C-Spring2019 using this link. Homework #1 (worth 10% of your final course grade) has already been assigned on Rosalind and is due by 11:59PM January 31.
  • A useful online resource if you get bogged down: Python for Biologists. (& just a heads-up that some of their instructions for running code relate to a command line environment that's a bit different from the default one you install following the Rosalind instructions. It won't affect the programs, just the way they are run or how you specific where files are located.) However, if you've never programmed Python before, definitely check this out!!!

Syllabus & course outline

Course syllabus

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 and exploratory data analyses and their applications, esp. in high-throughput biology.

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.

Some online references:
An online bioinformatics course
Assorted bioinformatics resources on the web: Assorted links
Online probability texts: #1, #2, #3

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 final grade). 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 midnight, April 29, 2019. The last 2.5 classes will be spent presenting your projects to each other. (The presentation will account for 5/25 points for the project.)

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 . 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 (UT academic integrity policy) and cause for dismissal with a failing grade.

The final project web site is due by midnight April 29, 2019.