[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-160253-en":3,"doc-seo-160253-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},160253,687207022233,"Connor ","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",4,"Exam","BIMM-143 - Introduction to Bioinformatics - Preparing for the Final Exam","BIMM-143 prepares students for an open-book, open-notes 150-minute final exam with 35 questions and 80 total points. The assessment focuses on key bioinformatics capabilities across major topics including database querying across core resources, sequence and structure representations, alignment via dynamic programming and scoring matrices, and limits of homology detection with BLAST-family and HMM-based tools. Additional coverage includes using R for data import, exploratory visualization, reproducible scripting, clustering and PCA interpretation, and protein sequence–structure–function analysis with Bio3D and in silico docking for drug discovery.","BIMM-143: INTRODUCTION TO BIOINFORMATICS  \n[http://thegrantlab.org/bimm143](http://thegrantlab.org/bimm143)  \nPreparing for the Final Exam  \nOverview: The final exam for BIMM-143 will be an open-book, open-notes 150-minute test consisting of 35 questions.  \nQuestions will be predominantly short answer (typically worth 2 points) with a number of more involved longer answer questions (typically worth 5 points) .  \nThe number of points for each question is indicated at the beginning of each question. There are 80 total points on offer.  \nThere will be no questions covering the material from lecture 10 (the git version control system) . However, major points from all other lecture material are examinable  \nGeneral exam guidance and test rules are provided at the end of this document.  \nMajor points from lecture 1.  \nUnderstand the increasing necessity for computation in modern life sciences research.  \nBe able to query, search, compare and contrast the data contained in major bioinformatics databases (GenBank, GENE, UniProt, PFAM, OMIM, PDB) and describe how these databases intersect.  \nBe able to describe how nucleotide and protein sequence and structure data are represented (FASTA, FASTQ, GenBank, SAM/BAM, PDB) .  \nExample question: What database should I visit to help determine the protein domains that my novel protein contains?  \nMajor points from lecture 2.  \nBe able to describe how dynamic programming works for pairwise sequence alignment  \nAppreciate the differences between global and local alignment along with their major application areas.  \nBIMM-143 Page 1 of 7  \nUnderstand how aligning novel sequences with previously characterized genes or proteins provides important insights into their common attributes and evolutionary origins.  \nExample question: Fill out the dynamic programming table for determining the optimum global alignment between sequences GATCG and GCTCA. Assume that a match is scored +3 and that mismatches and gaps are scored-1 each?  \nMajor points from lecture 3.  \nBe able to calculate the alignment score between two nucleotide or protein sequences using a provided scoring matrix.  \nUnderstand the limits of homology detection with tools such as BLAST  \nBe able to perform PSI-BLAST, HMMER and protein structure based database searches and interpret the results in terms of the biological significance of an e-value.  \nExample question: What is the major heuristic shortcut that BLAST uses to speed up database searches?  \nMajor points from lecture 4.  \nUnderstand why we use R for bioinformatics.  \nFamiliarity with R’s basic syntax.  \nBe able to use R to read and parse tab and comma-separated (.csv) formatted files ready for subsequent analysis.  \nFamiliarity with major R data structures (vectors, matrices and data.frames)  \nExample question: What is the base R function for importing a tab-separated-value (tsv) format file for further analysis in R?  \nMajor points from lecture 5.  \nAppreciate the major elements of exploratory data analysis and why it is important to visualize data.  \nBIMM-143 Page 2 of 7  \nBe conversant with data visualization best practices and understand how good visualizations optimize for the human visual system.  \nBe able to generate informative graphical displays including scatterplots, histograms, bar graphs, boxplots, dendrograms and heatmaps and thereby gain exposure to the extensive graphical capabilities of R  \nExample question: What is the R code to generate the following scatterplot including axis labels, point colors and lines?  \nMajor points from lecture 6.  \nUnderstand the structure and syntax of R functions and how to view the code of any R function.  \nUnderstand when you should be writing functions.  \nBe able to follow a step by step process of going from a working code snippet to a more robust function.  \nExample question: What are the major component parts of an R function?  \nMajor points from lecture 7.  \nBe able to find and install R packages from CRAN and bioconductor,  \nUndersta","cbCaiuiFhajMUNe4","https://ap.wps.com/l/cbCaiuiFhajMUNe4","pdf",80025,1,7,"English","en",105,"# Preparing for the Final Exam\n## Exam format and rules\n## Lecture 1: Bioinformatics databases and data representation\n## Lecture 2: Sequence alignment and dynamic programming\n## Lecture 3: Scoring, homology detection, BLAST/PSI-BLAST/HMMER\n## Lecture 4: Using R for bioinformatics data import\n## Lecture 5: Exploratory data analysis and visualization\n## Lecture 6-9: Writing R functions, packages, clustering\n## Lecture 10: Git excluded from the exam\n## Lecture 11-12: Energy/dynamics paradigm, Bio3D, flexibility, docking","[{\"question\":\"What are the exam format and total scoring details for BIMM-143?\",\"answer\":\"The final exam is an open-book, open-notes 150-minute test with 35 questions and 80 total points.\"},{\"question\":\"Which lecture material is explicitly excluded from the BIMM-143 final exam?\",\"answer\":\"Material from lecture 10 (the git version control system) will not be covered on the exam.\"},{\"question\":\"What R-related skills are expected in BIMM-143?\",\"answer\":\"Students should be able to import and parse tsv/csv files, understand core data structures, apply exploratory data analysis and visualization, and use R functions and packages to support reproducible workflows.\"}]","BIMM-143 - 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