Fundamental Models and Algorithms in Bioinformatics
INFO I519 (= I617) Fall 2023
Course description
INFO I519 FMAB
Class times and locations
Mon, Wed 3:00p - 4:15p (Credits: 3.0); Swain West (SW) 217
Computer Laboratory, Fri 9:45a - 11:00a; Radio-TV (TV) 186
Tentative schedule
HTML version of this schedule
| DAY | DATE | LECTURE | TOPIC | LECTURER | Mon | Aug 21 | 1.1 | Orientation Topics in bioinformatics, scope of class, and resources Catch-up for non-life scientists: An introduction to DNA (Khan Academy) Module 1: Bioinformatics resources and workspacesNational Center for Biotechnology Information (NCBI), a great starting point for "anything" bioinformatics Sequence gazing: ... the famous TATA-box Mapping biological question onto computational problems: The Modeling Spiral Precision matters: Webb Telescope Aim high: AlphaFold Ubuntu on Windows: ... a quick way to get to a command line terminal Virtual Machines: VirtualBox VMware | Volker Brendel |
| Wed | Aug 23 | 1.2 | Basic bioinformatics toolkit acquisition (Part I) Entrez Direct Guide: NCBI E-Utilities ... slides Background notes on: Installing NCBI EDirect EDirect Sample Code Explained | Volker Brendel |
| Fri | Aug 25 | L1.1 | Computer Laboratory: Linux Basics Basic UNIX shell tutorial The UNIX Shell The UNIX Shell: Summary of Basic Commands vi(m) editor tutorial | AI |
| Mon | Aug 28 | 1.3 | Mapping biological question onto computational problems: The modeling spiral Polistes dominula proteins SeqKit SeqKit Tutorial Entrez Direct NCBI Sequence search fields MEDLINE/PubMed search fields | Volker Brendel |
| Wed | Aug 30 | 1.4 | IU Supercomputing for Everyone IU Carbonate IU Research Desktop Apptainer Apptainer User Guide | Volker Brendel |
| Fri | Sept 1 | L1.2 | Computer Laboratory: Basic bioinformatics toolkit acquisition (Part II): Getting code: git GitHub Brendel Group on GitHub GitHub HowTo git: working with branches CodeFMAB | AI |
| Mon | Sept 4 | 2.1 | Module 2: Sequence Models and SpacesLabor Day | no class |
| Wed | Sept 6 | 2.2 | Simple Sequence Models | Volker Brendel |
| Fri | Sept 8 | L2.1 | Computer Laboratory: Python Basics Python tutorial Python Scripting for Computational Molecular Science Python for Everybody PY4E Lessons J. Sundnes: Introduction to Scientific Programming with Python Style matters ... Learning Scientific Programming with Python - an intriguing resource | AI |
| Mon | Sept 11 | 2.3 | Markov Models for Sequences | Volker Brendel |
| Wed | Sept 13 | 2.4 | Applications of Markov Models GENMARK Some resources for statistics background review: Event probabilities Union of events Bayes Theorem Probability distribution Expected value Review: Conditional Probability Sensitity, specificity, and all that Stat225 at Purdue - nice slides by Dr. Whitney Huang | Volker Brendel |
| Fri | Sept 15 | L2.1 | Computer Laboratory: Coding random sequence generation and pattern probability calculations | AI |
| Mon | Sept 18 | 3.1 | Module 3: Pairwise Sequence AlignmentModels for Pairwise Sequence Alignment Representations of alignments NW alignments Number of alignments (nNW algorithm) | Volker Brendel |
| Wed | Sept 20 | 3.2 | PWSA: gNW algorithm. | Volker Brendel |
| Fri | Sept 22 | L3.1 | Computer Laboratory: Coding the nNW and gNW algorithms | AI |
| Mon | Sept 25 | 3.3 | Algorithms for Pairwise Sequence Alignment: gSW, lSW, and other algorithms How Do We Compare Biological Sequences? (from Bioinformatics: An Active Learning Approach) | Volker Brendel |
| Wed | Sept 27 | 3.4 | PWSA: Review and extensions. | Volker Brendel |
| Fri | Sept 20 | L3.2 | Computer Laboratory: Coding PWSA algorithms. | AI |
| Mon | Oct 2 | 4.1 | Module 4: Sequence Analysis with ScoresSequence Analysis with Scores: Theory | Volker Brendel |
| Wed | Oct 4 | 4.2 | Sequence analysis with scores: Substitution scoring matrices Biological Sequence Analysis I (Lecturer: Dr. Andy Baxevanis) NCBI BLAST slides for Sequence Analysis I presentation handout for Sequence Analysis I presentation NCBI BLAST download site | Volker Brendel |
| Fri | Oct 6 | Computer Laboratory: | AI | |
| Mon | Oct 9 | 4.3 | Sequence Analysis with Scores: Applications Chance and Statistical Significance in Protein and DNA Sequence Analysis Expected Values I Expected Values II | Volker Brendel |
| Wed | Oct 11 | 4.4 | Brief review and outlook | Volker Brendel |
| Fri | Oct 13 | L4.2 | Fall Break: no class | |
| Mon | Oct 16 | 5.1 | Module 5: Hidden Markov ModelsHidden Markov Models: Motivation Rabiner's Tutorial | Volker Brendel |
| Wed | Oct 18 | 5.2 | Hidden Markov Models: Algorithms Hidden Markov Models (from Bioinformatics: An Active Learning Approach) | Volker Brendel |
| Fri | Oct 20 | L5.1 | Computer Laboratory: Coding and applications of HMM algorithms | AI |
| Mon | Oct 23 | 5.3 | Hidden Markov Models: Applications Application examples GENSCAN Profile Hidden Markov Models TagDust Tagdust2 on github Sequence motifs: models Biological Sequence Analysis II (Lecturer: Dr. Andy Baxevanis) InterPro | Volker Brendel |
| Wed | Oct 25 | 5.4 | Sequence motifs: algorithms HMMER The MEME Suite HOMER | Volker Brendel |
| Fri | Oct 27 | L5.2 | Computer Laboratory: Implementation of HMM algorithms | AI |
| Mon | Oct 30 | 6.1 | Module 6: Basic Concepts of Molecular PhylogeneticsThe Molecular Clock Linus Pauling Molecular Phylogeny: Models The powers and pitfalls of parsimony | Volker Brendel |
| Wed | Nov 1 | 6.2 | Parsimony and Distance Matrix Methods Lectures on molecular phylogeny (from Bioinformatics: An Active Learning Approach) | Volker Brendel |
| Fri | Nov 4 | L6.1 | Computer Laboratory: Molecular Phylogeny, applications | AI |
| Mon | Nov 6 | 6.3 | Molecular Phylogeny: Applications ... some proteins to analyze MEGA A list of Web-servers for molecular phylogeny analyses phylogeny.fr | Volker Brendel |
| Wed | Nov 8 | 6.4 | Brief review and outlook A first look at Genome Assembly | Volker Brendel |
| Fri | Nov 10 | L7.1 | Exploration of genome sequencing by simulation and genome assembly | AI |
| Mon | Nov 13 | 7.1 | Module 7: Genome Assembly and AnnotationDNA Sequencing Sanger sequencing Illumina sequencing nanopore sequencing Genome Resources The Genomic Landscape circa 2016 (Lecturer: Dr. Andy Green) Assembly basics NCBI Assembly Help NCBI Genome Genome Assembly Introduction to genome sequencing How do we assemble genomes? from Bioinformatics Algorithms: An Active Learning Approach How to set up, execute, and document a project | Volker Brendel |
| Wed | Nov 15 | 7.2 | Guest Lecture: Dr. Ryan Bracewell: A nematode sequencing project Genome Annotation Prokaryotic gene finding: GeneMark.hmm prokaryotic GeneMark article Eukaryotic gene finding: GeneMark.hmm eukaryotic AUGUSTUS GENSCAN; paper see here Sensitivity, specificity, and all that sample paper How to evaluate gene structure prediction accuracy Project Assignment Posted | Volker Brendel |
| Fri | Nov 17 | L7.1 | Computer Laboratory: wgsim - read generator SoapDeNovo2 - assembler | AI |
| Mon | Nov 21 | THANKSGIVING BREAK | n/a | |
| Wed | Nov 23 | THANKSGIVING BREAK | n/a | |
| Fri | Nov 25 | THANKSGIVING BREAK | n/a | |
| Mon | Nov 27 | 8.1 | Module 8: Genetic VariationGenetic variation Interpreting an individual genome NCBI dbSNP How To NCBI dbVar How To 1000 Genomes Project Nature 491:56 Example: rs1131769 file format specifications: Variant Call Format (VCF) Sequence Alignment Map format (SAM) SAM flags explained Pileup format (used by samtools) Relevant code: NCBI SRA Toolkit samtools bwa freebayes | Volker Brendel |
| Wed | Nov 29 | 9.1 | Module 9: Protein Structurepeptide bond Ramachandran plot ... very nice visualization thereof (thanks to Prof. Eric Martz) PDB: What is a protein? PDB: How enzymes work HIV I HIV II Guide to PDB PDB Molecule of the Month NCBI Protein Secondary Structure 2struct server Jpred - secondary structure prediction SPIDER3 foldit AlphaFold | Volker Brendel |
| Fri | Dec 1 | L7.2 | Project Assignment Due | AI |
| Mon | Dec 4 | Review SessionsSequence Alignment Bioinformatics Algorithms presentation | Volker Brendel | |
| Wed | Dec 6 | Gene Expression Analyses from Bioinformatics Algorithms: An Active Learning Approach MIT Lecture: Gene Regulatory Networks MIT Data Science: Clustering | Volker Brendel | |
| Fri | Dec 8 | Office hour | AI | |
| Wed | Dec 13 | 7:20pm | Final Project due | Students |