https://cw.fel.cvut.cz/b222/ 2026-04-19T10:19:59+0200 https://cw.fel.cvut.cz/b222/ https://cw.fel.cvut.cz/b222/lib/tpl/bulma-cw/images/favicon.ico text/html 2023-02-17T10:18:21+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/hmmer?rev=1676625501&do=diff HMMER This tutorial follows the HMMER User’s Guide written by Sean R. Eddy, Travis J. Wheeler and the HMMER development team. Thanks. Problem 1 - Install HMMER First of all, we download HMMERv3.1b2 from <http://hmmer.org> and unpack it. wget http://eddylab.org/software/hmmer3/3.1b2/hmmer-3.1b2.tar.gz tar xfv hmmer-3.1b2.tar.gz cd hmmer-3.1b2 text/html 2023-04-26T11:17:44+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/start?rev=1682500664&do=diff Tutorials Tutorial Date Tutor Topic Links 1 20.2. PR Introduction, first assignment, bioinformatics databases Tutorial 1 2 27.2. PR de Bruijn graphs and OLC approaches, Velvet tutorial Tutorial 2 3 6.3. PR Sequence alignment, second assignment text/html 2023-02-17T10:18:21+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial1?rev=1676625501&do=diff Tutorial 1 - Introduction, Assignment: WEB SEARCH, Bioinformatics databases 1 - Biology primer See [slides]. 2 - In lab web search Use google, NCBI database, Ensembl genome assembly, ENA archive, Wikipedia, UniProt or whatever you need to answer the following questions. text/html 2023-02-27T14:08:41+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial2?rev=1677503321&do=diff Tutorial 2 - de Bruijn and Overlap graphs, Velvet tutorial Problems TAATGCCATGGGATGTT$k=3$$k=5$TGGCAGCATTGCAATGCAATCAATTATTTGAC$k=4$$k=5$ Practical Example In this tutorial, we are going to de-novo assembly a genome of an unknown organism. First, download the read data: text/html 2023-03-06T12:30:25+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial3?rev=1678102225&do=diff Tutorial 3 - Sequence alignment Problem 1 - score of an alignment Calculate the score of alignment PRT---------EINS YRNWPSEEN- Use BLOSUM62 scoring matrix and affine gap penalty with gap opening cost 11 and gap extension cost 1. gap opening penaltygap opening penalty + gap extension penalty$\mathrm{gap\_penalty} = -4$$\mathrm{mismatch\_penalty} = -3$$\mathrm{match\_premium} = 5$$\lambda = 0.5$$5$$-3$$4$ text/html 2023-03-06T12:30:48+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial4?rev=1678102248&do=diff Tutorial 4 - BLAST, Star Alignment, Clustal Omega Problem 1 - Multiple Sequence Alignment Score Calculate the score of the following alignment sum-of-pairs$+4$$-2$$-1$$s(\_,\_)=0$entropy $$\begin{array}{l} \mathtt{MQPILL\_G} \\ \mathtt{MLR\_LL\_G} \\ \mathtt{MK\_ILLL\_} \\ \mathtt{MPPVLLI\_} \end{array}$$ Calculate the consensus sequence. [Adapted from (not available now) <http://www.bii.a-star.edu.sg/docs/education/lsm5192_04/Multiple%20Sequence%20Alignment%20Progressive%20Approaches.pdf>. … text/html 2023-02-17T10:18:21+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial5?rev=1676625501&do=diff Tutorial 5 - UPGMA, Neighbor Joining Problem 1 - UPGMA Using UPGMA reconstruct the phylogenetic tree that is consistent with the given data. Assume a set of sequences $A = \{a, b, c, d, e\}$ and the following distance matrix $\mathbf{D}$. $\mathbf{D}$ $$ \mathbf{D} = \begin{bmatrix} 0 & - & - & - & - \\ 12 & 0 & - & - & - \\ 12 & 4 & 0 & - & - \\ 12 & 6 & 6 & 0 & - \\ 12 & 6 & 6 & 2 & 0 \\ \end{bmatrix} \begin{array} \\ a \\ b \\ c \\ d \\ e \end{arra… text/html 2023-02-17T10:18:21+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial6?rev=1676625501&do=diff Tutorial 6 - Phylogenetic trees - parsimony and probabilistic approaches Problem 1 - Fitch's algorithm Using the Fitch algorithm, compute the total parsimony score under the Hamming distance and determine internal node labels. Problem 2 - Sankoff's algorithm (weighted parsimony) $\mathbf{S}$$$ \mathbf{S} = \begin{array}{c c} & \begin{array} {@{} c c c @{}} \hphantom{.}\mathrm{A}\hphantom{.} & \hphantom{.}\mathrm{C}\hphantom{.} & \hphantom{.}\mathrm{G}\hphantom{.} & \hphantom{.}\m… text/html 2023-04-17T13:14:22+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial7?rev=1681730062&do=diff Tutorial 7 - Hidden Markov models In this tutorial, we will study Markov models. Markov model is a four-tuple $(\Sigma, S, P_t, P_0)$ where $\Sigma$$S$$P_t : S \times S \mapsto [0,1]$$P_0 : S \mapsto [0, 1]$ The Markovian property is useful as for any sequence $x \in \Sigma^*$ $$ P(x) = P_0(x_1) \cdot P_t(x_2 \mid x_1) \cdot P_t(x_3 \mid x_2) \cdots P_t(x_l \mid x_{l-1}). $$ Hidden Markov models separate states from the observable symbols. Each state generates a symbol that is visible to… text/html 2023-04-24T13:40:19+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial8?rev=1682336419&do=diff Tutorial 8 - Hidden Markov models II. Problem 1 - Profile HMM construction Consider the following multiple-sequence alignment: $$ \begin{array} \mathrm{A} & \mathrm{C} & \mathrm{D} & \mathrm{E} & \mathrm{F} & \mathrm{A} & \mathrm{C} & \mathrm{A} & \mathrm{F} \\ \mathrm{A} & \mathrm{F} & \mathrm{D} & \mathrm{A} & \mathrm{\_} & \mathrm{\_} & \mathrm{\_} & \mathrm{C} & \mathrm{F} \\ \mathrm{A} & \mathrm{\_} & \mathrm{\_} & \mathrm{E} & \mathrm{F} & \mathrm{D} & \mathr… text/html 2023-02-17T10:18:21+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial9?rev=1676625501&do=diff Tutorial 9 - RNA-Seq - alignment, abundance quantification and differential expression analysis Introduction Analysis of differential gene expression is one of the most popular bioinformatics tasks. Each particular gene can be either turned on or off. This process regulates the amount of produced proteins in each cell, allowing it to react to a lack of minerals or change its type from stem cell to neuron. It is, however, problematic to measure protein levels directly. Therefore scientists deve… text/html 2023-05-09T09:11:11+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial10?rev=1683616271&do=diff Tutorial 10 - Gene Ontology Gene Ontology is the world’s largest knowledgebase of the functions of genes. In this tutorial we will demonstrate its utilization for set-level analysis of gene expression data: The set level gene expression analysis may bring additional knowledge about the disease under study as the straightforward detection of differentially expressed genes may not be not sensitive enough to detect the subtle differences between the expression patterns in both the groups. Disease… text/html 2023-05-22T16:07:18+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial11?rev=1684764438&do=diff Tutorial 11 - Protein structure, the MODELLER software Recap Make sure you can answer the following questions: “” Homology modeling - protein structure prediction exercise A simple, although not always reliable, way to discover the secondary structure of a peptide sequence is to look up a protein with similar primary sequence in a database. Let us try this! The task is to obtain the secondary structure of the following peptide sequence: text/html 2023-03-20T08:39:16+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b222/courses/bin/tutorials/tutorial12?rev=1679297956&do=diff Tutorial 12 - Motif discovery In this tutorial, we will practise the motif discovery algorithms learned during the motif finding lecture. A simple problem Consider the following set of DNA sequences: $$ \begin{array} \mathrm{A} & \mathrm{A} & \mathrm{C} & \mathrm{T} & \mathrm{G} & \mathrm{A}\\ \mathrm{A} & \mathrm{C} & \mathrm{T} & \mathrm{C} & \mathrm{C} & \mathrm{A}\\ \mathrm{C} & \mathrm{G} & \mathrm{G} & \mathrm{A} & \mathrm{C} & \mathrm{T}\\ \end{array} $$ T…