https://cw.fel.cvut.cz/b202/ 2026-04-19T09:27:56+0200 https://cw.fel.cvut.cz/b202/ https://cw.fel.cvut.cz/b202/lib/tpl/bulma-cw/images/favicon.ico text/html 2021-02-12T15:24:27+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/hmmer?rev=1613139867&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 2021-03-29T10:39:41+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/start?rev=1617007181&do=diff Tutorials Tutorial Date Tutor Topic Links 1 15.2. PR Introduction, first assignment, bioinformatics databases Tutorial 1 2 22.2. PR de Bruijn graphs and OLC approaches, Velvet tutorial Tutorial 2 3 1.3. PR Sequence alignment, second assignment text/html 2021-02-12T15:24:27+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial1?rev=1613139867&do=diff Tutorial 1 - Introduction, Assignment: WEB SEARCH, Bioinformatics databases 1 - Biology primer See [slides]. 2 - Assignment 2 - web search Work individually on the first homework assignment. 3 - 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 2021-02-22T15:55:10+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial2?rev=1614005710&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 2021-03-01T12:40:16+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial3?rev=1614598816&do=diff Tutorial 3 - Sequence alignment, second assignment: 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 penalty$\mathrm{gap\_penalty} = -4$$\mathrm{mismatch\_penalty} = -3$$\mathrm{match\_premium} = 5$$\lambda = 0.5$$5$$-3$$4$ text/html 2021-03-08T12:15:17+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial4?rev=1615202117&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}$$ Calculate the consensus sequence. [Adapted from (not available now) <http://www.bii.a-star.edu.sg/docs/education/lsm5192_04/Multiple%20Sequence%20Alignment%20Progressive%20Approaches.pdf>. … text/html 2021-03-22T10:45:50+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial5?rev=1616406350&do=diff Tutorial 5 - UPGMA, Neighbor Joining Problem 1 - UPGMA Using UPGMA reconstruct the phylogenetic tree that is consistent with the given data. Assume a set of sequences $A = \{a, b, c, d, e\}$ and the following distance matrix $\mathbf{D}$. $\mathbf{D}$ $$ \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 2021-02-12T15:24:27+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial6?rev=1613139867&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}$$$ \mathbf{S} = \begin{array}{c c} & \begin{array} {@{} c c c @{}} \hphantom{.}\mathrm{A}\hphantom{.} & \hphantom{.}\mathrm{C}\hphantom{.} & \hphantom{.}\mathrm{G}\hphantom{.} & \hphantom{.}\m… text/html 2021-03-29T10:32:48+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial7?rev=1617006768&do=diff Tutorial 7 - Hidden Markov models In this tutorial, we will study Markov models. Markov model is a four-tuple $(\Sigma, S, P_t, P_0)$ where $\Sigma$$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 2021-02-12T15:24:27+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial8?rev=1613139867&do=diff Tutorial 8 - Hidden Markov models II. Problem 1 - Profile HMM construction Consider the following multiple sequence alignmet. $$ \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} & \mathrm{\_… text/html 2021-02-12T15:24:27+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial9?rev=1613139867&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 2021-04-26T11:48:53+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial10?rev=1619430533&do=diff Tutorial 10 - Gene expression data analysis On the previous tutorial, we looked at the process of collection and assembly of gene expression data. In this tutorial we will reproduce a certain breakthrough experiment [1] (in a simplified scenario, of course) regarding the analysis of such data. This way, we will also learn about the popular dimensionality reduction method PCA. text/html 2021-05-03T14:18:52+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial11?rev=1620044332&do=diff Tutorial 11 - Protein structure, the MODELLER software Recap Make sure you can answer the following questions: “” Secondary 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 2021-05-10T10:15:29+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b202/courses/bin/tutorials/tutorial12?rev=1620634529&do=diff Tutorial 12 - Protein function prediction using propositionalization In this tutorial, we will look into an unconventional method of protein function prediction. We assume to have a labeled set of proteins (i.e. supervised learning scenario) with their structure represented relationally. We will search for patterns in relational data which could be decisive for the protein function.