Computational Biology

The availability of large amounts of high throughput omics data gives us new insights and a better understanding of the molecular mechanisms of life. This course revolves around two commonly asked questions:

• how can we transform this data into useful bioinformation?
• what can we learn from this kind of information?

This course will introduce the basic concepts and tools essential for this transformation process. Background information on frequently used computational tools for DNA, RNA, and protein sequence analysis is mixed with practical, hands-on elements consisting of exercises demonstrating important basic bioinformatics concepts.

The course is divided in a number of modules:

1. Building blocks of life.
   This initial part presents an introduction in primary DNA and protein sequence analysis. In this module it is explained what kind of information we can and cannot extract from a primary DNA and protein sequence.Topics include gene architecture, reading frames, intervening sequences, translation of a nucleotide sequence to protein, amino acids characteristics.

2. Global analysis of DNA, mRNA, protein sequences: the "omics".
   This second block presents an introduction in the technological and bioinformatics solutions for the analysis of genomic, transcriptomic and proteomic data. Topics include assembly and mapping of reads, differential expression analysis of transcripts, multiple testing correction, annotation of DNA and protein sequences using ontologies, high-throughput tandem mass spectrometry of peptides and proteins (LC-MS/MS), identification and quantification of proteins, use of a decoy database and calculation of false discovery rates.

3. FAIR data and databases.
   This third block will give you a chance to learn about the best ways of searching and storing public information and your scientific data. Topics include FAIR (Findable, Accessible, Interoperable, and Reusable) data principles, exploring NCBI, EMBL, UniProt public sequence databases, searching PubMed, gaining and summarizing information.

4. Individual sequence alignment.
   This part concerns methods used to learn more about a specific sequence. It dives into homology and similarity by looking at pairwise sequence alignment and basic sequence database search methods. Topics include PAM and BLOSUM matrices, BLAST algorithm for comparing primary biological sequence information, matrix derived raw-scores, bit-scores and E-values;

5. Sequence-defined properties.
   This block presents the bioinformatics solutions to the problem of predicting protein cellular localization and how multiple sequence alignments help to elucidate the possible function(s) of novel proteins. Topics include standard tools for extraction of topological signals based on AI, identific

• Identify the amino acids characteristics relevant for protein structure and function

• Explain the concepts behind widely used computational tools in bioinformatics (i.e. algorithms for DNA assembly, sequence alignment, translation into protein sequences, identification of protein motifs, topological signals and protein structure prediction)

• Recognize advantages and shortcomings of standardly used databases that store text, nucleotide and protein sequences

• Apply methods for DNA and protein sequence and structure analysis to (simple) real life biological problems

• Illustrate advantages and shortcomings of common computational tools for DNA and protein sequence analysis, for topological signal and 3D protein structure prediction

• Assess applications and limitations of “omics” derived information with respect to the biological questions involved

• Outline basic biological questions that can be addressed using the computational tools studied in this course

• Written test with open and closed questions (40%) Closed book written digital exam via BYOD. Rounding is performed only once on the final weighted average mark between the exam and the assignment.
• Assignment report (60%) To participate in the final assignment students must submit at least 80% of the practical exercises (including the ones marked as compulsory) by the in-course deadlines. The report is evaluated via a Rubric, made available to students. When failing the final assignment, a completely new report needs to be produced on different starting sequences. Report and/or exam can be resat in p1, p5 and Resit C for a maximum of 2 chances per academic year.

Cell Biology (CBI10306), Microbiology & Biochemistry (MIB10306), Gene Technology (MOB20306)

• Book: Introduction to Bioinformatics Arthur Lesk Fifth edition ISBN: 9780198794141 Course lectures, additional reading and hands-on exercises are available on Brightspace. Software are available via a dedicated server.