Research based on ultra-high-throughput (UHT) sequencing technologies is to a large extent bioinformatics: The aims of the course are: (i) UNDERSTANDING the biological questions adressed with these technologies, the nature of the data (Including noise and artifacts), the current state-of-the-art algorithms to interpret the data, and the computational challenges in the near future. (ii) KNOWING the major application areas of UHT sequencing, (iii) BEING ABLE to learn more from the corresponding scientific litterature. The programme will consist of UHT sequencing technologies, raw data management, base cavelling, de novo and homology-driven assembly of genomes, large-scale genotyping (SNP, CNV), ChiP-seq, transcription start site mapping, gene expression profiling. The topics will be covered by introductory lectures, hands-on practicals, and research seminars by users of UHT sequencing technologies.
The course is designed to provide graduate students in the biomedical sciences with experience in the application of basic statistical analysis techniques to a variety of biological problems.
No prior statistical knowledge is required in order to attend the course, however we strongly recommend you to get familiar with the R statistical analysis package prior attending the course. As the practical exercises will necessitate the use of the R program, you should already be familiar with the command line environment of such tool to avoid spending too much time during the practical exercises with the syntax of the program.
The goal of this course is to expose the participants to 3-dimensional structures of proteins. Analysis and visualization software (DeepView) will be used to display, analyze, compare and interpret protein structures. The second part of the course is dedicated to protein structure prediction using the Swiss-Model expert system for homology modeling.
The course will present an introduction to some of the main publicly available bioinformatics databases and mining tools available to the molecular biologist.
By the end of the course, students will have a working knowledge and a grasp of the underlying principles of a variety of publicly available data and computational tools important to address a range of specific biological problems. The course will cover the following topics: biological data & knowledgebases, sequence alignment and searching biological sequence databases, protein families and functional domain annotation, phylogenetic prediction, genome analysis.
The course is aimed at biomedical graduate students and research scientists with experience in Unix and script programming who would like to expand their programming knowledge for practical biological applications. Audience Ph.D. students and postdoctoral fellows with: Experience in programming (UNIX & PERL). Comparable skills and knowledge of the content of our past EMBnet courses, "Unix & Perl for life science".
The aim of this workshop is to give an insight in the field of protein functions through the use of both computationally derived predictions and large to medium scale protein interactions screen (e.g. yeast two hybrid, tap-tag-immunoprecipitations, siRNA screen).
Traditionally protein functions has been assigned through the use of domain identification, enzymatic activity etc. With the wealth of data provided by the mass sequencing of several genomes this allows the development of several methodologies that could infer functional protein interacting partners [Eisenberg 2000 Nature].
However using these types of data became difficult, this required graph-based approaches, and several tools have been developed. The aim of the workshop is to provide the first step in the use of these tools and the identification of the different resources providing protein-protein interaction data, functional predictions.
Introduction to Bioinformatics
The rapidly increasing number of nucleotide and amino acid sequence data has become a major source of information for biomedical researchers. Knowing how to use appropriate software tools running on powerful computers is a necessity for biologists wanting to identify new genes or new patterns. Too often, students in biology do not even know that these tools are available. Fortunately, the emergence of web interfaces to access databases and analyze sequences has made the field accessible for most scientists.
We think that this introductory course is an important part of the training of every student in Life Sciences.
Computational methods for proteomics data analysis with strong focus on algorithmic solutions
This 2-day workshop is aimed at developers interested in exploring Ensembl beyond the website. The workshop will covers the Ensembl core and compara databases, and how to programmatically access their data. For each databases the API design as well as its most important objects and their methods will be presented. This will be followed by practical sessions in which the participants can put the learned into practice.
Requirements:
Participants are expected to have experience in writing simple Perl scripts and a background in object oriented programming techniques. Being familiar with databases (MySQL) would be an advantage.
Important:
All participants are kindly requested to bring a laptop for the exercises.
The course aims to provide basic knowledge in PERL scripting to biomedical researchers. At the end of the course, participants should be able to write small PERL scripts to:
- Import/export data from/to Excel spreadsheets;
- Retrieve relevant information from a text file and convert it to different formats;