|
|
|
ABBTU13 Advanced Biostatistics for Bioinformatics Tool Users |
|
IMPORTANT DATES for this Course
Candidates with adequate profile will be accepted in the next 72 hours after the application, until we reach 20 participants. |
Instructors: |
Lisete Sousa is an Assistant Professor in Faculty of Sciences of the University
of Lisbon (FCUL), and coordinates the MSc in Biostatistics. She is an integrated member of the Center of Statistics
and Applications (CEAUL) since 2004 when she obtained her PhD in Probability and Statistics (Lisbon University and
Dortmund University - Germany). Since then she has taught the course Statistical Methods in Bioinformatics
in the University of Lisbon, among other statistical courses for BSc. and MSc. Since 2001, her main research interests
are the development of statistical methodologies for detecting differentially expressed genes, and the prediction of
transmembrane proteins topology based on hidden Markov models but adopting a Bayesian perspective. She collaborates with
researchers from Instituto de Medicina Molecular (IMM) and Instituto de Ciência Aplicada e
Tecnologia of FCUL (ICAT). She has been a GTPB instructor in the BFB course in 2010 and 2012. |
Carina Silva Fortes graduated in Statistics and Operational Research and holds a MSc degree in Probability and
Statistics from Faculdade de Ciências da Universidade de Lisboa. She is Adjunct Professor at Escola Superior de
Tecnologia da Saúde de Lisboa (ESTeSL - IPL) and teaches Applied Mathematics and Biostatistics there. She obtained
a PhD in Probability and Statistics in 2012. She has coordinated the course "Statistical Data Analysis with R" at ESTeSL. She is a member
and collaborator of CEAUL (Center of Statistics and Applications). She is the Coordinator of
the scientific area of Mathematics of ESTeSL. Her main research interests are Statistics in Health Sciences, ROC analysis,
Molecular Genetics (Microarray Data Analysis) and Bayesian Statistics. She has been a GTPB instructor in the BFB course in
2010, 2011 and 2012. |
Course description |
This is one of our "Foundations" type courses, providing a systematic and detailed review of fundamental concepts and techniques used in
Bioinformatics. This course is a standalone advanced Biostatistics course that can be taken as a continuation of the Introductory
Biostatistics for Bioinformatics (IBB) course that precedes it in GTPB. It is targeted for Biostatistical techniques often employed in
analytical tools for high throughput data and multivariate data. Participants can expect to attend a thorough set of lectures that will
reveal the conceptual frameworks that are needed to understand the methods. Extensive hands-on practice will be the main vehicle for providing
the skills and user independence. To keep things in context, the course is exclusively based on biological examples.
MethodologyThe course will introduce a relatively high number of concepts and methods. To keep it highly practical, we will spend most of the time in hands-on sessions.- We will focus on each method using examples taken from real world Bioinformatics practice. - We will then dissect the method, identifying the concepts and exploring their interrelationships. - The applicability and limitations of each method will be emphasized. - The use of the method will be illustrated using appropriate Bioinformatics tools and biological data resources. |
Target Audience
Everybody using Bioinformatics methods is implicitly using statistical methods. Moreover, proper judgment of the results often calls for a deeper
level of understanding than what is required to solve scholarly exercises. |
Course Pre-requisitesIntermediate knowledge in Statistics is necessary.Elementary skills in computer usage are also needed. We will assume that all the participants have checked their knowledge in: - probability - conditional probability - distributions - statistical tests - hypothesis testing - inference This level can also be obtained by attending the previous course in GTPB: The IBBTU course. Basic Familiarity with the R environment will be necessary. |
|
Detailed Program |
|
Instituto Gulbenkian de Ciência, Apartado 14, 2781-901 Oeiras, Portugal Last updated: May 30th 2013 |