BFB10 Biostatistical Foundations in Bioinformatics is now open for applications.
Course dates: November 15th-18th 2010
This course has been designed in order to be maximally useful to those
who need to know the methods in some depth, or in full depth if
appropriate. In that sense it can match the needs of users of
bioinformatics tools, but it can actually provide what
bioinformaticians need in order to implement new tools or modify
existing ones. We will mainly use the R environment.
Course description:
This is one of our ?Foundations? type courses, providing a systematic
and detailed review of fundamental concepts and techniques used in
Bioinformatics. Many analytical and inferential methods, regardless of
their novelty, have their niches of application all over the place in
Bioinformatics. Newer techniques such as the ones employed in high
throughput data analysis are not different in this respect. We will be
looking at statistical methods, digging into their inner workings,
wearing the skins of professional statisticians. Attendees can expect
to attend a thorough set of lectures that will reveal the conceptual
frameworks that are needed to understand the methods, and extensive
hands-on practice, exclusively based on biological examples.
Target Audience
Everybody using Bioinformatics methods is implicitly using statistical
methods. Most people have had one or more semester courses in
Statistics in their graduate education. For many, Statistics happened
in their lives a long a time ago, and that makes it difficult to go
back and manipulate the concepts with full confidence. Moreover,
proper judgment of the results often calls for a deeper level of
understanding than what is required to solve scholarly exercises.
Attending this course is a chance of revisiting subjects like
experimental design, hypothesis testing, inference and prediction in
an intensive and systematic way. We will look into particular areas
such as Bayesian Inference, Hidden Markov Chains and Multivariate
methods with the attitude, eyes and brains of a statistician that
wants to understand how the methods work.
Some of the software that will be used for practicals:
R The R Project for Statistical Computing
WinBugs Bayesian inference Using Gibbs Sampling
PROVID-TMHMM Transmembrane protein topology prediction using hidden
Markov models and evolutionary information
TOP-MOD Topological Mesh Modeler
dChip DNA-Chip Analyzer
BAMarray Bayesian analysis of variance for microarray data
SVM-light, SVM-Struct Support Vector Machine for classification and
regression problems
Methodology
The 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.
More information, including application details at
http://gtpb.igc.gulbenkian.pt/bicourses/BFB10
Information on all GTPB courses at
