Lectures

Lecture 03: Finding and analyzing signals in biological sequencesThe lecture will focus on the problem of motif detection and discovery in genomic/protein sequences. We will be discussing techniques such as positional weight matrices for motif discovery. There will be an introduction to randomized alogrithms such as Gibbs sampling. We will also discuss the notion of informational entropy in genomic sequences.

Lecture 04: Analyzing sequence similarity with alignment methodsWe will be discussing the problem of pairwise sequence alignment at both global and local levels. There will be an introduction to the notion of dynamic programming and how relevant methods are used in the alignment of biological sequences.

Lecture 05: Analysis of DNA and Chromatin Structure

The lecture is focused on the study of the structure of DNA and its higher order organization in chromatin. After discussing some basic principles on the conformation of the double helix, particular focus will be given on recent advances in the study of the nucleosome positioning and its relation to chromatin function. Last but not least we will be discussing the latest advances in the study of the structure of complete chromosomes and the three-dimensional structure of entire genomes.

Lecture 06: Analyzing sequence evolution. Introduction to Phylogenetic Methods

The lecture is focused on the study of the phylogenetic relationships between organisms. We will be discussing the notion of "phylogenetic distance" and take a closer look at the most common methodologies used for the construction of phylogenetic trees.

Lecture 08: Functional analysis of Gene ExpressionThis chapter is dedicated to the functional study of genes and gene expression. We will be discussing notions related to gene ontology and pathway ontology classifications, means of enrichment analysis and relevant methodologies to address the functional profile of a given gene expression experiment.

Lecture 09: Biological NetworksThis lecture will include a short but concise introduction to the concept of biological networks. Starting from a presentation of the various types of biological networks, we will then go on to discuss the mathematical properties of graphs. After an overview of the quantitative characteristics of networks in general, we will focus our discussion in the differences between random and scale-free networks and show how most of the biological networks fall in the latter category.

Lecture 10: Analysis of Genomic Variation in PopulationsIn this lecture we will be discussing the origins and types of genomic variation in population. After presenting the basic notions of single-nucleotide polymorphisms, copy number variation and their importance for biomedicine, we will shift our focus to the statistical and mathematical methods of their analysis. The lecture will conclude with the presentation of modern approaches of genome-wide analysis of genomic variation such as GWAS and the analysis of complete Exomes.

Lecture 11: big-Data BiologyTaking the ENCODE Project as starting point we will be discussing topics related to the era of big-data in Biology. We will start with an introduction on next-generation sequencing methodologies and how these are re-shaping the way of performing experiments in genome-scale. In the following we will be discussing how bog volumes of data may be accessed and integrated in new analyses.

Lecture 12: Introduction to Systems BiologyIn this (final) lecture we will be building on concepts presented in the previous chapter on large-scale genomics in order to present a systems-approach in the analysis of a real biological problem. After a brief introduction on the concept of "Systems Biology", we will follow, a step-by-step analysis that combines genomic data of different types in order to gain insight into an interesting biological question. In this context, we will see how we can employ machine learning methodologies in the analysis of biological data.