Skip to content Skip to navigation

Connexions

You are here: Home » Content » Introduction

Navigation

Recently Viewed

This feature requires Javascript to be enabled.

Introduction

Module by: Krzysztof Cyran, Marek Kimmel, Rudy Guerra. E-mail the authors

User rating (How does the rating system work?)
Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

:
(0 ratings)

Summary: This is introductory module to the innovative research-oriented course of Bioinfomatics at the advanced undergraduate or beginnig graduate level. The course concerns computational and statistical methods for problems which are coming to the forefront of bioinformatics as the Human Genome equencing project reaches completion

Course roadmap

The novel research-oriented course of bioinformatics called From Sequence to Expression and Structure is organized into three main parts listed below.

Course structure

  1. Statistical methods for gene expression and gene interaction using DNA-array data as well as other genomic data
  2. Statistical machine learning techniques for bioinformatics
  3. Application of computational geometry and robotics techniques to the study of biomolecules and receptor-ligand interactions

Figure 1: This is a 3 dimensional diagram of the living organism cell
Biological cell
Biological cell (3dcelldna.jpg)

Statistical methods for gene expression

Multiple gene expression techniques allow simultaneous measurement of expression levels of up to 50,000 genes. These novel methods already are being used to classify human cancers as well as to measure expression changes in experimental conditions. This part of the course introduces the student to the techniques and experiments for obtaining gene expression data, as well as the probabilistic and statistical methods for analysis of such data.

The data generated by large scale parallel hybridization techniques, such as DNA microarrays, constitute a new generation of data requiring novel methods of statistical analysis.

Figure 2: This is an enlarged view on a fragment of cDNA microarray. By calculation of the RED/GREEN ratio for each spot (corresponding to one gene)it is possible to determine the concentration of mRNA (gene expression measure) from test and the reference conditions.
DNA array
DNA array (s_protocols199x200.jpg)

You can also refer to the comprehensive presentation of the DNA-Microarray technology

Content actions

Give Feedback:

E-mail the module authors | Rate module ( How does the rating system work?)

Rating system

Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

(0 ratings)

Download:

Module PDF

Add module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections directly in Connexions. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need a Connexions account to use 'My Favorites'.

| A lens (?)

Definition of a lens

Lenses

A lens is a custom view of Connexions content. You can think of it as a fancy kind of list that will let you see Connexions through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to Connexions materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual Connexions member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks