IRIC's Bioinformatics Platform

Good resources to learn R

Since it's the summer vacations, why not take some time to learn R. There are numerous free resources online to dive into this powerful language. For whomever wants to learn it, the challenge more related to finding the time rather than finding resources. Videos Coursera is an inevitable for online learning. There are a few good video courses offered for R beginners that are more or less oriented toward genomics : https://www.coursera.org/learn/r-programming https://www.coursera.org/learn/exploratory-data-analysis https://www.coursera.org/learn/bioconductor (Bioconductor is a life science packages [...]

By Geneviève|2017-04-29T16:57:17+00:00July 11, 2016|Categories: Bioinformatics, R|Tags: beginner|0 Comments

SciPy and Logistic Regressions

Given a set of data points, we often want to see if there exists a satisfying relationship between them. Linear regressions can easily be visualized with Seaborn, a Python library that is meant for exploration and visualization rather than statistical analysis. As for logistic regressions, SciPy is a good tool when one does not have his or her own analysis script. Let's look at the optimize package from scipy.optimize import [...]

By Caroline|2017-04-29T16:58:35+00:00June 9, 2016|Categories: Data Analysis, Python|Tags: chemical screen, curve fitting|0 Comments

Realize your Bash potential

A bioinformatician's best tool is his shell. While some have already mastered the dark arts of the bash shell, I often see beginners (and even catch myself at times!) unknowingly repeating key sequences when they could be getting the same result with a few simple built-in keybindings or programmatic shortcuts. Let's have a look at some of the most useful bash shortcuts that no self-respecting bioinformatician should be without. This is by no means an exhaustive list of what Bash has to offer but will hopefully serve to save [...]

By Jonathan|2017-04-29T22:57:32+00:00May 26, 2016|Categories: Computer science, Shell scripting|0 Comments

Machine learning in life science

Machine learning's popularity is increasing among bioinformaticians and biologists as it gives interesting results and has become more accessible than ever. A machine learning model can now be easily applied on a given dataset using R or Python packages. For example, the Python package Scikit-learn provides several algorithms (Random Forest, Support Vector Machine - SVM -, regression model and much more) and good documentation. Even deep machine learning (neural networks with multiple layers or convolutional networks for example) is more accessible [...]

By Geneviève|2016-11-08T09:30:05+00:00May 18, 2016|Categories: Machine learning|0 Comments

The language(s) of bioinformatics

The most recurrent question I get regarding bioinformatics is unfortunately the one that leads to the least productive discussions I've participated in: Which programming language should I use for bioinformatics? Don't get me wrong, in a pub, over a beer, this can lead to some lively entertainment among the nerd intelligentsia... but rarely does it lead to enlightenment that persists in the morning! Here, I'd like to share the current answer I have honed over the past years. It is based [...]

By Sébastien|2017-04-29T16:59:22+00:00April 18, 2016|Categories: Bioinformatics|Tags: beginner|0 Comments