First steps with Python in Life Sciences

Overview

First steps with Python in Life Sciences

This course material is part of the "First Steps with Python in Life Science" three-day course of SIB-training and is addressed to beginners wanting to become familiar with the Python syntax, environment, and the most common commands.

This course material provides an introduction to python and jupyter notebooks (a web based notebook system for creating and sharing computational documents) in an interactive manner.

prerequisite installation

You can find tips and instructions to ensure you have installed all the required software before starting the course.

course material organization

The course revolves around a sery of jupyter notebooks which take you on your first steps in you python journey.

Each jupyter notebook interleaves theory and examples of codes. We heartily recommend you execute and play around with these bits of code as you follow along : in programming, perhaps even more than anywhere else, practice makes perfect.

Additionally, each notebook is associated with a number of exercises (often in a separate notebook) of varying difficulty, with associated corrections.

If you are attending this course with a teacher (or if you are just curious), you can take a look at our schedule. In short, lessons 00 to 04 deals with generalistic aspect of the python language, while notebooks 05 or 08 present some of the most common modules used in data analysis and/or life sciences.

The notebooks/ folder contains each lesson:

Exercise notebooks:

The data used in the practicals can be found in the data notebooks/data folder, and solutions codes can be found in the notebooks/solutions/ folder (NB: micro-exercises do not have a correction).

You might also like...
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an

Statsmodels: statistical modeling and econometrics in Python

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

A computer algebra system written in pure Python

SymPy See the AUTHORS file for the list of authors. And many more people helped on the SymPy mailing list, reported bugs, helped organize SymPy's part

ForecastGA is a Python tool to forecast Google Analytics data using several popular time series models.
ForecastGA is a Python tool to forecast Google Analytics data using several popular time series models.

ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.

Multiple Pairwise Comparisons (Post Hoc) Tests in Python
Multiple Pairwise Comparisons (Post Hoc) Tests in Python

scikit-posthocs is a Python package that provides post hoc tests for pairwise multiple comparisons that are usually performed in statistical data anal

Hidden Markov Models in Python, with scikit-learn like API

hmmlearn hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models. For supervised learning learning of HMMs and

Deep universal probabilistic programming with Python and PyTorch
Deep universal probabilistic programming with Python and PyTorch

Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab

Fast, flexible and easy to use probabilistic modelling in Python.
Fast, flexible and easy to use probabilistic modelling in Python.

Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic

Comments
  • Module 2-create your own functions - text columns

    Module 2-create your own functions - text columns

    Your tutorials are fantastic! minor format issues: the multiple column format in some pages (ex: module 2 in python training) collapse the text and making it unreadable. Hope to see it fixed to complete the tutorial! thank you.

    opened by catalicu 1
Releases(October2022)
Owner
SIB Swiss Institute of Bioinformatics
SIB Swiss Institute of Bioinformatics
MIR Cheatsheet - Survival Guidebook for MIR Researchers in the Lab

MIR Cheatsheet - Survival Guidebook for MIR Researchers in the Lab

SeungHeonDoh 3 Jul 02, 2022
Data Analysis for First Year Laboratory at Imperial College, London.

Data Analysis for First Year Laboratory at Imperial College, London. For personal reference only, and to reference in lab reports and lab books.

Martin He 0 Aug 29, 2022
Dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

Dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

dbt Labs 6.3k Jan 08, 2023
This program analyzes a DNA sequence and outputs snippets of DNA that are likely to be protein-coding genes.

This program analyzes a DNA sequence and outputs snippets of DNA that are likely to be protein-coding genes.

1 Dec 28, 2021
Python implementation of Principal Component Analysis

Principal Component Analysis Principal Component Analysis (PCA) is a dimension-reduction algorithm. The idea is to use the singular value decompositio

Ignacio Darago 1 Nov 06, 2021
.npy, .npz, .mtx converter.

npy-converter Matrix Data Converter. Expand matrix for multi-thread, multi-process Divid matrix for multi-thread, multi-process Support: .mtx, .npy, .

taka 1 Feb 07, 2022
A set of procedures that can realize covid19 virus detection based on blood.

A set of procedures that can realize covid19 virus detection based on blood.

Nuyoah-xlh 3 Mar 07, 2022
A project consists in a set of assignements corresponding to a BI process: data integration, construction of an OLAP cube, qurying of a OPLAP cube and reporting.

TennisBusinessIntelligenceProject - A project consists in a set of assignements corresponding to a BI process: data integration, construction of an OLAP cube, qurying of a OPLAP cube and reporting.

carlo paladino 1 Jan 02, 2022
Implementation in Python of the reliability measures such as Omega.

reliabiliPy Summary Simple implementation in Python of the [reliability](https://en.wikipedia.org/wiki/Reliability_(statistics) measures for surveys:

Rafael Valero Fernández 2 Apr 27, 2022
This repo contains a simple but effective tool made using python which can be used for quality control in statistical approach.

This repo contains a powerful tool made using python which is used to visualize, analyse and finally assess the quality of the product depending upon the given observations

SasiVatsal 8 Oct 18, 2022
Improving your data science workflows with

Make Better Defaults Author: Kjell Wooding [email protected] This is the git re

Kjell Wooding 18 Dec 23, 2022
Handle, manipulate, and convert data with units in Python

unyt A package for handling numpy arrays with units. Often writing code that deals with data that has units can be confusing. A function might return

The yt project 304 Jan 02, 2023
Data Competition: automated systems that can detect whether people are not wearing masks or are wearing masks incorrectly

Table of contents Introduction Dataset Model & Metrics How to Run Quickstart Install Training Evaluation Detection DATA COMPETITION The COVID-19 pande

Thanh Dat Vu 1 Feb 27, 2022
Fit models to your data in Python with Sherpa.

Table of Contents Sherpa License How To Install Sherpa Using Anaconda Using pip Building from source History Release History Sherpa Sherpa is a modeli

134 Jan 07, 2023
Ejercicios Panda usando Pandas

Readme Below we add configuration details to locally test your application To co

1 Jan 22, 2022
Learn machine learning the fun way, with Oracle and RedBull Racing

Red Bull Racing Analytics Hands-On Labs Introduction Are you interested in learning machine learning (ML)? How about doing this in the context of the

Oracle DevRel 55 Oct 24, 2022
A Python adaption of Augur to prioritize cell types in perturbation analysis.

A Python adaption of Augur to prioritize cell types in perturbation analysis.

Theis Lab 2 Mar 29, 2022
PyPDC is a Python package for calculating asymptotic Partial Directed Coherence estimations for brain connectivity analysis.

Python asymptotic Partial Directed Coherence and Directed Coherence estimation package for brain connectivity analysis. Free software: MIT license Doc

Heitor Baldo 3 Nov 26, 2022
PipeChain is a utility library for creating functional pipelines.

PipeChain Motivation PipeChain is a utility library for creating functional pipelines. Let's start with a motivating example. We have a list of Austra

Michael Milton 2 Aug 07, 2022
Very basic but functional Kakuro solver written in Python.

kakuro.py Very basic but functional Kakuro solver written in Python. It uses a reduction to exact set cover and Ali Assaf's elegant implementation of

Louis Abraham 4 Jan 15, 2022