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Keywords: computer-science  or Python 


How to use Python and R with RDF Data

How to use Python and R with RDF Data is a training that was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and is part of a series of trainings centred around the [SPHN Interoperability...

Scientific topics: Medical informatics, FAIR data, Data management, Computer science

Operations: Data retrieval, Data handling, Query and retrieval

Keywords: Clinical data, SPARQL, Query data, RDF, Knowledge graph, Python, R, GraphDB

Resource type: Video, Training materials, Mock data, E-learning

Introduction à la programmation Python pour la biologie

Cours de Python pour des biologistes par Patrick Fuchs et Pierre Poulain.

Keywords: Python, Programming, Python for Biologists

DE-Sim examples, tutorials, and documentation

DE-Sim is an open-source, Python-based object-oriented discrete-event simulation (DES) tool that makes it easy to use large, heterogeneous datasets and high-level data science tools such as NumPy, Scipy,...

Scientific topics: Computational biology, Mathematics, Computer science, Simulation experiment

Operations: Visualisation, Modelling and simulation

Keywords: data-driven modeling, Computational modelling, discrete-event simulation, DES, object-oriented programming, Python, data visualization, Data Science

Resource type: examples, Tutorial, Jupyter notebook, API reference

Big Data, Genes, and Medicine

This course distills for you expert knowledge and skills mastered by professionals in Health Big Data Science and Bioinformatics. You will learn exciting facts about the human body biology and chemistry, genetics, and medicine that will be intertwined with the science of Big Data and skills to...

Keywords: life-sciences, computer-science, bioinformatics, algorithms

Bioinformatics Capstone: Big Data in Biology

In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data.

In particular, in a series of Application Challenges will see how genome assembly can be used...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Finding Hidden Messages in DNA (Bioinformatics I)

Named a top 50 MOOC of all time by Class Central!

This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat.

In the first half of the...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Finding Mutations in DNA and Proteins (Bioinformatics VI)

In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins.

In the first half of the course, we would like to ask how an individual's genome differs from the...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Genome Sequencing (Bioinformatics II)

You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome?

Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Biology Meets Programming: Bioinformatics for Beginners

Are you interested in learning how to program (in Python) within a scientific setting?

This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gently-paced introduction...

Keywords: life-sciences, computer-science, health-informatics, software-development

Genomic Data Science and Clustering (Bioinformatics V)

How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Comparing Genes, Proteins, and Genomes (Bioinformatics III)

Once we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different.

In the first half of the course, we will compare two short biological sequences, such as genes (i.e., short sequences of DNA) or proteins. We...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Molecular Evolution (Bioinformatics IV)

In the previous course in the Specialization, we learned how to compare genes, proteins, and genomes. One way we can use these methods is in order to construct a "Tree of Life" showing how a large collection of related organisms have evolved over time.

In the first half of the course, we will...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Introduction to Biopython

This is a module from the "Python for Biologists" course. The module presents an introduction to Biopython. It shows how to deal with sequences and sequence records, how to download records from NCBI databases, how to run Blast and how to parse XML Blast outputs.

Keywords: Bioinformatics, Biopython, Programming, Python, Python biologists

Python @ TGAC - Python for Life Scientists: Managing biological data with Python

Python is an object-oriented programming language that is ideal for biological data analysis. The course will start with very basic language concepts and instructions and will cover all the main language aspects, including variables, types, modules, functions, exceptions, control of flux, input,...

Keywords: Biopython, Python, Python biologists

Using R with Python

This is a module from the "Python for Biologists" course. It describes the Python module interfacing the R package for statistics. The module shows how to calculate mean, standard deviation, z-score and p-value of a set of numbers, and how to generate plots. Input files for the scripts presented...

Keywords: Programming, Python, Python biologists

Searching data using Python

This is a module from the "Python for Biologists" course. It describes how to use Python dictionary and set data structures to search your data. In particular, how to use a dictionary to represent the genetic code table and use it to translate a nucleotide sequence into a protein sequence, and...

Keywords: Programming, Python, Python biologists

Pattern Matching

This is a module from the "Python for Biologists" course. It teaches how to do pattern matching in Python, i.e. how to find a substring (or a set of substrings) in a string. To this aim, it introduces the regular expression syntax, and the tools needed to search regular expressions in biological...

Keywords: Pattern matching, Programming, Python, Python biologists

Writing functions in Python programming

This is a module from the "Python for Biologists" course. It deals with functions and how to write and use them. It also introduces namespaces and the tuple data structure. The module contains several exercises and suggested solutions. The text of exercises is also provided in a separate file. 

Scientific topics: Bioinformatics

Keywords: Programming, Python, Python biologists

Python Programs

This is a module from the "Python for Biologists" course. It deals with Python programs, how to write and run them, and how to provide input and generate output. The module also contains exercises and suggested solutions. 

Keywords: Programming, Python, Python biologists

An Introduction to Unix, Perl and Python

This  course provides an introduction to Unix, Perl and Python. In addition to lecture material (in the form of slides), there are exercises, answers to the exercises and pointers to addition resources.

Keywords: Perl, Python, Unix

Parsing data records using Python programming

This is a module from the "Python for Biologists" course. One typical problem in bioinformatics is parsing data files. This module explains how to parse FASTA files and GenBank records. It also introduces the if/elif/else construct to make choice in programming and the list  data structure. The...

Keywords: Bioinformatics, Programming, Python, Python biologists, Record parsing