Code in almost all popular languages using Coding Ground. Edit, compile, execute and share your projects, 100% cloud.

http://www.tutorialspoint.com/codingground.htm

Address of the bookmark: http://www.tutorialspoint.com/codingground.htm

In this tutorial series article, I will explore features and packages of python which are widely used in the big data, NGS, and bioinformatics. I will also walk through a real biological example which shows NGS data processing with the help of python packages and programming.

Python has a couple of points to recommend it to biologists and scientists specifically:

• It's widely used in the scientific community
• It has a couple of very well designed libraries for doing complex scientific computing (although we won't encounter them in this book)
• It lend itself well to being integrated with other, existing tools
• It has features which make it easy to manipulate strings of characters (for example, strings of DNA bases and protein amino acid residues, which we as biologists are particularly fond of)

In general, following are some of the important features of python which makes it a perfect fit for rapid application development.

• Python is interpreted language so the program does not need to be compiled. Interpreter parses the program code and generates the output.
• Python is dynamically typed, so the variables types are defined automatically.
• Python is strongly typed. So the developers need to cast the type manually.
• Less code and more use makes it more acceptable.
• Python is portable, extendable and scalable.

There are two major Python versions, Python 2 and Python 3. Python 2 and 3 are quite different. This tutorial uses Python 3, because it more semantically correct and supports newer features.

I will post tutorial on daily basis on this page. Check the sub-pages on right side.

The tutorial is divided in three main parts:

• In the Sequence part, you will see how to look efficiently for a particular protein sequence, how to blast it against the database of your choice to find homologues, how to perform a multiple alignment of the homologues you've selected and how to edit this alignment.
• The Structure part is about molecular visualization, homology modeling and structural domain prediction.
• In the Function part, you will be introduced to you 3 useful servers to investigate the function of a protein. i.e. finding interactors, co-expressed genes, see a phylogenetic profile, easily access papers citing your gene etc ...

During all the three parts, we will use the S. cerevisiae VPS36 protein as an example.

Address of the bookmark: http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html

Address of the bookmark: http://marinetics.org/teaching/hts/Assembly.html

Python is a very simple language, and has a very straightforward syntax. The simplest directive in Python is the "print" directive - it simply prints out a line (and also includes a newline).

Create a file Hello.py

print("Hello, Python World !.")

Run

python3 Hello.py

To take care of this issue, many ways are opened to the researchers to improve the quality of the algorithms:

1. Usage of new information processing methods like artificial neuronal networks, genetic algorithms, etc. 2. Usage of Data mining  to explore biochemical databases,
3. Usage of Machine learning on the biological examples to solve, for example, the problem of classification in Bioinformatics.

UFR offers in addition a doctoral training in Computer Science and Bioinformatics.

Doctoral module which includes: a Diplôme des Etudes Supérieures Approfondies (DESA)  of two years; and a doctorate studies program with a national Ph.D. certification. Three specializations constitute the teaching trunk of the ENSAT: Computer engineering, Telecom  engineering, and electronic systems engineering.

Research Interest and Activities:

The following are the present areas of research interest:

1. Machine Learning and Profile Gene Expression of Cancer
2. Predicting Protein structure
3. Hidden Markov Models (HMMs) and multiple alignments
4. Transformational Grammar for sequence modelling
5. Physical Mapping: STSs
6. Evolutionary Computation applied to Genomic and Proteomic
7. Predicate Logic and Protein Structure

Web site and links:

http://www.ensat.ac.ma/udiab http://www.pasteur.fr/pasteur/international/annonce_coursBioinfoannonce06_casa.pdf

https://github.com/remicnrd/ml_cheatsheet

Visual AI / ML

https://setosa.io/ev/

Simple and efficient tools for predictive data analysis

https://scikit-learn.org/stable/

In this tutorial we’ll be going through the steps of setting up an Apache server.

What you’ll learn

• How to set up Apache
• Some basic Apache configuration

Address of the bookmark: https://ubuntu.com/tutorials/install-and-configure-apache#3-creating-your-own-website

Each chapter focuses on a single scientific problem and contains a core text accompanied by code alongs and autograded exercises.

You can meet Phillip Compeau in our intro video. Phillip has taught programming at Carnegie Mellon University for years and is a serial online education founder. He is thrilled to bring you this course.

Address of the bookmark: https://programmingforlovers.com/