<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/44179?offset=0 https://bioinformaticsonline.com/pages/view/36605/hello-python-world Mon, 14 May 2018 16:41:01 -0500 https://bioinformaticsonline.com/pages/view/36605/hello-python-world <![CDATA[Hello Python World !]]> As I mentioned earlier, I will keep on posting one Python script per day to introduce you to Python programming. Whether you are an experienced programmer or not, this tutorial is intended for everyone who wishes to learn the Python programming language.

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

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/10182/biocodesbioscripts Tue, 22 Apr 2014 20:53:33 -0500 https://bioinformaticsonline.com/bookmarks/view/10182/biocodesbioscripts <![CDATA[BioCodes/BioScripts]]> Over the years most bioinformatics people amass a collection of small utility scripts which make their lives easier. Too often they are kept either in private repositories or as part of a public collection to which noone else can contribute. Biocode is a curated repository of general-use utility scripts.

Algorithms scripts @ https://github.com/jschendel/bioinformatics-algorithms-coursera

Address of the bookmark: https://github.com/jorvis/biocode

]]> Jit https://bioinformaticsonline.com/pages/view/35805/python-learning-resources-for-bioinformatics-and-computational-biologist Fri, 02 Mar 2018 06:54:15 -0600 https://bioinformaticsonline.com/pages/view/35805/python-learning-resources-for-bioinformatics-and-computational-biologist <![CDATA[Python learning resources for bioinformatics and computational biologist !]]> Python is a general-purpose language, which means it can be used to build just about anything, which will be made easy with the right tools/libraries.

Professionally, Python is great for backend web development, data analysis, artificial intelligence, and scientific computing. Many developers have also used Python to build productivity tools, games, and desktop apps, so there are plenty of resources to help you learn how to do those as well.

For pros and cons visit http://www.bestprogramminglanguagefor.me/why-learn-python and http://bioinformaticsonline.com/discussion/view/459/python-vs-perl

More resources at https://github.com/CodementorIO/Python-Learning-Resources

Following are the list of useful python programming resources:

]]> Jit https://bioinformaticsonline.com/bookmarks/view/33398/tiny-python36-notebook Sat, 03 Jun 2017 03:16:28 -0500 https://bioinformaticsonline.com/bookmarks/view/33398/tiny-python36-notebook <![CDATA[Tiny Python3.6 Notebook]]> This is not so much an instructional manual, but rather notes, tables, and examples for Python syntax. It was created by the author as an additional resource during training, meant to be distributed as a physical notebook. Participants (who favor the physical characteristics of dead tree material) could add their own notes, thoughts, and have a valuable reference of curated examples.

Address of the bookmark: https://github.com/mattharrison/Tiny-Python-3.6-Notebook/blob/master/python.rst

]]> Neel https://bioinformaticsonline.com/pages/view/36603/learning-python-programming-a-bioinformatician-perspective Mon, 14 May 2018 16:33:03 -0500 https://bioinformaticsonline.com/pages/view/36603/learning-python-programming-a-bioinformatician-perspective <![CDATA[Learning Python Programming - a bioinformatician perspective !]]> Python Programming is a general purpose programming language that is open source, flexible, powerful and easy to use. One of the most important features of python is its rich set of utilities and libraries for data processing and analytics tasks. In the current era of big biological data, python and biopython is getting more popularity due to its easy-to-use features which supports big data processing.

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.

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn Mon, 29 Feb 2016 17:39:24 -0600 https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn <![CDATA[scikit-learn]]> Machine Learning in Python

Simple and efficient tools for data mining and data analysis
Accessible to everybody, and reusable in various contexts
Built on NumPy, SciPy, and matplotlib
Open source, commercially usable - BSD license

More at http://scikit-learn.org/stable/index.html

 

Address of the bookmark: http://scikit-learn.org/stable/auto_examples/index.html

]]> Jitendra Prajapati https://bioinformaticsonline.com/blog/view/44633/learn-python-with-example Tue, 06 Aug 2024 23:51:51 -0500 https://bioinformaticsonline.com/blog/view/44633/learn-python-with-example <![CDATA[Learn python with example]]>

There are over 21 unique Python project walkthroughs in this content that range from beginner to advanced. See below for the timestamps for these projects:

00:00:00 | How To Navigate These Projects
---
00:01:46 | #1 - Quiz Game (Easy)
Code: https://github.com/techwithtim/5-Python-Projects-For-Beginners/blob/main/quiz_game.py 
---
00:22:00 | #2 - Number Guessing Game (Easy)
Code: https://github.com/techwithtim/5-Python-Projects-For-Beginners/blob/main/number_guesser.py 
---
00:39:49 | #3 - Rock, Paper, Scissors (Easy)
Code: https://github.com/techwithtim/5-Python-Projects-For-Beginners/blob/main/rock_paper_scissors.py 
---
00:54:40 | #4 - Choose Your Own Adventure Game (Easy)
Code: https://github.com/techwithtim/5-Python-Projects-For-Beginners/blob/main/choose_your_own_adventure.py 
---
01:06:47 | #5 - Password Manager (Medium)
Code: https://github.com/techwithtim/5-Python-Projects-For-Beginners/ 
Fernet Cryptography Documentation: https://cryptography.io/en/latest/fernet/ 
---
01:37:37 | #6 - PIG (Medium)
Code: https://github.com/techwithtim/3-Mini-Python-Projects/blob/main/project1.py 
---
01:59:07 | #7 - Madlibs Generator (Medium)
Code: https://github.com/techwithtim/3-Mini-Python-Projects/blob/main/project2.py 
---
02:15:04 | #8 - Timed Math Challenge (Medium)
Code: https://github.com/techwithtim/3-Mini-Python-Projects/blob/main/project3.py 
---
02:28:02 | #9 - Slot Machine (Medium)
Code: https://github.com/techwithtim/Python-Slot-Machine 
---
03:20:43 | #10 - Turtle Racing (Medium)
Code: https://github.com/techwithtim/Turtle-Racing-V2 
Turtle Docs: https://docs.python.org/3/library/turtle.html 
---
04:13:09 | #11 - WPM Typing Test (Medium)
Code: https://github.com/techwithtim/WPM_Typing_Test 
Curses Docs: https://docs.python.org/3/howto/curses.html 
05:09:43 | #12 - Alarm Clock (Easy)
Python Project Idea Blog: https://hackr.io/blog/python-projects 
Sound Effects: https://www.fesliyanstudios.com/royalty-free-sound-effects-download/alarm-203 
---
05:22:07 | #13 - Password Generator (Easy)
Python Project Idea Blog: https://hackr.io/blog/python-projects 
---
05:39:16 | #14 - Shortest Path Finder (Advanced)
Code: https://github.com/techwithtim/3-Mini-Python-Projects-For-Intermediates/blob/main/path-finder.py 
---
06:14:53 | #15 - NBA Stats & Current Scores (Medium)
Code: https://github.com/techwithtim/3-Mini-Python-Projects-For-Intermediates/blob/main/nba-scores.py 
---
06:38:22 | #16 - Currency Converter (Medium)
Code: https://github.com/techwithtim/3-Mini-Python-Projects-For-Intermediates/blob/main/currency-converter.py 
API: https://free.currencyconverterapi.com/
---
06:58:51 | #17 - YouTube Video Downloader (Medium)
Code:  https://github.com/techwithtim/Python-Beginner-Automation-Projects/blob/main/youtube.py 
---
07:09:50 | #18 - Automated File Backup (Medium)
Code: https://github.com/techwithtim/Python-Beginner-Automation-Projects/blob/main/backup.py 
---
07:21:18 | #19 - Mastermind/4 Color Match (Advanced)
---
07:48:20 | #20 - Aim Trainer (Advanced)
Code: https://github.com/techwithtim/Python-Aim-Trainer 
---
08:39:20 | #21 - Advanced Python Scripting (Advanced)
Code: https://github.com/techwithtim/Python-Scripting-Project 

]]> BioStar https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics Wed, 20 Aug 2014 22:09:21 -0500 https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics <![CDATA[Pimp your brain: Bioinformatics]]> Jan Lisec from the Max Planck Institute of Molecular Plant Physiology explains, in this "pimp your brain" episode, what bioinformatics is and why bioinformatics is so important and indispensable for biological research. In the video serial "Pimp your brain" scientists from the Max Planck Institute of Molecular Plant Physiology describe their research. More videos from the 'Pimp your brain' serial are available on www.youtube.com/playlist?list=PL-l9VItC9Gn2Ur2Xj6PTOAkjLUlVPbIOO More videos are available on www.mpimp-golm.mpg.de]]> https://bioinformaticsonline.com/bookmarks/view/32076/ngs-teaching-material Wed, 05 Apr 2017 04:29:06 -0500 https://bioinformaticsonline.com/bookmarks/view/32076/ngs-teaching-material <![CDATA[NGS teaching material]]> High throughput sequencing (HTS) technologies are being applied to a wide range of important topics in biology. However, the analyses of non-model organisms, for which little previous sequence information is available, pose specific problems. This course addresses the specific strengths and weaknesses of alternative HTS technologies, the computational resources needed for HTS, and how to analyze non-model species using HTS. The course consists of a practical training module, HTS bioinformatics training, and lecturing/seminars of HTS approaches specifically targeting non-model organisms.

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

]]> Jit https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco Sat, 06 Feb 2021 13:31:24 -0600 https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco <![CDATA[Bioinformatics in Africa: Part 4 - Morocco]]> Bioinformatics, in the UFR in Artificial Intelligence and Bioinformatics, deals with the management, the analysis, the modelling and the visualization of biological databases. Since the size of the databases is often exponential, the traditional algorithms are not very effective when seeking for a good computational solution.

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

]]> BioStar