<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/43552?offset=40 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/bookmarks/view/34041/r-tuorial Mon, 31 Jul 2017 08:41:40 -0500 https://bioinformaticsonline.com/bookmarks/view/34041/r-tuorial <![CDATA[R tuorial]]> R learning resources

https://flowingdata.com/

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

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/42672/introduction-to-bioinformatics-and-computational-biology Mon, 25 Jan 2021 01:32:30 -0600 https://bioinformaticsonline.com/bookmarks/view/42672/introduction-to-bioinformatics-and-computational-biology <![CDATA[Introduction to Bioinformatics and Computational Biology]]> This is the course material for STAT115/215 BIO/BST282 at Harvard University.

Xiaole Shirley Liu (lead instructor)
Joshua Starmer
Martin Hemberg
Ting Wang
Feng Yue

Ming Tang
Yang Liu
Jack Kang
Scarlett Ge
Jiazhen Rong
Phillip Nicol
Maartin De Vries

We thank many colleagues in the community, who helped Dr. Liu in prepare the STAT115/215 BIO/BST282 course over the years. 

Address of the bookmark: https://liulab-dfci.github.io/bioinfo-combio/

]]> Jit https://bioinformaticsonline.com/pages/view/42814/bioinformatics-in-africa-part6-sudan Sat, 06 Feb 2021 21:20:59 -0600 https://bioinformaticsonline.com/pages/view/42814/bioinformatics-in-africa-part6-sudan <![CDATA[Bioinformatics in Africa: Part6 - Sudan]]> Commission for Biotechnology & Genetic Engineering ­ Khartoum: The Commission for Biotechnology and Genetic Engineering was established in 9/2/1993 as  research unit. In addition to research activities it acts as focal point for the International Center for  Biotechnology and Genetic Engineering. The commission conducts researches in order to play a part in solving economical, environmental,  health and nutritional problems using modern research techniques with an emphasis on the applied  researches in these areas. The laboratories were well furnished with the essential equipments and the catalyst infrastructure to  facilitate emergence of a successful for research. The Commission equipped with a computer center  and information to serve as informatics and Digital library.

Research Interest and Activities: 1. Plant Genetic Transformations
2. Molecular Population Genetics 3. Detection of human and Animals diseases 4. Breast Cancer­specific protein marker 5. Phytochemical 6. Genomic map 7. Bioremediation 8. Tissue Culture.

Web site and links: www.geocity.cbge.com

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/43431/code-golf Wed, 06 Oct 2021 04:17:29 -0500 https://bioinformaticsonline.com/bookmarks/view/43431/code-golf <![CDATA[Code Golf]]> Code Golf is a game designed to let you show off your code-fu by solving problems in the least number of characters.

Since this is your first time here, I suggest starting with something simple like Fizz Buzz.

Address of the bookmark: https://code.golf/

]]> Abhi https://bioinformaticsonline.com/bookmarks/view/43681/a-guide-to-machine-learning-for-biologists Tue, 28 Dec 2021 01:43:25 -0600 https://bioinformaticsonline.com/bookmarks/view/43681/a-guide-to-machine-learning-for-biologists <![CDATA[A guide to machine learning for biologists]]> Because of the increasing size and inherent complexity of biological data, there has been an increase in the application of machine learning in biology to create useful and predictive models of the underlying biological processes. All machine learning techniques fit models to data; nevertheless, the specific methods are highly variable and can appear baffling at first glance. In this Review, we hope to give readers a moderate introduction to a few fundamental machine learning techniques, including the most recently created and frequently used deep neural network techniques. We illustrate how different algorithms may be adapted to specific types of biological data, as well as some best practises and points to consider when embarking on machine learning studies. There is also discussion of several upcoming directions in machine learning methodology.

Address of the bookmark: https://www.nature.com/articles/s41580-021-00407-0

]]> Abhi 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/bookmarks/view/44648/modern-statistics-with-r Thu, 22 Aug 2024 04:44:06 -0500 https://bioinformaticsonline.com/bookmarks/view/44648/modern-statistics-with-r <![CDATA[Modern Statistics with R]]> This is the online version of the second edition of Modern Statistics with R. It is free to use, and always will be. Printed copies are available from CRC Press.

Live online courses on statistics with R based on this book, led by the author, are offered regularly; see this page for more information and dates.

The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you:

  • Data wrangling - importing, formatting, reshaping, merging, and filtering data in R.
  • Exploratory data analysis - using visualisations and multivariate techniques to explore datasets.
  • Statistical inference - modern methods for testing hypotheses and computing confidence intervals.
  • Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting.
  • Simulation - using simulation techniques for sample size computations and evaluations of statistical methods.
  • Ethics in statistics - ethical issues and good statistical practice.
  • R programming - writing code that is fast, readable, and (hopefully!) free from bugs.

The book includes plenty of examples and more than 200 exercises with worked solutions. The datasets used for the examples and the exercises can be downloaded here.

Address of the bookmark: https://www.modernstatisticswithr.com/

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping Wed, 29 Jan 2020 06:29:55 -0600 https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping <![CDATA[Understanding your reads and mapping !]]> One of the best tutorial for beginners ...

https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html

Address of the bookmark: https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html

]]> Neel https://bioinformaticsonline.com/bookmarks/view/43273/understanding-kmer Wed, 18 Aug 2021 04:27:51 -0500 https://bioinformaticsonline.com/bookmarks/view/43273/understanding-kmer <![CDATA[Understanding kmer !]]> What is a k-mer anyway? A k-mer is just a sequence of k characters in a string (or nucleotides in a DNA sequence). Now, it is important to remember that to get all k-mers from a sequence you need to get the first k characters, then move just a single character for the start of the next k-mer and so on. Effectively, this will create sequences that overlap in k-1 positions.

Address of the bookmark: https://bioinfologics.github.io/post/2018/09/17/k-mer-counting-part-i-introduction/

]]> BioStar