<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/40754?offset=90 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 https://bioinformaticsonline.com/blog/view/43008/list-of-useful-machine-ai-learning-resources Tue, 30 Mar 2021 08:56:06 -0500 https://bioinformaticsonline.com/blog/view/43008/list-of-useful-machine-ai-learning-resources <![CDATA[List of useful machine / ai learning resources !]]> ML cheatsheet !

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/

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/43563/apache-server-setting Fri, 29 Oct 2021 04:29:51 -0500 https://bioinformaticsonline.com/bookmarks/view/43563/apache-server-setting <![CDATA[Apache server setting !]]> Apache is an open source web server that’s available for Linux servers free of charge.

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

]]> Abhi https://bioinformaticsonline.com/bookmarks/view/44543/seeing-theory-and-learn Tue, 04 Jun 2024 00:31:54 -0500 https://bioinformaticsonline.com/bookmarks/view/44543/seeing-theory-and-learn <![CDATA[Seeing Theory and Learn]]> Seeing Theory was created by Daniel Kunin while an undergraduate at Brown University. The goal of this website is to make statistics more accessible through interactive visualizations (designed using Mike Bostock’s JavaScript library D3.js).

Address of the bookmark: https://seeing-theory.brown.edu/

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/44620/diy-transcriptomics Wed, 31 Jul 2024 01:19:26 -0500 https://bioinformaticsonline.com/bookmarks/view/44620/diy-transcriptomics <![CDATA[DIY Transcriptomics]]> A semester-long course covering best practices for the analysis of high-throughput sequencing data from gene expression (RNA-seq) studies, with a primary focus on empowering students to be independent in the use of lightweight and open-source software using the R programming language and the Bioconductor suite of packages. This course follows a hybrid format in which online lectures are paired with in-person labs where students participate in hands-on, live coding exercises using real ‘omic datasets. The course is focused on datasets and topics central to infectious disease research, immunology, and One-Health, but the concepts and approaches covered are applicable to any genomic study.

https://diytranscriptomics.com

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

]]> Abhi 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/43243/interactive-bioinformatics-resources Thu, 12 Aug 2021 00:09:00 -0500 https://bioinformaticsonline.com/bookmarks/view/43243/interactive-bioinformatics-resources <![CDATA[Interactive Bioinformatics Resources !]]> Learn how to use bioinformatics tools right from your browser.
Everything runs in a sandbox, so you can experiment all you want.

More at sandbox.bio

Address of the bookmark: http://sandbox.bio

]]> Jit https://bioinformaticsonline.com/bookmarks/view/43631/pangolin-tutorial Fri, 10 Dec 2021 05:58:59 -0600 https://bioinformaticsonline.com/bookmarks/view/43631/pangolin-tutorial <![CDATA[Pangolin tutorial !]]> This is a tutorial for using the Pangolin Web Application. For information on using the command line tool, please visit the command line tool usage page.

https://cov-lineages.org/resources/pangolin/tutorial.html

Address of the bookmark: https://cov-lineages.org/resources/pangolin/tutorial.html

]]> Abhi https://bioinformaticsonline.com/bookmarks/view/44601/free-resources-to-learn-statistics Sat, 06 Jul 2024 10:30:50 -0500 https://bioinformaticsonline.com/bookmarks/view/44601/free-resources-to-learn-statistics <![CDATA[Free resources to learn statistics]]> Welcome to the course notes for STAT 414: Introduction to Probability Theory. These notes are designed and developed by Penn State's Department of Statistics and offered as open educational resources. These notes are free to use under Creative Commons license CC BY-NC 4.0.

 

A free online version of the second edition of the book based on Stat 110, Introduction to Probability by Joe Blitzstein and Jessica Hwang, is now available at http://probabilitybook.net

Print copies are available via CRC Press, Amazon, and elsewhere. 

Stat110x is also available as an edX course. Free signup at https://www.edx.org/course/introduction-to-probability-0

The edX course focuses on animations, interactive features, readings, and problem-solving, and is complementary to the Stat 110 lecture videos on YouTube, which are available at https://goo.gl/i7njSb

The Stat110x animations are available within the course and at https://goo.gl/g7pqTo

https://projects.iq.harvard.edu/stat110/home 

Address of the bookmark: https://online.stat.psu.edu/stat414/

]]> BioStar https://bioinformaticsonline.com/view/2044 Mon, 12 Aug 2013 12:19:29 -0500 https://bioinformaticsonline.com/view/2044 <![CDATA[Does anyone have Nanopore latest updates?]]> There was a lot of buzz about Oxford Nanopore Technologies® is developing the GridION™ system and miniaturised MinION™ device. These are a new generation of electronic molecular analysis system for use in scientific research, personalised medicine, crop science, security/defence and more. The platform technology uses nanopores to analyse single molecules including DNA/RNA and proteins. With a broad patent portfolio, the Oxford Nanopore pipeline includes biological nanopores and solid-state nanopores.

Is this available, or still under trial mode? 

https://www.nanoporetech.com/

https://www.nanoporetech.com/technology/the-minion-device-a-miniaturised-sensing-system/the-minion-device-a-miniaturised-sensing-system

]]> Poonam Mahapatra