<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/44279?offset=20 https://bioinformaticsonline.com/news/view/22073/bcil-bioinformatics-bitp-application Fri, 17 Apr 2015 04:34:56 -0500 https://bioinformaticsonline.com/news/view/22073/bcil-bioinformatics-bitp-application <![CDATA[BCIL Bioinformatics BITP Application !!]]> BCIL Bioinformatics BITP Application Form 2015 logoGrab latest Information! Biotech Consortium India Limited has announced a notification for offering admission in Biotech Industrial Training Program. The organization has invited online application from 7th April 2015 BCIL Admission 2015. BCIL has conducted an entrance exam which is scheduled on 20th June 2015. Candidates those who are looking for this program just go for it and don’t miss this opportunity.

To apply for Biotech Industrial Training Programme the candidates should have 50% marks in B.Tech/BE/M.Tech Degree in Bio technology, bio process technology and other related disciplines form any recognized institution. The organization has decided application fee of Rs.500/- for all candidates and that should be paid through demand draft. Applicants who satisfy the organization requirement, they can take their steps forward.

Candidates should submit the online application before 10th May 2015. After registering the online application you need to take the hard copy of it and send through post. Print out of this application should be reached before 15th May 2015. All the latest updates like selection process, exam syllabus and other related information are updated soon at the main URL of the department and aspirants should keep in touch with this site. Further details of BCIL Bioinformatics BITP Application Form 2015 are explained below.

Organization: Biotech Consortium India Limited

Website URL: www.bcil.nic.in

Location: New Delhi

Course Name: Biotech Industrial Training Program

Exam Name: BCIL Entrance Exam

Educational Details: Applicants should complete their B.Tech/M.Tech/BE programs in Neuro- Science, Agricultural, Bio technology, bio process technology and other related disciplines having 50% aggregate from any authorized university.

Application Fee: For all candidates application fee is Rs.500/- and it will be paid through Demand Draft drawn in favour of BCIL, New Delhi.

How to Apply: Candidates who are willing to apply for this program they can apply through online mode. Then send the hard copy of registered application form to through post.

Important Dates

Opening Date of Submission Online Application Form: 7h April 2015

Closing Date of Submission of Online Application Form: 10th May 2015

Last Date of Receipt of Application Form: 15th May 2015

Exam Date: 20th June 2015

More at http://bcil.nic.in/default.htm

]]> Pranjali Yadav https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning Fri, 01 Jul 2016 12:57:12 -0500 https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning <![CDATA[Machine Learning !!!]]> In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.

Keep scrolling. Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.

Address of the bookmark: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/

]]> Gudiya Pal https://bioinformaticsonline.com/news/view/30364/bioinformatics-contest-2017 Fri, 23 Dec 2016 14:03:37 -0600 https://bioinformaticsonline.com/news/view/30364/bioinformatics-contest-2017 <![CDATA[Bioinformatics Contest 2017!]]> Bioinformatics Contest 2017! Rosalind is co-organizer.
Compete with thousands of people worldwide on bioinformatics problem solving.
Everything is online. Qualification round starts on January 23, 2017. Final is on Feb 18.

You will need to solve bioinformatics problems using programming. The goal is to correctly solve as many problems as possible within 24 hours. Some of them will be approximation problems and will have partial grades. All rounds will be held online, submissions will be auto-graded in real time.

Check more at http://contest.bioinf.me/

Good luck!

]]> Neel https://bioinformaticsonline.com/bookmarks/view/30538/gkno Tue, 17 Jan 2017 03:35:34 -0600 https://bioinformaticsonline.com/bookmarks/view/30538/gkno <![CDATA[GKNO]]> gkno opens the world of complex bioinformatic analysis to people of all level of computational expertise. This site contains documentation, tutorials and information on all the tools that comprise gkno.

More at http://gkno.me/

Address of the bookmark: http://gkno.me/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/35798/an-introduction-to-applied-bioinformatics Fri, 02 Mar 2018 04:26:38 -0600 https://bioinformaticsonline.com/bookmarks/view/35798/an-introduction-to-applied-bioinformatics <![CDATA[An Introduction to Applied Bioinformatics]]> IAB is primarily being developed by Greg Caporaso(GitHub/Twitter: @gregcaporaso) in the Caporaso Lab at Northern Arizona University. You can find information on the courses I teach on my teaching website and information on my research and lab on my lab website.

 

Address of the bookmark: http://readiab.org/

]]> Jit https://bioinformaticsonline.com/pages/view/42810/bioinformatics-in-africa-part3-mali Sat, 06 Feb 2021 13:28:44 -0600 https://bioinformaticsonline.com/pages/view/42810/bioinformatics-in-africa-part3-mali <![CDATA[Bioinformatics in Africa: Part3 - Mali]]> International Center for Excellence in Research (ICER):

The ICER is a research center composed of the following three programs: 1. The Malaria Research and Training Center ­ Parasitology Group,  2. The Malaria Research and Training Center ­ Entomology Group  3. The SEREFO Group.

The first two programs develop biomedical researches in malaria, Filariasis and Leishmaniasis. The  third program develops biomedical researches in tuberculosis and HIV.

Bioinformatics was introduced recently to the ICER and is constantly growing. The ICER has one  team, headed by Sidy SOUMARE, which supports the three programmes in all their needs in  informatics and bioinformatics. This team can beneficiate from some computational facilities (4  blast servers, 15 other servers and around 200 terminals), but the ICER staff needs some training in  order to be able to administrate these facilities.

Research Interest and Activities: The following are the present areas of research interest: 1. Functional genomics 2. Analysis of microarray data 3. Interaction between the vector and the parasite.

]]> BioStar https://bioinformaticsonline.com/opportunity/view/43292/bioinformatics-scientist-production-bioinformatics-south-san-francisco-ca Thu, 19 Aug 2021 08:45:24 -0500 <![CDATA[Bioinformatics Scientist, Production Bioinformatics @ South San Francisco, CA]]> wist is looking for a Bioinformatics Scientist to join our Production Bioinformatics Team. You will work alongside research scientists, software engineers and data scientists to further deliver on our mission to expand access to best-in-class synthetic biology and next-generation sequencing applications. You will be developing and engineering tools to better evaluate and build hardened, production quality pipelines, optimize data quality, and automate lab and bioinformatics processes. Our ideal candidate is an organized problem solver with a background in developing and building novel production-quality bioinformatics tools and packages. Equally excellent communication skills and a proven ability to work independently are required.

More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us

]]> 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/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/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/

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