<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/29638?offset=620 https://bioinformaticsonline.com/bookmarks/view/23498/algorithms-for-dna-sequencing-course-offered-each-month Sun, 26 Jul 2015 01:57:02 -0500 https://bioinformaticsonline.com/bookmarks/view/23498/algorithms-for-dna-sequencing-course-offered-each-month <![CDATA[Algorithms for DNA Sequencing (course offered each month)]]> "We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets."

Source : https://www.coursera.org/course/ads1

 

Address of the bookmark: https://www.coursera.org/course/ads1

]]> Rahul Agarwal https://bioinformaticsonline.com/videolist/watch/2699/translational-bioinformatics-transforming-300-billion-points-of-data Tue, 20 Aug 2013 19:03:47 -0500 https://bioinformaticsonline.com/videolist/watch/2699/translational-bioinformatics-transforming-300-billion-points-of-data <![CDATA[Translational Bioinformatics: Transforming 300 Billion Points of Data]]> Translational Bioinformatics: Transforming 300 Billion Points of Data into Diagnostics, Therapeutics, and New Insights into Disease Air date: Wednesday, June 20, 2012, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Description: There is an urgent need to translate genome-era discoveries into clinical utility, but the difficulties in making bench-to-bedside translations haven't been well described. The nascent field of translational bioinformatics may help. Dr. Butte's lab at Stanford University builds and applies tools that convert more than 300 billion points of molecular, clinical, and epidemiological data (measured by researchers and clinicians over the past decade) into diagnostics, therapeutics, and new insights into disease. Dr. Butte, a bioinformatician and pediatric endocrinologist, will highlight his lab's work on using publicly available molecular measurements to find new uses for drugs, discovering new treatable mechanisms of disease in type 2 diabetes, and evaluating patients presenting with whole genomes sequenced. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series Author: Atul Butte, M.D., Ph.D., Stanford University Runtime: 01:07:42 Permanent link: http://videocast.nih.gov/launch.asp?17321]]> https://bioinformaticsonline.com/opportunity/view/35422/postdoc-at-jaypee-institute-of-information-technology-jiit-noida-department-of-biotechnology Fri, 02 Feb 2018 11:13:25 -0600 <![CDATA[PostDoc at Jaypee Institute of Information Technology (JIIT), Noida Department of Biotechnology]]> Lab of Dr. Rawal is supported by generous grants to build advanced applications in emerging areas of cancer genomics, network sciences, vaccine development and epidemiology. The lab has dedicated high end Xeon servers, desktops, & laptops for research purpose. Currently, there are several researchers (JRFs, B. Techs, M. Tech and PhDs) working on several challenging bioinformatics projects. In addition, Dr. Rawal has collaborations with reputed national and international research teams.

Dr. Rawal and his US based collaborators have recently secured grant for development of vaccine against an infectious disease agent. For this project, applications are invited for the posts of Post Doctoral Fellow/Research Scientist (One Position) for the following time-bound sponsored projects as per the details given below:

PI: Dr. Kamal Rawal, Biotechnology Department, JIIT, Noida.

Essential Qualification(s) for Post Doctoral Fellow/ Research Scientist:

We are seeking an individual with expertise in analyzing literature information, text mining, network biology, data integration, and modeling. Competitive candidates would also have programming experience in scripting languages with perl, C, C++, and R programming. This position requires a PhD in Computational Biology, Bioinformatics, Biostatistics, Physics or related fields, and evidence of scientific productivity through publications in international journals. Motivation to gain an in-depth understanding of biological phenomena is required. Applications should include a current CV and names of at least three references. Application packages and inquiries regarding this position can be sent to Dr. Kamal Rawal (bioinfocvatgmaildotcom and kamaldotrawalatgmaildotcom). Screening of applications will commence immediately and the position will remain open until filled. Candidates having master’s degree with extensive experience in IT industry or research can also be considered for this post.

Salary: Rs 50000 per month.

Duration: 2 years or upto the project duration.

Number of position: 1

Candidate may also fill the following form:

https://docs.google.com/…/1FAIpQLSdZoZ21ZoNRStEeL5…/viewform

http://tinyurl.com/bioinfocv2017

]]> https://bioinformaticsonline.com/file/view/2741/bioinformatician-dreams Wed, 21 Aug 2013 10:50:45 -0500 https://bioinformaticsonline.com/file/view/2741/bioinformatician-dreams <![CDATA[Bioinformatician Dreams]]> Bioinformatician life is interconnected, they always dream for a powerful server, little more space on server as they are generating lots of data per run, dream to publish results in good impact journals, meetings reminders :) and research analysis off course!!! 

]]> Jitendra Narayan 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/videolist/watch/4072/bioinformatics Wed, 28 Aug 2013 19:16:33 -0500 https://bioinformaticsonline.com/videolist/watch/4072/bioinformatics <![CDATA[BIOINFORMATICS]]> This is a promo video for the brand new cross-boarder branch of study - BIOINFORMATICS. It´s a co-operation between Johannes Kepler University in Linz (Austria) and University of South Bohemia in České Budějovice (Czech Republic). Written, Edited and Directed by, DOP, VFX: Jan Míka Sound by: Mirek Šmilauer Narrator: Jack Bright Produced by: FILMOFON (http://www.filmofon.cz) Released: Nov 2012]]> 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/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates Thu, 16 May 2019 00:17:39 -0500 https://bioinformaticsonline.com/bookmarks/view/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates <![CDATA[multiPhATE: bioinformatics pipeline for functional annotation of phage isolates]]> multiple-genome Phage Annotation Toolkit and Evaluator (multiPhATE). multiPhATE is a throughput pipeline driver that invokes an annotation pipeline (PhATE) across a user-specified set of phage genomes. This tool incorporates a de novo phage gene-calling algorithm and assigns putative functions to gene calls using protein-, virus-, and phage-centric databases. 

 

Address of the bookmark: https://github.com/carolzhou/multiPhATE

]]> Abhimanyu Singh https://bioinformaticsonline.com/videolist/watch/4043/what-is-bioinformatics Wed, 28 Aug 2013 06:53:05 -0500 https://bioinformaticsonline.com/videolist/watch/4043/what-is-bioinformatics <![CDATA[What is Bioinformatics?]]> Illustration and Animation: Rachel Robinson Script: Tiffany Trent Voice-over: Kris Monger Sound: Glisten Carefully by Guennadi Malyshevski]]> https://bioinformaticsonline.com/videolist/watch/4093/ibm-research-computational-biology-center Thu, 29 Aug 2013 08:43:59 -0500 https://bioinformaticsonline.com/videolist/watch/4093/ibm-research-computational-biology-center <![CDATA[IBM Research Computational Biology Center]]> The IBM Computational Biology Center embraces activities at Yorktown Heights, with strong affiliations with activities at Almaden and other IBM Research Centers. Computational Biology (CompBio) including bioinformatics is the study of how computer systems can manage, analyze, and simulate the complex structures and processes inherent in living systems. CompBio Research at IBM spans pattern recognition in sequences, structures and processes, the studying of systems ranging from single protein molecules through to complex molecular interactions, and the data analysis, interpretation and reverse-engineering of complex disease-lifestyle-genomic interactions for fuller biological understanding. "CompBio" has a flavor of its own independant of its parents, biology and computer science. Nonetheless, CompBio is inherently a multi- disciplinary field with important applications in biology, chemical physics, materials science, agriculture, chemistry and ultimately nanotechnology.]]>