<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/35800?offset=200 https://bioinformaticsonline.com/bookmarks/view/36360/dendropy-a-python-library-for-phylogenetic-computing Mon, 23 Apr 2018 05:49:50 -0500 https://bioinformaticsonline.com/bookmarks/view/36360/dendropy-a-python-library-for-phylogenetic-computing <![CDATA[DendroPy: a Python library for phylogenetic computing]]> DendroPy is a Python library for phylogenetic computing. It provides classes and functions for the simulation, processing, and manipulation of phylogenetic trees and character matrices, and supports the reading and writing of phylogenetic data in a range of formats, such as NEXUS, NEWICK, NeXML, Phylip, FASTA, etc. Application scripts for performing some useful phylogenetic operations, such as data conversion and tree posterior distribution summarization, are also distributed and installed as part of the libary. DendroPy can thus function as a stand-alone library for phylogenetics, a component of more complex multi-library phyloinformatic pipelines, or as a scripting “glue” that assembles and drives such pipelines.

The primary home page for DendroPy, with detailed tutorials and documentation, is at:

DendroPy is also hosted in the official Python repository:

Requirements and Installation

DendroPy 4.x runs under Python 3 (all versions > 3.1) and Python 2 (Python 2.7 only).

You can install DendroPy by running:

 

More information is available here:

Address of the bookmark: https://pypi.org/project/DendroPy/

]]> Seema Singh https://bioinformaticsonline.com/bookmarks/view/11609/bioinformatician%E2%80%99s-pocket-reference Sun, 08 Jun 2014 09:56:58 -0500 https://bioinformaticsonline.com/bookmarks/view/11609/bioinformatician%E2%80%99s-pocket-reference <![CDATA[Bioinformatician’s Pocket Reference !!]]> It is amusing how brain of bioinformaticians work! Learning a new programming language for days feels so much of fun that making 5 minute discussion with neighbours (unless under special circumstances!) in our own mother-tongue. Today every bioinformatician keeps more than few languages and core IT toolkits on their plate. It has become mandatory to be able to mould different code snippets to build our own custom workflows, and thus keeping syntax at our fingertips has become essential.Although Google is best way to get syntax problem solved, it is not a bad idea to keep reference sheets is our smartphones or stick out some printed sheets on the back of your door, in the old fashion way!!

Address of the bookmark: http://infoplatter.wordpress.com/2014/04/06/bioinformaticians-pocket-reference/

]]> RAJESH DETROJA https://bioinformaticsonline.com/blog/view/37627/setting-python-version-as-default-on-linux Tue, 04 Sep 2018 10:15:47 -0500 https://bioinformaticsonline.com/blog/view/37627/setting-python-version-as-default-on-linux <![CDATA[Setting python version as default on Linux]]> If you have a later version than 2.6 you'll need to set 2.6 as the default Python. Later versions would be 2.7 and 3.1; see what you have by typing

python -V

at the terminal. For purposes of this example we'll assume you have 3.1 installed. You'll next need to execute the following commands:

 

sudo apt-get install python2.6 idle-python2.6
sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.1 1
sudo update-alternatives --install /usr/bin/python python /usr/bin/python2.6 10
sudo update-alternatives --config python

This last command will allow you to choose which version of python to use by default. If you have done everything above correctly, python2.6 should already be set as the default. If it is not, choose it to be the default. From now on, running python should start version 2.6.

Undoing These Changes

In some cases (e.g., installing or updating certain packages), you'll get an error message if you've run the commands above. To update these packages, you'll have to temporarily undo these changes. Here's how to do that:

sudo update-alternatives --remove-all python
sudo ln -s python3.1 /usr/bin/python

Once you're done updating these packages, execute the commands at the top to set python2.6 as the default again.

]]> Rahul Nayak https://bioinformaticsonline.com/videolist/watch/12288/genomic-medicine-bruce-korf-2014 Tue, 24 Jun 2014 07:58:44 -0500 https://bioinformaticsonline.com/videolist/watch/12288/genomic-medicine-bruce-korf-2014 <![CDATA[Genomic Medicine - Bruce Korf (2014)]]> May 21, 2014 - Current Topics in Genome Analysis 2014 A lecture series covering contemporary areas in genomics and bioinformatics. More: http://www.genome.gov/COURSE2014]]> https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data Sun, 02 Feb 2020 08:14:19 -0600 https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data <![CDATA[Nucleus: Python and C++ code for reading and writing genomics data.]]> Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF. In addition, Nucleus enables painless integration with the TensorFlow machine learning framework, as anywhere a genomics file is consumed or produced, a TensorFlow tfrecords file may be used instead.

Address of the bookmark: https://github.com/google/nucleus

]]> Jit https://bioinformaticsonline.com/opportunity/view/12594/faculty-positions-at-central-university-of-punjab Mon, 07 Jul 2014 23:33:33 -0500 <![CDATA[Faculty Positions at Central University of Punjab]]> Faculty Positions: Rolling/Open Advertisement Advt.No: T-10 (2013)

Pay Scale: Pay Band Rs.15600-39100 with AGP of Rs.6,000/-

Essential Qualifications for Professors, Associate Professors, and Assistant Professors: As per “UGC REGULATIONS ON MINIMUM QUALIFICATIONS FOR APPOINTMENT OF TEACHERS AND OTHER ACADEMIC STAFF IN UNIVERSITIES AND COLLEGES AND MEASURES FOR THE MAINTENANCE OF STANDARDS IN HIGHER EDUCATION 2010“ and the 2nd Amendments to the regulation issued in June 2013.

For details: http://www.ugc.ac.in/oldpdf/regulations/revised_finalugcregulationfinal10.pdf http://www.ugc.ac.in/pdfnews/8539300_English.pdf and University rules.

Procedure to apply:

Application forms along with API form complete in all respect along with necessary documents and application fee of Rs. 500/-. (Rs. 250/- for Scheduled Caste/Scheduled Tribe/Person with disabilities) should be sent to:

Registrar, Central University of Punjab, City Campus, Mansa Road, Bathinda-151001

For more info visit: http://www.centralunipunjab.com/Teaching/Final%20Details-t10-2013.pdf, http://www.centralunipunjab.com/Teaching/Advertisement-t10-2013.jpg

Last Apply Date: 31 Dec 2014

]]> 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/12787/integrative-genomics-viewer-igv-tutorial Sat, 12 Jul 2014 15:16:23 -0500 https://bioinformaticsonline.com/bookmarks/view/12787/integrative-genomics-viewer-igv-tutorial <![CDATA[Integrative Genomics Viewer (IGV) tutorial]]> The Integrative Genomics Viewer (IGV) from the Broad Center allows you to view several types of data files involved in any NGS analysis that employs a reference genome, including how reads from a dataset are mapped, gene annotations, and predicted genetic variants.

http://www.broadinstitute.org/igv/

Address of the bookmark: https://wikis.utexas.edu/display/bioiteam/Integrative+Genomics+Viewer+%28IGV%29+tutorial

]]> Neel https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data Thu, 30 May 2019 04:06:13 -0500 https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data <![CDATA[snakepipes: A toolkit based on snakemake and python for analysis of NGS data]]> snakePipes are flexible and powerful workflows built using snakemake that simplify the analysis of NGS data.

  • DNA-mapping*
  • ChIP-seq*
  • RNA-seq*
  • ATAC-seq*
  • scRNA-seq
  • Hi-C
  • Whole Genome Bisulfite Seq/WGBS

(*Also available in "allele-specific" mode)

snakePipes can be installed via conda :

'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'.

Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online.

Address of the bookmark: https://github.com/maxplanck-ie/snakepipes

]]> Jit https://bioinformaticsonline.com/pages/view/44284/tools-for-geospatial-data-analysis Wed, 22 Mar 2023 02:10:28 -0500 https://bioinformaticsonline.com/pages/view/44284/tools-for-geospatial-data-analysis <![CDATA[Tools for Geospatial data analysis !]]>

Geospatial data is becoming increasingly important in many fields, including urban planning, environmental science, public health, and more. These tools can help you work with data from a variety of sources, including satellite imagery, GPS data, and other forms of spatial data. They can help you visualize data, perform complex analysis, and even create maps and other visualizations.

The list includes some of the most popular and widely used geospatial tools available in Python. These tools can help you work with data from a variety of sources and in a variety of formats. Some of the tools are focused on visualization, such as Cartopy, Folium, and Contextily, which allow you to create interactive maps and other visualizations. Other tools are more focused on data manipulation and analysis, such as Fiona, GeoPandas, and Rasterio, which allow you to manipulate and analyze spatial data in a variety of ways.

The list also includes some tools for working with specific types of geospatial data. For example, the H3 library is designed specifically for working with hexagonal grids, while PySAL is focused on spatial econometrics and spatial analysis. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.

In summary, this list is an excellent resource for anyone working with geospatial data in Python. It contains a wide range of tools for working with different types of data, and can help you visualize data, perform complex analysis, and create maps and other visualizations. If you're looking to enhance your skills in geospatial analysis, this list is definitely worth checking out.

These tools are:

These tools offer a wide range of capabilities for working with geospatial data, from visualizing and manipulating data to performing complex analysis and modeling. Whether you are a data scientist, GIS specialist, or geospatial enthusiast, these tools are sure to enhance your work and help you achieve your goals.

]]> BioStar