Python Resources for Bioinformatics
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Python Resources for Bioinformatics
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vcfpy - python package for reading and writing VCF files.

vcfpy - Python 3 library with good support for both reading and writing VCF
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Python in Viral Bioinformatics Research

Trevor Bell https://2016.za.pycon.org/talks/25/ The field of bioinformatics -- using computer technology to store, process and analyze biological data -- i
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Democratic databases: science on GitHub

Democratic databases: science on GitHub | Python Resources for Bioinformatics | Scoop.it
Scientists are turning to a software–development site to share data and code.
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A Focus on Allostery, Programming for Bioscientists, Ten Simple Rules for Effective Stats Practice: the PLOS Comp Biol June Issue | PLOS Biologue

A Focus on Allostery, Programming for Bioscientists, Ten Simple Rules for Effective Stats Practice: the PLOS Comp Biol June Issue | PLOS Biologue | Python Resources for Bioinformatics | Scoop.it
Check out our highlights from the PLOS Computational Biology June 2016 Issue:   History of allostery. Image Credit: Liu, Nussinov. Allostery Focus Feature This Focus Feature, led by Jin Liu and Ruth Nussinov, turns the spotlight on allostery.
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thombashi/pytablewriter

pytablewriter is a python library to write a table in various formats: CSV / HTML / JavaScript / JSON / Markdown / Excel / Pandas / Python / reStructuredText

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vinta/awesome-python

awesome-python - A curated list of awesome Python frameworks, libraries, software and resources

awesome-python - A curated list of awesome Python frameworks, libraries, software and resources

 
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Virus trading cards

Virus trading cards | Python Resources for Bioinformatics | Scoop.it
Deadly but beautiful - The trading cards you probably don’t want to collect.

Deadly but beautiful - The trading cards you probably don’t want to collect.

 
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Bioconda — Bioconda documentation

Bioconda is a distribution of bioinformatics software realized as a channel for the versatile Conda package manager. 
Bioconda is a distribution of bioinformatics software realized as a channel for the versatile Conda package manager. Key features of Conda are a command line client for simple installation and dependency handling in the spirit of conda install mypackage, very easy package creation, a mechanism for creating isolated environments that allows different package versions to coexist.
Bioconda is a distribution of bioinformatics software realized as a channel for the versatile Conda package manager. 
Key features of Conda are a command line client for simple installation and dependency handling in the spirit of conda install mypackage, very easy package creation, a mechanism for creating isolated environments that allows different package versions to coexist.
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Easy Python Time Series Plots with Matplotlib

Easy Python Time Series Plots with Matplotlib | Python Resources for Bioinformatics | Scoop.it
A detailed guide to plotting data over time in Matplotlib, from exploration to presentation-ready graphics
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Powered By Jupyter: A Survey of the Project Ecosystem - IBM Emerging Technologies Blog

Powered By Jupyter: A Survey of the Project Ecosystem - IBM Emerging Technologies Blog | Python Resources for Bioinformatics | Scoop.it
Share: Project Jupyter has a large and growing developer community, one that both includes and extends beyond the Jupyter org on GitHub. In this post, we’ll take a walk through the wonderful things people are building based on Jupyter technology today. The Jupyter Notebook is the most well-known application in the Jupyter ecosystem. It is a web-based environment for combining …

Share: Project Jupyter has a large and growing developer community, one that both includes and extends beyond the Jupyter org on GitHub. In this post, we’ll take a walk through the wonderful things people are building based on Jupyter technology today. The Jupyter Notebook is the most well-known application in the Jupyter ecosystem. It is a web-based environment for combining …

 
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tqdm - A fast, extensible progress bar for Python

tqdm - A fast, extensible progress bar for Python
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socketubs/requirements

Python requirements for Humans ™
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Python requirements for Humans
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A review of bioinformatic pipeline frameworks

High-throughput bioinformatic analyses increasingly rely on pipeline frameworks to process sequence and metadata. Modern implementations of these frameworks differ on three key dimensions: using an implicit or explicit syntax, using a configuration, convention or class-based design paradigm and offering a command line or workbench interface. Here I sur- vey and compare the design philosophies of several current pipeline frameworks. I provide practical recommendations based on analysis requirements and the user base.
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Why scientists must share their research code

Why scientists must share their research code | Python Resources for Bioinformatics | Scoop.it
'Reproducibility editor' Victoria Stodden explains the growing movement to make code and data available to others.
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Python for Bioinformatics for learning Python | Bioinformatics Training

Python for Bioinformatics for learning Python | Bioinformatics Training | Python Resources for Bioinformatics | Scoop.it
Martin Schweitzer https://2016.pycon-au.org/schedule/89/view_talk In this talk I will explain why Python is an excellent language for learning abou | Bioinformatics Training
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4 Best Python Programming Language Courses of All Times!

4 Best Python Programming Language Courses of All Times! | Python Resources for Bioinformatics | Scoop.it
If you’ve been working for a while or are still searching for an ideal job, it would be best to develop yourself a bit more before you apply further. In order to emerge successful and break through these highly competitive doors, it is essential to learn a few programming skills that will certainly help you…
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An Introduction to Programming for Bioscientists: A Python-Based Primer

An Introduction to Programming for Bioscientists: A Python-Based Primer | Python Resources for Bioinformatics | Scoop.it
Author Summary Contemporary biology has largely become computational biology, whether it involves applying physical principles to simulate the motion of each atom in a piece of DNA, or using machine learning algorithms to integrate and mine “omics” data across whole cells (or even entire ecosystems). The ability to design algorithms and program computers, even at a novice level, may be the most indispensable skill that a modern researcher can cultivate. As with human languages, computational fluency is developed actively, not passively. This self-contained text, structured as a hybrid primer/tutorial, introduces any biologist—from college freshman to established senior scientist—to basic computing principles (control-flow, recursion, regular expressions, etc.) and the practicalities of programming and software design. We use the Python language because it now pervades virtually every domain of the biosciences, from sequence-based bioinformatics and molecular evolution to phylogenomics, systems biology, structural biology, and beyond. To introduce both coding (in general) and Python (in particular), we guide the reader via concrete examples and exercises. We also supply, as Supplemental Chapters, a few thousand lines of heavily-annotated, freely distributed source code for personal study.
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Junnplus/awesome-python-books

awesome-python-books - :books: Directory of Python books

awesome-python-books - :books: Directory of Python books

 
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metric-learn: Metric Learning in Python — metric-learn 0.1.0 documentation

Distance metrics are widely used in the machine learning literature. Traditionally, practicioners would choose a standard distance metric (Euclidean, City-Block, Cosine, etc.) using a priori knowledge of the domain. Distance metric learning (or simply, metric learning) is the sub-field of machine learning dedicated to automatically constructing optimal distance metrics. This package contains efficient Python implementations of several popular metric learning algorithms.
Distance metrics are widely used in the machine learning literature. Traditionally, practicioners would choose a standard distance metric (Euclidean, City-Block, Cosine, etc.) using a priori knowledge of the domain. Distance metric learning (or simply, metric learning) is the sub-field of machine learning dedicated to automatically constructing optimal distance metrics. This package contains efficient Python implementations of several popular metric learning algorithms.
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ResidentMario/missingno

ResidentMario/missingno | Python Resources for Bioinformatics | Scoop.it
missingno - Missing data visualization module for Python.

missingno - Missing data visualization module for Python.

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chapmanb/bcbio-nextgen

bcbio-nextgen - Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis

bcbio-nextgen - Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis

 
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Python Virtual Environments - a primer - Real Python

Python Virtual Environments - a primer - Real Python | Python Resources for Bioinformatics | Scoop.it
This article details how to use a Python virtual environment to manage your Python projects.

This article details how to use a Python virtual environment to manage your Python projects.

 
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esfahanpayamak72's curator insight, April 3, 7:51 AM

http://www.esfahanpayamak.com/Property

سامانه پیام کوتاه اصفهان

 

خب کار دشواری نیست شما می تونید با داشتن پنل ارسال اس ام اس یا سامانه ارسال اس ام اس که به نام های دیگه ای همچون پنل پیامک ، پیامک تبلیغاتی و.. معروف است که نرم افزاری تحت وب می باشد و پنل ارسال اس ام اس اصفهان دارای قابلیت ها و امکانات و ماژول های فراوانی برای ارسال پیامک هست اقدام به ارسال پیامک کوتاه (SmS)  به صورت تکی یا انبوه کنید