scikit-bio.org scikit-bio.org

scikit-bio.org

scikit-bio

Scikit-bio is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics. Scikit-bio is currently in beta. We are very actively developing it, and backward-incompatible interface changes can and will arise. For more details, including what we mean by. To install the latest release of scikit-bio:. Equivalently, you can use the. Package manager available in Anaconda. You can verify your installation by running the scikit-bio unit tests:.

http://www.scikit-bio.org/

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Scikit-bio is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics. Scikit-bio is currently in beta. We are very actively developing it, and backward-incompatible interface changes can and will arise. For more details, including what we mean by. To install the latest release of scikit-bio:. Equivalently, you can use the. Package manager available in Anaconda. You can verify your installation by running the scikit-bio unit tests:.
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scikit-bio | scikit-bio.org Reviews

https://scikit-bio.org

Scikit-bio is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics. Scikit-bio is currently in beta. We are very actively developing it, and backward-incompatible interface changes can and will arise. For more details, including what we mean by. To install the latest release of scikit-bio:. Equivalently, you can use the. Package manager available in Anaconda. You can verify your installation by running the scikit-bio unit tests:.

INTERNAL PAGES

scikit-bio.org scikit-bio.org
1

scikit-bio — scikit-bio 0.1.1 documentation

http://scikit-bio.org/docs/0.1.1/index.html

Sequence collections and alignments (. Dissimilarity and distance matrices (. Performing Striped Smith Waterman Alignments (. Format biological sequences (. Alpha diversity measures (. Parse biological sequences (. Supporting Python 2 and Python 3. Adding a new module to skbio. Is a library for working with biological data in Python. scikit-bio is open source, BSD-licensed software that is currently under active development. Sequence collections and alignments (. Dissimilarity and distance matrices (.

2

scikit-bio — scikit-bio 0.4.0 documentation

http://scikit-bio.org/docs/0.4.0/index.html

Alignments and Sequence collections (. Supporting Python 2 and Python 3. Adding a new module to skbio. Is a library for working with biological data in Python. scikit-bio is open source, BSD-licensed software that is currently under active development. Alignments and Sequence collections (. The user documentation contains high-level information for users of scikit-bio. The developer documentation contains information for how to contribute to scikit-bio. Supporting Python 2 and Python 3.

3

scikit-bio — scikit-bio 0.2.3 documentation

http://scikit-bio.org/docs/0.2.3/index.html

Sequence collections and alignments (. Format biological sequences (. Parse biological sequences (. Supporting Python 2 and Python 3. Adding a new module to skbio. Is a library for working with biological data in Python. scikit-bio is open source, BSD-licensed software that is currently under active development. Sequence collections and alignments (. Format biological sequences (. Parse biological sequences (. The developer documentation contains information for how to contribute to scikit-bio.

4

scikit-bio — scikit-bio 0.1.4 documentation

http://scikit-bio.org/docs/0.1.4/index.html

Sequence collections and alignments (. Dissimilarity and distance matrices (. Format biological sequences (. Alpha diversity measures (. Beta diversity measures (. Miscellaneous statistics utilities (. Parse biological sequences (. Supporting Python 2 and Python 3. Adding a new module to skbio. Is a library for working with biological data in Python. scikit-bio is open source, BSD-licensed software that is currently under active development. Sequence collections and alignments (. Beta diversity measures (.

5

scikit-bio — scikit-bio 0.5.0 documentation

http://scikit-bio.org/docs/latest/index.html

Adding a new module to skbio. Is a library for working with biological data in Python 3. scikit-bio is open source, BSD-licensed software that is currently under active development. The user documentation contains high-level information for users of scikit-bio. The developer documentation contains information for how to contribute to scikit-bio. Adding a new module to skbio.

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qiime.org qiime.org

Illumina Overview Tutorial (an IPython Notebook): open reference OTU picking and core diversity analyses — Homepage

http://qiime.org/tutorials/illumina_overview_tutorial.html

News and Announcements ». Illumina Overview Tutorial (an IPython Notebook): open reference OTU picking and core diversity analyses. This tutorial is provided as an IPython Notebook. See the Illumina Overview Tutorial IPython Notebook. OTU picking strategies in QIIME. 454 Overview Tutorial: de novo OTU picking and diversity analyses using 454 data. Enter search terms or a module, class or function name.

qiime.org qiime.org

QIIME Tutorials — Homepage

http://qiime.org/tutorials/index.html

News and Announcements ». The QIIME tutorials illustrate how to use various features of QIIME. We recommend that all users begin with either the QIIME Illumina Overview Tutorial. Or the QIIME 454 Overview Tutorial. These tutorials take the user through a full analysis of sequencing data. After you’ve begun analyzing your own data, you’ll want to move on to the special-purpose tutorials as needed. If you’re interested in contributing. OTU picking strategies in QIIME. Analysis of 18S data. Creating Distanc...

qiime.org qiime.org

QIIME Virtual Box — Homepage

http://qiime.org/install/virtual_box.html

News and Announcements ». As a consequence of QIIME’s. Architecture, QIIME has a lot of dependencies and can (but doesn’t have to) be very challenging to install. The QIIME Virtual Box gets around the difficulty of installation by providing a functioning QIIME full install inside an Ubuntu Linux virtual machine. You can use the QIIME Virtual Box on Mac OS X, Windows, or Linux. It is strongly recommended that your system have 8 gigabytes or more of memory to use the QIIME Virtual Box. Select “Use ex...

microbe.net microbe.net

Teaching bioinformatics using IPython Notebooks – microBEnet: the microbiology of the Built Environment network.

http://microbe.net/2014/05/01/teaching-bioinformatics-using-ipython-notebooks

Skip to main content. Media Coverage of microBEnet. Meetings and Conference Reports. Microbiology blog of the day series. Microbial Ecology in the Built Environment. Ribosomal RNA (rRNA), the details. RRNA in Evolutionary Studies and Environmental Sampling. Sloan Program on the Microbiology of the Built Environment. Full List of Sloan Grants. Microbiology of the Built Environment Network (microBEnet). Biology and the Built Environment (BioBE) Center. IM-BOL: The Indoor Mycota Barcode of Life. May 1, 2014.

terragenome.org terragenome.org

TerraGenome » Workshops

http://www.terragenome.org/workshops

Dates: 29-30 September 2016. Location: Noble Foundation, Ardmore, OK. There are 10 available slots for QIIME training opportunity. A limited number of student / postdoc travel awards are available for workshop participants. Accommodation and food will be provided for all the participants by the workshop organizers. Please email us if you are interested in attending the workshop at pkankanala@noble.org. By September 10th 2016. Applicant must be a student or postdoctoral researcher. Dates: 4-5 November 2016.

ilovesymposia.com ilovesymposia.com

Python | I Love Symposia!

https://ilovesymposia.com/tag/python

Science and Tech for the Small Fry. The cost of a Python function call. December 10, 2015. I’ve read in various places that the Python function call overhead is very high. As I was parroting this “fact” to Ed Schofield. Recently, he asked me what the cost of a function actually was. I had no idea. This prompted us to do a few quick benchmarks. The short version is that it takes about 150ns to call a function in Python (on my laptop). This doesn’t sound like a lot, but it means that you can make. Lose two...

ilovesymposia.com ilovesymposia.com

Go to SciPy 2015 | I Love Symposia!

https://ilovesymposia.com/2015/03/23/go-to-scipy-2015

Science and Tech for the Small Fry. Go to SciPy 2015. March 23, 2015. Is my favourite conference. My goal with this post is to convince someone to go who hasn’t had that chance yet. Most scientists go to conferences in their own field: neuroscientists go to the monstrous Society for Neuroscience (SfN); Bioinformaticians go to RECOMB, ISMB, or PSB; and so on. People go to these to keep up with the latest advances in their field, and often, to do a bit of networking. SciPy is a different kind of conference.

ilovesymposia.com ilovesymposia.com

conference | I Love Symposia!

https://ilovesymposia.com/category/conference

Science and Tech for the Small Fry. October 9, 2015. The videos from EuroSciPy 2015 are up. This marks a good time to write up my thoughts on the conference. That the yearly SciPy conference is stunningly useful. This year I couldn’t make it to Austin, but I did attend EuroSciPy. The European version of the same conference, in Cambridge, UK. It was spectacular. The talk of the conference, for me, goes to Robin Wilson for recipy. I also enjoyed Nicolas Rougier’s talk. A new journal dedicated to replicated...

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Programma 101: Il libro. Informativa estesa sull’uso dei Cookie. Attenti a chi avete tra gli amici su Facebook. Mar 08, 2017. Oggi vi parlerò di un metodo di indagine molto semplice ma potente, perché non sfrutta l’insicurezza del profilo della persona su cui state indagando, ma quella dei suoi amici. Vi spiego la situazione ideale: Avete una persona di cui non sapete. Telegram Desktop introduce i temi. Gen 13, 2017. Falla in Telegram sulle foto. Gen 03, 2017. Dic 03, 2016. Nov 26, 2016. Nov 18, 2016.

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scikit-bio.org scikit-bio.org

scikit-bio

Scikit-bio is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics. Scikit-bio is currently in beta. We are very actively developing it, and backward-incompatible interface changes can and will arise. For more details, including what we mean by. To install the latest release of scikit-bio:. Equivalently, you can use the. Package manager available in Anaconda. You can verify your installation by running the scikit-bio unit tests:.

scikit-criteria.org scikit-criteria.org

Indices and tables — Scikit-Criteria 0.0.1 documentation

Scikit-criteria is a collection of Multiple-criteria decision analysis ( MCDA. Methods integrated into scientific python stack. Built on NumPy, SciPy, and matplotlib. Open source, commercially usable - BSD license. Provided by Read the Docs. On Read the Docs. Free document hosting provided by Read the Docs.

scikit-image.org scikit-image.org

scikit-image: Image processing in Python — scikit-image

Image processing in Python. Is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. Filtering an image with. For more examples, please visit our gallery. Or any NumPy array! If you find this project useful, please cite:. PeerJ 2:e453 (2014) http:/ dx.doi.org/10.7717/peerj.453. Version 0.11.0 04/03/2015. Version 0.10.0 27/05/2014. Belgium, August 2012.

scikit-learn.org scikit-learn.org

scikit-learn: machine learning in Python — scikit-learn 0.16.1 documentation

Scikit-learn 0.16 (Stable). Machine Learning in Python. Simple and efficient tools for data mining and data analysis. Accessible to everybody, and reusable in various contexts. Built on NumPy, SciPy, and matplotlib. Open source, commercially usable - BSD license. An introduction to machine learning with scikit-learn. Machine learning: the problem setting. Loading an example dataset. A tutorial on statistical-learning for scientific data processing. Nearest neighbor and the curse of dimensionality. Evalua...

scikit-multilearn.github.io scikit-multilearn.github.io

scikit-multilearn | Multi-label classification package for python

Multi-label classification package for python. Download 0.0.1. A native Python implementation of a variety of multi-label classification algorithms. The list includes:. Label cooccurence-based partitioning clasifiers. Hierarchy of Multi-label Classifiers [in-progress]. Classifier chains and others [in-progress]. For reference purposes and integration needs a Meka wrapper class is implemented. Thus providing access to all methods available in meka, mulan and weka - the reference standard of the field.

scikit-nano.org scikit-nano.org

scikit-nano

The scikit-nano Project is an open-source Python toolkit for nanoscience. Current Version: 0.3.21. You can install the latest version of scikit-nano using pip. Or by downloading the source code and installing it manually - see the Source. Tab above for more details. You can install the latest version of scikit-nano using pip. Or by downloading the source code and installing it manually - see the Source. Tab above for more details. You can install the latest version of scikit-nano using pip. Check out the...