Search Results for "tkinter for python 2.7"

DataPrep v0.2 is a Tkinter-based GUI application/tool designed to assist users in data preprocessing, multicollinearity removal, and feature selection for a wide range of applications in Cheminformatics, Bioinformatics, Data Analysis, Feature Selection, Molecular Modeling, Machine Learning, and Quantitative-structure-property relationship (QSPR) studies. It includes functionality to load, process, and save datasets with support for different preprocessing & multicollinearity removal...

RELEASE NOTE: Get raxmlGUI 2.0 at the NEW PROJECT LOCATION: https://antonellilab.github.io/raxmlGUI/ raxmlGUI is a graphical user interface to RAxML, one of the most popular and widely used software for phylogenetic inference using maximum likelihood. A userfriendly graphical front-end for phylogenetic analyses using RAxML (Stamatakis, 2006). Please cite: Silvestro, Michalak (2012) - raxmlGUI: a graphical front-end for RAxML. Organisms Diversity and Evolution 12, 335-337. DOI:...

pySBOL is a SWIG-Python wrapper around libSBOL, a module for reading, writing, and constructing genetic designs according to the standardized specifications of the Synthetic Biology Open Language (SBOL). This page provides binary installers for Windows operating system for Python 2.7 and 3.6. For installation instructions, visit: https://pysbol2.readthedocs.io/en/latest/installation.html For full documentation, visit: https://pysbol2.readthedocs.io/en/latest/index.html

This project contains Python scripts usable for a dual transcript-discovery approach that improves the delimitation of gene features from RNA-seq data in the chicken model. Documentation: http://bio.biologists.org/content/biolopen/suppl/2018/01/17/bio.028498.DC1/BIO028498supp.pdf Citation: Orgeur M., Martens M., Börno S. T., Timmermann B., Duprez D. and Stricker S. (2018). A dual transcript-discovery approach to improve the delimitation of gene features from RNA-seq data in the...

...It can flexibly handle (1) discrete or continuous attributes, (2) missing data, (3) balanced or imbalanced datasets, and (4) binary or many classes. A complete users guide for ExSTraCS is included. Coded in Python 2.7.

This is an automatic spike detection program which takes account of probe geometry and produces a .mask file to be used with the new masked version of KlustaKwik. We recommend you use Python 2.6 or 2.7, e.g. a free academic version can be obtained from Entthought Python. The input files for SpiKeDeteKt are: .dat (raw data file) .probe (probe file, described below - user constructed) parameters.py (optional - otherwise it uses defaultparameters.py) SpiKeDeteKt outputs the following files: .fet.n (feature file) .mask.n (needed for using the new (masked) KlustaKwik) .clu.n (a trivial clue file where everything is put into a single cluster) .fmask.n (trial - float masks instead of binary, we are using this for testing masked KlustaKwik) .spk.n (spike file) .upsk.n (unfiltered spike waveform) .res.n (list of spike times) .xml (an xml file with all the parameters that can subsequently be used by neuroscope or klusters) .fil (highpass filtered data) .h5 (

Amplicon is a Python script for designing PCR primer sets. Amplicon is written in Python 2.3 and Tkinter 8.4. The current script was created for Windows and an executable is available. Future versions of the script should be able to run on Linux and Mac