Search Results for "analysis" - Page 35
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Showing 1228 open source projects for "analysis"
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HPeak
A HMM-based algorithm for defining enriched regions from ChIP-seq data
HPeak is a hidden Markov model-based approach that can accurately pinpoint regions to where significantly more sequence reads map. Testing on real data shows that these regions are indeed highly enriched by the right protein binding sites. Command (single-end): perl /compbio/software/HPeak3/HPeak.pl -sp HUMAN/MOUSE -format BED -t TREATMENT.inp -c CONTROL.inp -n OUTPUTPREFIX -fmin 100 -fmax 300 -r 36 -ann -wig -seq -interfiles Command (pair-end): perl /compbio/software/HPeak3/HPeak.pl... -
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GeneticM
Grow beat reactive digital art with ProjectM
GeneticM takes ProjectM preset files and allows you to breed them together to evolve and grow new visualizations with unique traits and visual effects. -
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Analyzes programs (and projects) written in Cobol and generates information (HTML) for its easy reading, understanding and analysis.
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IMPORTANT: The project moved over to github! You can find it at: https://github.com/exhuma/python-cluster
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Provide a reference implementation of Moving Taylor Bayesian Regression, a method for nonparametric multi-dimensional function estimation with correlated errors from finite samples, as a Python package based on SciPy
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Lograph
Log text into graph on python and javascript.
Graphize logs on the web browser. Fast javascript implementation needed with large monitor use. -
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GIIAF Microscopy Library
The GIIAF Microscopy Library, that uses customised OMERO software
This project incorporates a suite of tools that aim to allow researchers within Griffith's Imaging and Image Analysis Facility (GIIAF) to efficiently and effectively provide secure, centralised, web-accessible data storage, management and manipulation. The open-source Java-based OMERO software was customised to provide most of the features of this project. -
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A C++ library for the computation of bifurcation diagrams: it provides tools for the integration of systems of ODEs that depend on parameters. A Python interface is included.
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ox_black_rhino
black_rhino is a multi-agent simulator for financial network analysis
This is the outdated code of black_rhino. The new version is maintained and hosted on github. Please see https://github.com/cogeorg/black_rhino -
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PYC Dissasembler
Disassemble python byte compiled file for python 2.x
PYC Dissasembler disassemble python byte compiled files (.pyc) into a series of opcodes. It work for every version of python 2 (that use cpython) but must be run with a good interpreter. Ex: you can only disassemble python 2.7 pyc files with a python 2.7 interpreter. -
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SpiKeDeteKt
An automatic spike detection program to be used with new KlustaKwik
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... -
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vigenere.py
this simple program implements the Vigenere cipher in python
For details of this cipher see; http://en.wikipedia.org/wiki/Vigenere_cipher This cipher can be broken by frequency analysis, this is a toy project, and should not be used in situations where security is important. -
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A web-based interface for the Hadoop MapReduce framework that simplifies the process of writing and running MapReduce jobs. Aimed at introducing parallelism concepts in introductory computer science courses.
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eSpoor
Determine a User's Internet Footprint
A Project undertaken as part of my MSc to determine a User's Internet Footprint. The project uses the fiwalk.py package to extract relevant artifacts from a disk image in the DFXML format, performs an analysis and saves the results in a form for human readers. -
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CSST
Cascade and Sharing Survival Trees, an ensemble for survival analysis
Cascading and Sharing Survival Trees (CSST) is a tree-based enseble that allows to efficiently analize survival data. It is a strightforward extension of the CS4 method for lifetime collections of data. The CSST software comes along with its companion the CSST Prediction tool, to use the ensemble prediction in everyday life. Please, refer to the user's manual for further information. -
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colonyzer image analysis software
Image analysis estimating cell density in arrayed microbial cultures
Image analysis software for quantification of cell density in microbial cultures (e.g. S. cerevisiae) growing on solid agar plates. Specialises in detection of extremely low cell densities. Forms part of the Quantitative Fitness Analysis (QFA) workflow: http://research.ncl.ac.uk/qfa/ Suitable for high-throughput, genome-wide analysis of culture libraries when combined with the following qfa R package: http://qfa.r-forge.r-project.org/ This is the version presented, used and demonstrated in the following manuscripts: Lawless et al. 2010 http://dx.doi.org/10.1186/1471-2105-11-287 Addinall et al. 2011 http://dx.doi.org/10.1371/journal.pgen.1001362 Chang et al. 2011 http://dx.doi.org/10.1534/g3.111.000216 Banks et al. 2012 http://dx.doi.org/10.3791/4018 Development has been moved to github, where Colonyzer has undergone several recent improvements, particuarly making installation easier and analysis faster: https://github.com/CnrLwlss/Colonyzer -
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GUI for DEDA
GUI for DEmography Data Analysis
<This project has been completely rewrote and transformed into a new one: https://sourceforge.net/projects/deday/. 2013/06/26> The graphic user interface for DEDA (DEmography Data Analysis), a scientific software package fitting survivalship data to a number of distributions using maximum likelihood (ML) method. Currently, Weibull (2p), Gompertz and Gompertz-Makeham are supported. IMPORTANT NOTICE: Only the GUI is provided here. In order to perform the analysis, one also need the DEDA computation core program. ... -
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GUANO
GUANO - Graphical User interface for performing ANalysis Of variance
...Features: - Capable of high order factorial designs (> 2 factors) - Within and mixed analyses of variance provide corrections for violations of sphericity (Huynh-Feldt, Greenhouse-Geisser, Box) - A variety of data transformations can be applied (log10, reciprocal, arcsine, square-root, and Windsor) - Generalized eta-squared measures of effect size - Post-hoc power analysis (should match G*Power) - Outputs include tables of estimated marginal means - Up to 4-way interaction plots with errorbars (png, svg) - Confidence intervals account for within-subject variability (where applicable; Loftus and Masson, 1994) - Non-proprietary HTML output files - Non-proprietary codebase Gotchas: - Assumes balanced designs -
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Python Script to process a wave file and transform to movement (key frames) on Blender 2.5. Input: sound file (.wav) Output: Key frames direct into the selected object Work to meshes and bones (location, scale or rotation in any axis)
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aim is to provide support for monitoring system behaviour through dynamic analysis, and for analysing and modeling this data for a better understanding of system behaviour and for test automation
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ROOTlib
C++ lib, that provides access to multiple ROOT routines (root.cern.ch)
This C++ lib is used and created to provide easy methods based on ROOT (a CERN data analysis framework). It was developed for use in practical courses but is not limited to. In addition it is ported step by step into Python. -
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Plotmeister is a data exploration tool. It parses your ASCII data and generates a simple (text-based) table format. You can modify this table and eventually create nice looking figures.
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Arachne
Exploration of a Hierarchical+Functional Approach To Data Organization
This is dedicated to development of a small class for organizing data in both a traditional parent<->child hierarchy and by the functions used to generate child data nodes from parent data. The core of the project is in the class definitions contained within arachne.py, a demonstration of how this method of arranging data can be used to solve a relatively interesting problem may be found in test.py
