Search Results for "xlrd module python"
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Showing 6 open source projects for "xlrd module python"
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BioC
We describe a simple XML format to share text documents and annotation
A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are... -
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PRADA
PRADA : Pipeline for RNA-Sequencing Data Analysis
Massively parallel sequencing of cDNA reverse transcribed from RNA (RNASeq) provides an accurate estimate of the quantity and composition of mRNAs. To characterize the transcriptome through the analysis of RNA-seq data, we developed PRADA. PRADA focuses on the processing and analysis of gene expression estimates, supervised and unsupervised gene fusion identification, and supervised intragenic deletion identification. PRADA currently supports 7 modules to process and identify... -
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AMBIENT
Find active modules in metabolic networks using high-throughput data
...If you wish to use the version used in the paper it is v0.6.3, however I recommend using the latest version which works in the same way but with additional options and has stability and performance improvements. Thanks for your interest! AMBIENT (Active Modules for Bipartite Networks) is a Python module that uses simulated annealing to find areas of a metabolic network (modules) that have some consistent characteristic. AMBIENT does not require predefined pathways and gives highly specific predictions of affected areas of metabolism. For example, scores for reactions based on transcriptional data of their annotated encoding genes can be used in the network and modules of coordinated expression changes can be found. ... -
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ABE is a small, fast and convenient program for visualizing and modeling experimental bioassay data. The data can be modeled using either polynomials or a more specific four-parameter model based upon the standard, sigmoidal dose-response curve.
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