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bioc
HiCExperiment:Bioconductor class for interacting with Hi-C files in R
R generic interface to Hi-C contact matrices in `.(m)cool`, `.hic` or HiC-Pro derived formats, as well as other Hi-C processed file formats. Contact matrices can be partially parsed using a random access method, allowing a memory-efficient representation of Hi-C data in R. The `HiCExperiment` class stores the Hi-C contacts parsed from local contact matrix files. `HiCExperiment` instances can be further investigated in R using the `HiContacts` analysis package.
Maintained by Jacques Serizay. Last updated 15 days ago.
9 stars 7.02 score 48 scripts 2 dependentsbioc
bioassayR:Cross-target analysis of small molecule bioactivity
bioassayR is a computational tool that enables simultaneous analysis of thousands of bioassay experiments performed over a diverse set of compounds and biological targets. Unique features include support for large-scale cross-target analyses of both public and custom bioassays, generation of high throughput screening fingerprints (HTSFPs), and an optional preloaded database that provides access to a substantial portion of publicly available bioactivity data.
Maintained by Thomas Girke. Last updated 5 months ago.
immunooncologymicrotitreplateassaycellbasedassaysvisualizationinfrastructuredataimportbioinformaticsproteomicsmetabolomics
5 stars 6.70 score 46 scriptsbioc
ternarynet:Ternary Network Estimation
Gene-regulatory network (GRN) modeling seeks to infer dependencies between genes and thereby provide insight into the regulatory relationships that exist within a cell. This package provides a computational Bayesian approach to GRN estimation from perturbation experiments using a ternary network model, in which gene expression is discretized into one of 3 states: up, unchanged, or down). The ternarynet package includes a parallel implementation of the replica exchange Monte Carlo algorithm for fitting network models, using MPI.
Maintained by McCall N. Matthew. Last updated 5 months ago.
softwarecellbiologygraphandnetworknetworkbayesiancpp
3.30 score 3 scripts