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Cai Lab at Texas A&M (cailab-tamu)'s Projects

awesome-single-cell icon awesome-single-cell

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

hvg icon hvg

Supporting information for 'Single-cell expression variability implies cell function'

lcl_scrna-seq icon lcl_scrna-seq

scRNA-seq with LCLs - Three cell line samples sequenced: (1) GM12878, (2) GM18502, and (3) the 1:1 mixture of the two

lrsma icon lrsma

Low-rank Sparse Matrix Approximation for ChIP-Seq Consensus Peak Detection

matlab-gan icon matlab-gan

MATLAB implementations of Generative Adversarial Networks -- from GAN to Pixel2Pixel, CycleGAN

matlab_kauffman_nk_random_boolean_network icon matlab_kauffman_nk_random_boolean_network

The initial version of this is entirely thanks to the work of Christof Teuscher (http://www.teuscher.ch/christof/ext/), who created the original Matlab Random Boolean Network Toolbox (http://www.teuscher.ch/rbntoolbox/). The only changes made so far are to make the toolbox compatible with r2015a. Refer to the Toolbox site for additional overview and documentation information. This is posted with permission, under a BSD license, with permission from the original author. Additional updates (or notification of features that still don't work - I haven't tested all of them yet) are welcome.

quantumgrn icon quantumgrn

Quantum Gene Regulatory Networks with Application to Single-cell Data

scidata-lcl icon scidata-lcl

Supporting information of 'Single-cell RNA sequencing of a European and an African lymphoblastoid cell line'

sctenifoldknk icon sctenifoldknk

R/MATLAB package to perform virtual knockout experiments on single-cell gene regulatory networks.

sctenifoldnet icon sctenifoldnet

A R/MATLAB package to construct and compare gene regulatory networks from single-cell transcriptomic data

sm-sctenifoldnet icon sm-sctenifoldnet

Support material for "scTenifoldNet: A Machine Learning Workflow for Constructing and Comparing Transcriptome-wide Gene Regulatory Networks from Single-Cell Data"

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