A General Causal Inference Framework by Encoding Generative Modeling
Python 57 8
PECA is a software for inferring context specific gene regulatory network from paired gene expression and chromatin accessibility data
MATLAB 42 6
Complex structural variant detection from WGS data
Python 21 6
HTML 19 5
Regression with Summary Statistics exploiting Network Topology.
R 17 4
Coupled clustering of single cell genomic data
Python 12 1
cRegulon is an optimization model to identify combinatorial regulon from single cell expression and chromatin accessibility data.
A Bayesian approach for generative modeling of high-dimensional data
Sequence-conserved Enhancer-like Elements
time course regulatory analysis from paired gene expression and chromatin accessibility time course data
Polygenic prediction by leveraging genomic large language models
Roundtrip: a deep generative neural density estimator
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