Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: NExUS: Bayesian simultaneous network estimation across unequal sample
  sizes   Network-based analyses of high-throughput genomics data provide a holistic,
systems-level understanding of various biological mechanisms for a common
population. However, when estimating multiple networks across heterogeneous
sub-populations, varying sample sizes pose a challenge in the estimation and
inference, as network differences may be driven by differences in power. We are
particularly interested in addressing this challenge in the context of
proteomic networks for related cancers, as the number of subjects available for
rare cancer (sub-)types is often limited. We develop NExUS (Network Estimation
across Unequal Sample sizes), a Bayesian method that enables joint learning of
multiple networks while avoiding artefactual relationship between sample size
and network sparsity. We demonstrate through simulations that NExUS outperforms
existing network estimation methods in this context, and apply it to learn
network similarity and shared pathway activity for groups of cancers with
related origins represented in The Cancer Genome Atlas (TCGA) proteomic data.

8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph