Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CLMB: deep contrastive learning for robust metagenomic binning   The reconstruction of microbial genomes from large metagenomic datasets is a
critical procedure for finding uncultivated microbial populations and defining
their microbial functional roles. To achieve that, we need to perform
metagenomic binning, clustering the assembled contigs into draft genomes.
Despite the existing computational tools, most of them neglect one important
property of the metagenomic data, that is, the noise. To further improve the
metagenomic binning step and reconstruct better metagenomes, we propose a deep
Contrastive Learning framework for Metagenome Binning (CLMB), which can
efficiently eliminate the disturbance of noise and produce more stable and
robust results. Essentially, instead of denoising the data explicitly, we add
simulated noise to the training data and force the deep learning model to
produce similar and stable representations for both the noise-free data and the
distorted data. Consequently, the trained model will be robust to noise and
handle it implicitly during usage. CLMB outperforms the previous
state-of-the-art binning methods significantly, recovering the most
near-complete genomes on almost all the benchmarking datasets (up to 17\% more
reconstructed genomes compared to the second-best method). It also improves the
performance of bin refinement, reconstructing 8-22 more high-quality genomes
and 15-32 more middle-quality genomes than the second-best result.
Impressively, in addition to being compatible with the binning refiner, single
CLMB even recovers on average 15 more HQ genomes than the refiner of VAMB and
Maxbin on the benchmarking datasets. CLMB is open-source and available at
https://github.com/zpf0117b/CLMB/.

19
The categories of this paper are: eess
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
31
The categories of this paper are: ao-sci
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph