FastTENET: an accelerated TENET algorithm based on manycore computing in Python

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Publication Details

Journal
Bioinformatics
Published
2024-11-21
DOI
https://doi.org/10.1093/bioinformatics/btae699
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.23

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article

FastTENET: an accelerated TENET algorithm based on manycore computing in Python

Hyeonkyu Kim, Junil Kim, Daewon Lee, R. Sung
1 citations
Bioinformatics
Single-cell and spatial transcriptomics
0.23
article

FastTENET: an accelerated TENET algorithm based on manycore computing in Python

Hyeonkyu Kim, Junil Kim, Daewon Lee, R. Sung
article en
1 citations

Abstract

No abstract available for this paper.
BioinformaticsVol. 40(12)
Soongsil University (KR), Chung-Ang University (KR)
National Research Foundation, Chung-Ang University, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, National Supercomputing Center, Korea Institute of Science and Technology Information
Openalex Percentile: Top 41%
Single-cell and spatial transcriptomics
0.23
DOIOpen Access PDFOpenAlex
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