Attention-based Feature Fusion for Reconstructing Gene-Regulatory Interactions-Reference-Cited by-同舟云学术

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Attention-based Feature Fusion for Reconstructing Gene-Regulatory Interactions

Published:2022-10-13 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)
language:
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Author:

Xiang Mingrong¹,Luo Wei¹,Hou Jingyu¹,Tao Wenjing²

Affiliation:

1. Deakin University,School of Information Technology,Geelong,Australia

2. Southwest University,Key Laboratory of Freshwater Fish Reproduction and Development (Ministry of Education) Key Laboratory of Aquatic Science of Chongqing School of Life Sciences,Chongqing,China,400715

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10032305/10032324/10032449.pdf?arnumber=10032449

Reference34 articles.

1. ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context

2. Learning gene regulatory networks from only positive and unlabeled data

3. Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

4. SCGRNs: Novel supervised inference of single-cell gene regulatory networks of complex diseases

5. Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles

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