A Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference

By Tsuyoshi Kato, Kinya Okada, Hisashi Kashima, Masashi Sugiyama. 2010

43 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Marco Loog
2. Qian Xu
3. Qiang Yang
4. Wouter M. Kouw

In Molecular Biology

1. Qiang Yang
2. Wouter M. Kouw
3. Qian Xu
4. Marco Loog
5. Yan Cui
6. Yu Zhang

Citations in the corpus

• Transfer Learning for Molecular Cancer Classification Using Deep Neural Networks (2019, background): “[19] proposed a transfer learning algorithm to infer biological net-”
• A Survey of Transfer and Multitask Learning in Bioinformatics (2011, background): “[45] considered multiple assays where learning via the sharing of local knowledge occurs, reflected by learning weights in the formula below:”
• A Review of Domain Adaptation without Target Labels (2019, methodology): “In bioinformatics, adaptive approaches have been successful in sequence classification [58], [59] and biological network reconstruction [60].”