ArticleTechnometrics : a journal of statistics for the physical, chemical, and engineering sciences
A Transfer Learning Approach for Predictive Modeling of Degenerate Biological Systems.
Article in Technometrics : a journal of statistics for the physical, chemical, and engineering sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A Review.IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2025Article
- PrCRS: a prediction model of severe CRS in CAR-T therapy based on transfer learning.BMC bioinformatics · 2024Article
- Towards a more general drug target interaction prediction model using transfer learning.Procedia computer science · 2023Article
- Binding affinity prediction for binary drug-target interactions using semi-supervised transfer learning.Journal of computer-aided molecular design · 2021Article
- Medication Adherence Prediction Through Online Social Forums: A Case Study of Fibromyalgia.JMIR medical informatics · 2019Article
- Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning.AJNR. American journal of neuroradiology · 2019Article
- A context-free encoding scheme of protein sequences for predicting antigenicity of diverse influenza A viruses.BMC genomics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Modeling of a new domain can be challenging due to scarce data and high-dimensionality. Transfer learning aims to integrate data of the new domain with knowledge about some related old domains, in order to model the new domain better. This paper studies transfer learning for degenerate biological systems. Degeneracy refers to the phenomenon that structurally different elements of the system perform the same/similar function or yield the same/similar output. Degeneracy exits in various biological systems and contributes to the heterogeneity, complexity, and robustness of the systems. Modeling of degenerate biological systems is challenging and models enabling transfer learning in such systems have been little studied. In this paper, we propose a predictive model that integrates transfer learning and degeneracy under a Bayesian framework. Theoretical properties of the proposed model are studied. Finally, we present an application of modeling the predictive relationship between transcription factors and gene expression across multiple cell lines. The model achieves good prediction accuracy, and identifies known and possibly new degenerate mechanisms of the system.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.