Strength of stacking technique of ensemble learning in rockburst prediction with imbalanced data: Comparison of eight single and ensemble models
Rockburst is a common dynamic geological hazard, severely restricting the development
and utilization of underground space and resources. As the depth of excavation and mining …
and utilization of underground space and resources. As the depth of excavation and mining …
UAV-based hyperspectral and ensemble machine learning for predicting yield in winter wheat
Z Li, Z Chen, Q Cheng, F Duan, R Sui, X Huang, H Xu - Agronomy, 2022 - mdpi.com
Winter wheat is a widely-grown cereal crop worldwide. Using growth-stage information to
estimate winter wheat yields in a timely manner is essential for accurate crop management …
estimate winter wheat yields in a timely manner is essential for accurate crop management …
NSRGRN: a network structure refinement method for gene regulatory network inference
The elucidation of gene regulatory networks (GRNs) is one of the central challenges of
systems biology, which is crucial for understanding pathogenesis and curing diseases …
systems biology, which is crucial for understanding pathogenesis and curing diseases …
NSCGRN: a network structure control method for gene regulatory network inference
W Liu, X Sun, L Yang, K Li, Y Yang… - Briefings in …, 2022 - academic.oup.com
Accurate inference of gene regulatory networks (GRNs) is an essential premise for
understanding pathogenesis and curing diseases. Various computational methods have …
understanding pathogenesis and curing diseases. Various computational methods have …
DeepDRIM: a deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-seq data
Single-cell RNA sequencing has enabled to capture the gene activities at single-cell
resolution, thus allowing reconstruction of cell-type-specific gene regulatory networks …
resolution, thus allowing reconstruction of cell-type-specific gene regulatory networks …
Exploring gene regulation and biological processes in insects: Insights from omics data using gene regulatory network models
Gene regulatory network (GRN) comprises complicated yet intertwined gene-regulator
relationships. Understanding the GRN dynamics will unravel the complexity behind the …
relationships. Understanding the GRN dynamics will unravel the complexity behind the …
Inferring a Gene Regulatory Network from Gene Expression Data. An Overview of Best Methods and a Reverse Engineering Approach
Abstract Gene Regulatory Networks (GRNs) are widely used to understand processes in
cellular organisms. The spread of viruses and the development of new unknown diseases …
cellular organisms. The spread of viruses and the development of new unknown diseases …
Inference of gene regulatory networks using pseudo-time series data
Motivation Inferring gene regulatory networks (GRNs) from high-throughput data is an
important and challenging problem in systems biology. Although numerous GRN methods …
important and challenging problem in systems biology. Although numerous GRN methods …
A novel tree-based algorithm for real-time prediction of rockburst risk using field microseismic monitoring
Rockburst is a kind of complex and catastrophic dynamic geological disaster in the
development and utilization of underground space, which seriously threatens the safety of …
development and utilization of underground space, which seriously threatens the safety of …
Time dependence of the enhancement effect of chemical enhancers: molecular mechanisms of enhancing kinetics
X Liu, P Quan, S Li, C Liu, Y Zhao, Y Zhao… - Journal of Controlled …, 2017 - Elsevier
Chemical enhancers are widely used for facilitating drug penetration in transdermal drug
delivery system (TDDS). However, there is a lack of knowledge about how the enhancement …
delivery system (TDDS). However, there is a lack of knowledge about how the enhancement …