Machine learning applications in river research: Trends, opportunities and challenges

L Ho, P Goethals - Methods in Ecology and Evolution, 2022 - Wiley Online Library
As one of the earth's key ecosystems, rivers have been intensively studied and modelled
through the application of machine learning (ML). With the amount of large data available …

A survey on methods for predicting polyadenylation sites from DNA sequences, bulk RNA-seq, and single-cell RNA-seq

W Ye, Q Lian, C Ye, X Wu - Genomics, Proteomics and …, 2023 - academic.oup.com
Alternative polyadenylation (APA) plays important roles in modulating mRNA stability,
translation, and subcellular localization, and contributes extensively to shaping eukaryotic …

Advances in machine learning modeling reviewing hybrid and ensemble methods

S Ardabili, A Mosavi, AR Várkonyi-Kóczy - International conference on …, 2019 - Springer
The conventional machine learning (ML) algorithms are continuously advancing and
evolving at a fast-paced by introducing the novel learning algorithms. ML models are …

Context-aware poly (a) signal prediction model via deep spatial–temporal neural networks

Y Guo, D Zhou, P Li, C Li, J Cao - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Polyadenylation Poly (A) is an essential process during messenger RNA (mRNA) maturation
in biological eukaryote systems. Identifying Poly (A) signals (PASs) from the genome level is …

[HTML][HTML] Splice2Deep: An ensemble of deep convolutional neural networks for improved splice site prediction in genomic DNA

S Albaradei, A Magana-Mora, M Thafar, M Uludag… - Gene, 2020 - Elsevier
Background The accurate identification of the exon/intron boundaries is critical for the
correct annotation of genes with multiple exons. Donor and acceptor splice sites (SS) …

Survey of deep learning techniques for disease prediction based on omics data

X Yu, S Zhou, H Zou, Q Wang, C Liu, M Zang, T Liu - Human Gene, 2023 - Elsevier
In the era of big data, computer science has been applied to every aspect of biomedical
field. At the same time, transforming biomedical data into valuable knowledge is one of the …

Alternative splicing affects synapses in the hippocampus of offspring after maternal fructose exposure during gestation and lactation

Y Zou, Q Guo, Y Chang, Y Zhong, L Cheng… - Chemico-Biological …, 2023 - Elsevier
Increased fructose over-intake is a global issue. Maternal fructose exposure during gestation
and lactation can impair brain development in offspring. However, the effect on synapses is …

Well control space out: A deep-learning approach for the optimization of drilling safety operations

A Magana-Mora, M Affleck, M Ibrahim… - IEEE …, 2021 - ieeexplore.ieee.org
As drilling of new oil and gas wells increase to meet energy demands, it is essential to
optimize processes to ensure the health and safety of the crew as well as the protection of …

Context-aware dynamic neural computational models for accurate Poly (A) signal prediction

Y Guo, C Li, D Zhou, J Cao, H Liang - Neural networks, 2022 - Elsevier
Abstract Accurately predicting Polyadenylation (Poly (A)) signals isthe key to understand the
mechanism of translation regulation and mRNA metabolism. However, existing …

Machine-learning model for the prediction of lithology porosity from surface drilling parameters

A Magana-Mora, M Abughaban, A Ali - Abu Dhabi International …, 2020 - onepetro.org
Introduction The accurate characterization of the lithology porosity is critical for geological
interpretation and decision making in petroleum exploration. For this, wireline logging …