Multimodal machine learning in precision health: A sco** review
Abstract Machine learning is frequently being leveraged to tackle problems in the health
sector including utilization for clinical decision-support. Its use has historically been focused …
sector including utilization for clinical decision-support. Its use has historically been focused …
Machine learning: its challenges and opportunities in plant system biology
Sequencing technologies are evolving at a rapid pace, enabling the generation of massive
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …
Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier
Protein-protein interactions (PPIs) are involved with most cellular activities at the proteomic
level, making the study of PPIs necessary to comprehending any biological process …
level, making the study of PPIs necessary to comprehending any biological process …
Prediction and analysis of train arrival delay based on XGBoost and Bayesian optimization
R Shi, X Xu, J Li, Y Li - Applied Soft Computing, 2021 - Elsevier
Accurate train arrival delay prediction is critical for real-time train dispatching and for the
improvement of the transportation service. This study proposes a data-driven method that …
improvement of the transportation service. This study proposes a data-driven method that …
Early prediction of diabetes using an ensemble of machine learning models
Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of
significant complications, including cardiovascular disease, kidney failure, diabetic …
significant complications, including cardiovascular disease, kidney failure, diabetic …
LightGBM-PPI: Predicting protein-protein interactions through LightGBM with multi-information fusion
Protein-protein interactions (PPIs) play an important role in cell life activities such as
transcriptional regulation, signal transduction and drug signal transduction. The study of …
transcriptional regulation, signal transduction and drug signal transduction. The study of …
Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework
Origins of replication sites (ORIs), which refers to the initiative locations of genomic DNA
replication, play essential roles in DNA replication process. Detection of ORIs' distribution in …
replication, play essential roles in DNA replication process. Detection of ORIs' distribution in …
SDNN-PPI: self-attention with deep neural network effect on protein-protein interaction prediction
Abstract Background Protein-protein interactions (PPIs) dominate intracellular molecules to
perform a series of tasks such as transcriptional regulation, information transduction, and …
perform a series of tasks such as transcriptional regulation, information transduction, and …
MARPPI: boosting prediction of protein–protein interactions with multi-scale architecture residual network
Protein–protein interactions (PPIs) are a major component of the cellular biochemical
reaction network. Rich sequence information and machine learning techniques reduce the …
reaction network. Rich sequence information and machine learning techniques reduce the …
iEnhancer-5Step: identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding
An enhancer is a short (50–1500bp) region of DNA that plays an important role in gene
expression and the production of RNA and proteins. Genetic variation in enhancers has …
expression and the production of RNA and proteins. Genetic variation in enhancers has …