A quantile geometry-enhanced graph neural network is proposed to learn the molecular structure-retention time relationship, which shows a satisfactory predictive ability for enantiomers. The domain knowledge of chromatography is incorporated into the machine learning model to achieve multi-column prediction,...
The model assumes that the vertices of the graph are partitioned into two unknown blocks and that the probability of an edge between two vertices depends only on the blocks to which they belong. Statistical procedures are derived for estimating the probabilities of edges and for predicting the ...
Time-Aware Long Short-Term Memory was used to quantitatively predict the children’s and adolescents’ spherical equivalent within two and a half years. The mean absolute prediction error on the testing set was 0.103 ± 0.140 (D) for spherical equivalent, ranging from 0.040 ± 0.050 (D) to ...
- If the deserialized JSON object was missing any required properties. grades public List grades() Get the grades property: The prediction grades. Returns: the grades value.id public String id() Get the id property: Fully qualified resource Id for the resource. Overrides...
. ├── Metrics.py # The core source code of metrics. ├── graphConstruct.py # The core source code of building hypergraph. ├── parsers.py # The core source code of parameter settings. └── Constants.py: └── dataLoader.py: # Data loading. └── run.py: # Run the ...
Returns: the project valueresizedImageUri public String resizedImageUri() Get the resizedImageUri value. Returns: the resizedImageUri valuethumbnailUri public String thumbnailUri() Get the thumbnailUri value. Returns: the thumbnailUri valueApplies to Azure SDK for Java Latest在...
In this study, a novel method called TPpred-LE based on Transformer framework was proposed for predicting therapeutic peptide multiple functions, which can explicitly extract the function correlation information by using label embedding methodology and exploit the specificity information based on function-...
The primary contributions of GPDRP include: 1. We integrate the drug molecular graph with gene pathway activity score, leveraging the strengths of both types of data to enhance the predictive power of our model. 2. We introduce GPDRP, a novel multimodal framework for DRP, which leverages ...
Tandem mass spectra capture fragmentation patterns that provide key structural information about molecules. Although mass spectrometry is applied in many areas, the vast majority of small molecules lack experimental reference spectra. For over 70 years,
To improve the prediction accuracy of traffic flow under the influence of nearby time traffic flow disturbance, a dynamic spatiotemporal graph attention network traffic flow prediction model based on the attention mechanism was proposed. Considering the macroscopic periodic characteristics of traffic flow,...