Multi-source medical knowledge adaptive fusion network for combinatorial medication recommendation.

Heterogeneous graph contrastive learning with gradient balance for drug repositioning.

Orchestrating information across tissues via a novel multitask GAT framework to improve quantitative gene regulation relation modeling for survival analysis.

EvaGoNet: An integrated network of variational autoencoder and Wasserstein generative adversarial network with gradient penalty for binary classification tasks.

EpiTEAmDNA: Sequence feature representation via transfer learning and ensemble learning for identifying multiple DNA epigenetic modification types across species.

Gender-specific dysregulations of nondifferentially expressed biomarkers of metastatic colon cancer.

Transforming OMIC features for classification using siamese convolutional networks.

Pan-cancer identification of the relationship of metabolism-related differentially expressed transcription regulation with non-differentially expressed target genes via a gated recurrent unit network.

HLAB: learning the BiLSTM features from the ProtBert-encoded proteins for the class I HLA-peptide binding prediction.

Impacts of high-quality public data: Special issue on integrating public and in-house biomedical data.

RIFS2D: A two-dimensional version of a randomly restarted incremental feature selection algorithm with an application for detecting low-ranked biomarkers.

Computational pan-cancer characterization of model-based quantitative transcription regulations dysregulated in regional lymph node metastasis.

Application of Bayesian phylogenetic inference modelling for evolutionary genetic analysis and dynamic changes in 2019-nCoV.

A comprehensive comparison of residue-level methylation levels with the regression-based gene-level methylation estimations by ReGear.

Survival Time Prediction of Breast Cancer Patients Using Feature Selection Algorithm Crystall.

RTL3D: real-time LIDAR-based 3D object detection with sparse CNN.

Selection of features for patient-independent detection of seizure events using scalp EEG signals.

FeSTwo, a two-step feature selection algorithm based on feature engineering and sampling for the chronological age regression problem.

Feature selection may improve deep neural networks for the bioinformatics problems.

ELMO: An Efficient Logistic Regression-Based Multi-Omic Integrated Analysis Method for Breast Cancer Intrinsic Subtypes.

MuscNet, a Weighted Voting Model of Multi-Source Connectivity Networks to Predict Mild Cognitive Impairment Using Resting-State Functional MRI.