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Identifying and ranking potential cancer drivers using representation learning on attributed network

期刊: METHODS, 2021; 192 ()

Cancer can arise as a consequence of the accumulation of genomic alterations. Only a small part of driver mutations contributes to cancer development ......

DeepTL-Ubi: A novel deep transfer learning method for effectively predicting ubiquitination sites of multiple species

期刊: METHODS, 2021; 192 ()

Ubiquitination is one of the most important post-translational modifications which involves in many biological processes. Because mass spectrometry-ba......

PrGeFNE: Predicting disease-related genes by fast network embedding

期刊: METHODS, 2021; 192 ()

Identifying disease-related genes is of importance for understanding of molecule mechanisms of diseases, as well as diagnosis and treatment of disease......

Detect differentially methylated regions using non-homogeneous hidden Markov model for bisulfite sequencing data

期刊: METHODS, 2021; 189 ()

DNA methylation plays an important role in many biological processes and diseases. With the rise of the whole genome bisulfite sequencing technique, a......

A network embedding based method for partial multi-omics integration in cancer subtyping

期刊: METHODS, 2021; 192 ()

Integrative analysis of multiple omics offers the opportunity to uncover coordinated cellular processes acting across different omics layers. The ever......

A multi-objective optimization method for identification of module biomarkers for disease diagnosis

期刊: METHODS, 2021; 192 ()

Biomarker identification aims at finding a set of biological indicators that best discriminate biological samples of different phenotypes. In this pap......

A novel subnetwork representation learning method for uncovering disease-disease relationships

期刊: METHODS, 2021; 192 ()

Analyzing disease-disease relationships plays an important role for understanding disease mechanisms and finding alternative uses for a drug. A diseas......

Deep learning of brain magnetic resonance images: A brief review

期刊: METHODS, 2021; 192 ()

Magnetic resonance imaging (MRI) is one of the most popular techniques in brain science and is important for understanding brain function and neuropsy......

Variational graph auto-encoders for miRNA-disease association prediction

期刊: METHODS, 2021; 192 ()

Cumulative experimental studies have demonstrated the critical roles of microRNAs (miRNAs) in the diverse fundamental and important biological process......

Ensemble learning models that predict surface protein abundance from single-cell multimodal omics data

期刊: METHODS, 2021; 189 ()

Single-cell protein abundance is a fundamental type of information to characterize cell states. Due to high cost and technical barriers, however, dire......

A network-based computational framework to predict and differentiate functions for gene isoforms using exon-level expression data

期刊: METHODS, 2021; 189 ()

Motivation: Alternative splicing makes significant contributions to functional diversity of transcripts and proteins. Many alternatively spliced gene ......

Prediction and interpretation of cancer survival using graph convolution neural networks

期刊: METHODS, 2021; 192 ()

The survival rate of cancer has increased significantly during the past two decades for breast, prostate, testicular, and colon cancer, while the brai......

Hyper-graph based sparse canonical correlation analysis for the diagnosis of Alzheimer?s disease from multi-dimensional genomic data

期刊: METHODS, 2021; 189 ()

The effective and accurate diagnosis of Alzheimer?s disease (AD), especially in the early stage (i.e., mild cognitive impairment (MCI)) remains a big ......

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