AIMC Topic: Gene Regulatory Networks

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A novel graph attention adversarial network for predicting disease-related associations.

Methods (San Diego, Calif.)
Identifying complex human diseases at molecular level is very helpful, especially in diseases diagnosis, therapy, prognosis and monitoring. Accumulating evidences demonstrated that RNAs are playing important roles in identifying various complex human...

Unveiling new disease, pathway, and gene associations via multi-scale neural network.

PloS one
Diseases involve complex modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, new biological knowledge about a disease can be extracted from these prof...

Convolutional neural network models for cancer type prediction based on gene expression.

BMC medical genomics
BACKGROUND: Precise prediction of cancer types is vital for cancer diagnosis and therapy. Through a predictive model, important cancer marker genes can be inferred. Several studies have attempted to build machine learning models for this task however...

Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations.

BMC medical genomics
BACKGROUND: Recent advances in kernel-based Deep Learning models have introduced a new era in medical research. Originally designed for pattern recognition and image processing, Deep Learning models are now applied to survival prognosis of cancer pat...

Meta-Analysis Based on Nonconvex Regularization.

Scientific reports
The widespread applications of high-throughput sequencing technology have produced a large number of publicly available gene expression datasets. However, due to the gene expression datasets have the characteristics of small sample size, high dimensi...

Research on Multi-Time-Delay Gene Regulation Network Based on Fuzzy Label Propagation.

Journal of healthcare engineering
In view of time delay existing in gene regulation, by using the analysis idea and methods of complex network, this paper proposes a multi-time-delay gene regulation network analysis method based on the fuzzy label propagation. The algorithm takes the...

Network modeling of patients' biomolecular profiles for clinical phenotype/outcome prediction.

Scientific reports
Methods for phenotype and outcome prediction are largely based on inductive supervised models that use selected biomarkers to make predictions, without explicitly considering the functional relationships between individuals. We introduce a novel netw...

Finite-time synchronization of fractional-order gene regulatory networks with time delay.

Neural networks : the official journal of the International Neural Network Society
As multi-gene networks transmit signals and products by synchronous cooperation, investigating the synchronization of gene regulatory networks may help us to explore the biological rhythm and internal mechanisms at molecular and cellular levels. We a...

Genome-wide inference of the Camponotus floridanus protein-protein interaction network using homologous mapping and interacting domain profile pairs.

Scientific reports
Apart from some model organisms, the interactome of most organisms is largely unidentified. High-throughput experimental techniques to determine protein-protein interactions (PPIs) are resource intensive and highly susceptible to noise. Computational...

PANDA: Prioritization of autism-genes using network-based deep-learning approach.

Genetic epidemiology
Understanding the genetic background of complex diseases and disorders plays an essential role in the promising precision medicine. The evaluation of candidate genes, however, requires time-consuming and expensive experiments given a large number of ...