Supervised network inference

Dropouts distort gene expression and misclassify cell types in single-cell transcriptome. Although imputation may improve gene expression and downstream analysis to some degree, it also inevitably introduces false signals. We develop DISC, a novel deep learning network with semi-supervised learning to infer gene structure and expression obscured by dropouts.

28p viarchimedes 26-01-2022 8 0   Download

Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate.

14p viwyoming2711 16-12-2020 10 1   Download

Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized.

13p vikentucky2711 26-11-2020 12 1   Download

Predication of gene regularity network (GRN) from expression data is a challenging task. There are many methods that have been developed to address this challenge ranging from supervised to unsupervised methods. Most promising methods are based on support vector machine (SVM).

7p vikentucky2711 26-11-2020 12 1   Download

Despite the great technological advancement experienced in recent years, Programmable Logic Controllers (PLC) are still used in many applications from the real world and still play a central role in infrastructure of industrial automation. PLC operate in the factory-floor level and are responsible typically for implementing logical control, regulatory control strategies, such as PID and fuzzy-based algorithms, and safety logics. Usually PLC are interconnected with the supervision level through communication network, such as Ethernet networks, in order to work in an integrated form....

178p 123859674 30-06-2012 174 52   Download