Statistical Network Inference for Time-Varying Molecular Data with Dynamic Bayesian Networks.
Sign Up to like & getrecommendations! Published in 2019 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-8882-2_2
Abstract: In this chapter, we review the problem of network inference from time-course data, focusing on a class of graphical models known as dynamic Bayesian networks (DBNs). We discuss the relationship of DBNs to models based… read more here.
Keywords: network; time varying; time; network inference ... See more keywords
SIES: A Novel Implementation of Spiking Convolutional Neural Network Inference Engine on Field-Programmable Gate Array
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Computer Science and Technology"
DOI: 10.1007/s11390-020-9686-z
Abstract: Neuromorphic computing is considered to be the future of machine learning, and it provides a new way of cognitive computing. Inspired by the excellent performance of spiking neural networks (SNNs) on the fields of low-power… read more here.
Keywords: network; convolutional neural; network inference; neural network ... See more keywords
Bayesian Network inference for probabilistic strength estimation of aging pipeline systems
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Pressure Vessels and Piping"
DOI: 10.1016/j.ijpvp.2018.01.004
Abstract: Abstract A novel approach for reliability assessment of aging gas pipeline systems based on a Bayesian network methodology is proposed in this paper with a focus on the improvement of the pipeline strength prediction. A… read more here.
Keywords: network inference; strength; pipeline systems; bayesian network ... See more keywords
Experimental noise cutoff boosts inferability of transcriptional networks in large-scale gene-deletion studies
Sign Up to like & getrecommendations! Published in 2017 at "Nature Communications"
DOI: 10.1038/s41467-017-02489-x
Abstract: Generating a comprehensive map of molecular interactions in living cells is difficult and great efforts are undertaken to infer molecular interactions from large-scale perturbation experiments. Here, we develop the analytical and numerical tools to quantify… read more here.
Keywords: large scale; network; transcriptional networks; network inference ... See more keywords
Network inference from short, noisy, low time-resolution, partial measurements: Application to C. elegans neuronal calcium dynamics.
Sign Up to like & getrecommendations! Published in 2023 at "Proceedings of the National Academy of Sciences of the United States of America"
DOI: 10.1073/pnas.2216030120
Abstract: Network link inference from measured time series data of the behavior of dynamically interacting network nodes is an important problem with wide-ranging applications, e.g., estimating synaptic connectivity among neurons from measurements of their calcium fluorescence.… read more here.
Keywords: network; calcium; time; network inference ... See more keywords
Interaction-based transcriptome analysis via differential network inference
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in Bioinformatics"
DOI: 10.1093/bib/bbac466
Abstract: Abstract Gene-based transcriptome analysis, such as differential expression analysis, can identify the key factors causing disease production, cell differentiation and other biological processes. However, this is not enough because basic life activities are mainly driven… read more here.
Keywords: network; differential network; network inference; interaction based ... See more keywords
MANIEA: A Microbial Association Network Inference Method Based on Improved Eclat Association Rule Mining Algorithm.
Sign Up to like & getrecommendations! Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab241
Abstract: MOTIVATION Modelling microbiome systems as complex networks is known as the problem of network inference. Microbial association network inference is of great significance in applications on clinical diagnosis, disease treatment, pathological analysis, etc. However, most… read more here.
Keywords: network; association; microbial association; network inference ... See more keywords
Importance-Penalized Joint Graphical Lasso (IPJGL): differential network inference via GGMs.
Sign Up to like & getrecommendations! Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab751
Abstract: MOTIVATION Differential network inference is a fundamental and challenging problem to reveal gene interactions and regulation relationships under different conditions. Many algorithms have been developed for this problem; however, they do not consider the differences… read more here.
Keywords: network inference; importance penalized; differential network;
Multiple hot‐deck imputation for network inference from RNA sequencing data
Sign Up to like & getrecommendations! Published in 2018 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btx819
Abstract: Motivation: Network inference provides a global view of the relations existing between gene expression in a given transcriptomic experiment (often only for a restricted list of chosen genes). However, it is still a challenging problem:… read more here.
Keywords: imputation; network; inference rna; network inference ... See more keywords
Dual threshold optimization and network inference reveal convergent evidence from TF binding locations and TF perturbation responses.
Sign Up to like & getrecommendations! Published in 2020 at "Genome research"
DOI: 10.1101/gr.259655.119
Abstract: A high-confidence map of the direct, functional targets of each transcription factor (TF) requires convergent evidence from independent sources. Two significant sources of evidence are TF binding locations and the transcriptional responses to direct TF… read more here.
Keywords: threshold optimization; network; binding locations; evidence ... See more keywords
On the Properties of Gromov Matrices and Their Applications in Network Inference
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2019.2908133
Abstract: The spanning tree heuristic is a commonly adopted procedure in network inference and estimation. It allows one to generalize an inference method developed for trees, which is usually based on a statistically rigorous approach, to… read more here.
Keywords: inference; network inference; applications network; gromov matrices ... See more keywords