Results 91 to 100 of about 5,161,693 (301)
A Novel Data-Driven Boolean Model for Genetic Regulatory Networks
Frontiers in Physiology, 2018 A Boolean model is a simple, discrete and dynamic model without the need to consider the effects at the intermediate levels. However, little effort has been made into constructing activation, inhibition, and protein decay networks, which could indicate ...
Leshi Chen +2 more
doaj +1 more source
Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
Network Inference From Time-Course Data
, 2016 The network inference method presented in this chapter is inspired by the theory of time-lagged correlation inference, and uses a maximum likelihood approach with regard to the estimation of the kinetic parameters of the network.
Thanh-Phuong Nguyen +9 more
core +1 more source
Multi‐sample inference network
IET Computer Vision, 2019 This study explores whether neural networks can classify multiple samples simultaneously in a forward process. Therefore, a multi‐input multi‐prediction network architecture has been proposed. The authors call this method a multi‐sample inference network (MSIN).
Daojun Liang +3 more
openaire +3 more sources
Molecular Oncology, EarlyView.Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur +11 more
wiley +1 more source
ROC curves of network structure inference.
, 2014 The performance of structure inference, under 6 different numbers of perturbations (from 2 to 7), is evaluated by ROC curves. Each subplot contains the inference results for 6 benchmark networks. The average AUROC is 0.97.
Ian Adcock (486486) +4 more
core +1 more source
Multi-Omics Regulatory Network Inference in the Presence of Missing Data
, 2022 Multiomics Regulatory Network Inference in the Presence of Missing Data We present a benchmarking of six different lasso models integrated within the KiMONo approach looking for network inference using multi-omics data dealing with missing ...
Markus List +7 more
core +1 more source
Exploiting fluctuations in gene expression to detect causal interactions between genes
eLifeCharacterizing and manipulating cellular behavior requires a mechanistic understanding of the causal interactions between cellular components.
Euan Joly-Smith +5 more
doaj +1 more source
Structural Inference of Hierarchies in Networks [PDF]
, 2008 One property of networks that has received comparatively little attention is hierarchy, i.e., the property of having vertices that cluster together in groups, which then join to form groups of groups, and so forth, up through all levels of organization in the network.
Aaron Clauset +2 more
openaire +2 more sources
Molecular Oncology, EarlyView.Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq +8 more
wiley +1 more source