Results 51 to 60 of about 606,212 (231)
Inference of Ecological Interaction Networks [PDF]
Annales Zoologici Fennici, 2008 To appear in Annales Zoologici ...
Vera-Licona, Paola +1 more
openaire +2 more sources
Phosphatidylinositol 4‐kinase as a target of pathogens—friend or foe?
FEBS Letters, EarlyView.This graphical summary illustrates the roles of phosphatidylinositol 4‐kinases (PI4Ks). PI4Ks regulate key cellular processes and can be hijacked by pathogens, such as viruses, bacteria and parasites, to support their intracellular replication. Their dual role as essential host enzymes and pathogen cofactors makes them promising drug targets.
Ana C. Mendes +3 more
wiley +1 more source
Gene-network inference by message passing
, 2008 The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing algorithm which is ...
A Braunstein +10 more
core +2 more sources
Neural networks for inference, inference for neural networks
, 2018 Bayesian statistics is a powerful framework for modeling the world and reasoning over uncertainty. It provides a principled method for representing our prior knowledge, and updating that knowledge in the light of new information. Traditional Bayesian statistics, however, has been limited to simple models.
openaire +3 more sources
FEBS Letters, EarlyView.This study reveals how the mitochondrial protein Slm35 is regulated in Saccharomyces cerevisiae. The authors identify stress‐responsive DNA elements and two upstream open reading frames (uORFs) in the 5′ untranslated region of SLM35. One uORF restricts translation, and its mutation increases Slm35 protein levels and mitophagy.
Hernán Romo‐Casanueva +5 more
wiley +1 more source
Identification of Boolean Network Models From Time Series Data Incorporating Prior Knowledge
Frontiers in Physiology, 2018 Motivation: Mathematical models take an important place in science and engineering. A model can help scientists to explain dynamic behavior of a system and to understand the functionality of system components.
Thomas Leifeld, Zhihua Zhang, Ping Zhang
doaj +1 more source
Network Model Selection for Task-Focused Attributed Network Inference
, 2017 Networks are models representing relationships between entities. Often these relationships are explicitly given, or we must learn a representation which generalizes and predicts observed behavior in underlying individual data (e.g. attributes or labels).
Berger-Wolf, Tanya Y. +2 more
core +1 more source
ASIAN: a website for network inference [PDF]
Bioinformatics, 2004 Abstract Summary: We constructed a website for inferring a network by applying the graphical Gaussian model, from a large amount of data, including redundant information. The available tools on the website are based on a system, named ASIAN (Automatic System for Inferring A Network), in combination with the two methods in our previous ...
Sachiyo Aburatani +9 more
openaire +2 more sources
FEBS Letters, EarlyView.We identified a systemic, progressive loss of protein S‐glutathionylation—detected by nonreducing western blotting—alongside dysregulation of glutathione‐cycle enzymes in both neuronal and peripheral tissues of Taiwanese SMA mice. These alterations were partially rescued by SMN antisense oligonucleotide therapy, revealing persistent redox imbalance as ...
Sofia Vrettou, Brunhilde Wirth
wiley +1 more source
Inference of Causal Networks Using a Topological Threshold
IEEE AccessWe propose a constraint-based algorithm, which automatically determines causal relevance thresholds, to infer causal networks from data. We call these topological thresholds.
Filipe Barroso +2 more
doaj +1 more source