Results 81 to 90 of about 7,083,147 (335)
Epigenetic reprogramming of lineage switching in cancer
Cancer cells rarely commit to a single identity. Epigenetic mechanisms and tumor microenvironment cues push epithelial cells toward flexible, hybrid states that can shift into mesenchymal, neuroendocrine, or stem‐like fates, driving metastasis, drug resistance, and tumor heterogeneity. Targeting the epigenetic regulators behind these transitions, using
Ezgi Boyvatlı +4 more
wiley +1 more source
A Model for Programmability and Virtuality in Dynamical Neural Networks [PDF]
In this dissertation a fixed-weight architecture for Continuous Time Recurrent Neural Networks (CTRNNs) is proposed in order to give an account for biological phenomena, controlled by neuronal activity, in which changes of behavior occur so fast that ...
Donnarumma, Francesco
core +1 more source
Unsupervised Recurrent Neural Network Grammars [PDF]
Recurrent neural network grammars (RNNG) are generative models of language which jointly model syntax and surface structure by incrementally generating a syntax tree and sentence in a top-down, left-to-right order.
Yoon Kim +5 more
semanticscholar +1 more source
Metastatic niche shaped by host factors influences disseminated cancer cell fate
Metastasis is shaped not only by cancer cells but also by the environments they encounter. This review explores how factors such as aging, diet, the microbiome, lifestyle, and environmental exposures remodel organ‐specific niches in the lung, liver, bone, and brain, influencing where metastatic cells survive, remain dormant, or grow, and ultimately ...
Gwennan Delyth Ward +2 more
wiley +1 more source
Sentiment analysis has been a well-studied research direction in computational linguistics. Deep neural network models, including convolutional neural networks (CNN) and recurrent neural networks (RNN), yield promising results on text classification ...
Aytuğ Onan
doaj +1 more source
Using recurrent neural network models for early detection of heart failure onset
Objective: We explored whether use of deep learning to model temporal relations among events in electronic health records (EHRs) would improve model performance in predicting initial diagnosis of heart failure (HF) compared to conventional methods that ...
E. Choi +3 more
semanticscholar +1 more source
Relational recurrent neural networks
Memory-based neural networks model temporal data by leveraging an ability to remember information for long periods. It is unclear, however, whether they also have an ability to perform complex relational reasoning with the information they remember.
Adam Santoro +9 more
openaire +3 more sources
A lecture transcription system combining neural network acoustic and language models [PDF]
This paper presents a new system for automatic transcription of lectures. The system combines a number of novel features, including deep neural network acoustic models using multi-level adaptive networks to incorporate out-of-domain information, and ...
Hori, C +6 more
core
Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis [PDF]
This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Elsevier LtdThis Letter is concerned with the analysis problem of exponential stability for a class of discrete-time ...
Liu, Y, Liu, X, Wang, Z, Serrano, A
core +1 more source
Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment
This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley +1 more source

