R.I.P.
π»
Ghosted
Finite-State Channel Models for Signal Transduction in Neural Systems
September 18, 2016 Β· Declared Dead Β· π IEEE International Conference on Acoustics, Speech, and Signal Processing
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Andrew W. Eckford, Kenneth A. Loparo, Peter J. Thomas
arXiv ID
1609.05517
Category
q-bio.QM
Cross-listed
cs.IT,
q-bio.NC
Citations
7
Venue
IEEE International Conference on Acoustics, Speech, and Signal Processing
Last Checked
6 months ago
Abstract
Information theory provides powerful tools for understanding communication systems. This analysis can be applied to intercellular signal transduction, which is a means of chemical communication among cells and microbes. We discuss how to apply information-theoretic analysis to ligand-receptor systems, which form the signal carrier and receiver in intercellular signal transduction channels. We also discuss the applications of these results to neuroscience.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β q-bio.QM
R.I.P.
π»
Ghosted
DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences
R.I.P.
π»
Ghosted
ProtVec: A Continuous Distributed Representation of Biological Sequences
R.I.P.
π»
Ghosted
A Perspective on Deep Imaging
R.I.P.
π
404 Not Found
Deep learning in bioinformatics: introduction, application, and perspective in big data era
R.I.P.
π»
Ghosted
Data-driven Advice for Applying Machine Learning to Bioinformatics Problems
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted