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- DeepSig: deep learning improves signal peptide detection in proteins | Bioinformatics - Oxford Academic
DeepSig is designed for both detecting signal peptides and finding their cleavage sites in protein sequences The predictor consists of two consecutive building blocks: a deep neural network architecture and a probabilistic method that incorporates the current biological knowledge of the signal peptide structure
- A Search For The Sm Higgs Boson In The Process Zhllbb In 4. 1 fb Of Cdf Ii Data by Shalhout Zaki Shalhout - digitalcommons. wayne. edu
This dissertation presents a search for the standard model (SM) Higgs boson in the associated production process ZH → l + l - bb using 4 1fb -1 of Tevatron collision data collected with the CDF II detector To increase the sensitivity to a ZH signal over previous CDF searches, we implement new electron and expanded b-jet identification algorithms
- [1812. 04342] Learning latent representations for style control and transfer in end-to-end speech synthesis - arXiv. org
In this paper, we introduce the Variational Autoencoder (VAE) to an end-to-end speech synthesis model, to learn the latent representation of speaking styles in an unsupervised manner The style representation learned through VAE shows good properties such as disentangling, scaling, and combination, which makes it easy for style control
- Search for the standard model Higgs boson produced in association with a Z boson in 7. 9 fb−1 of pp¯ collisions at s=1. 96 TeV using the . . . - ScienceDirect
Using a new technique, we are able to accurately model the combined behavior of these triggers, allowing access to ZH candidate events beyond the reach of the previous CDF searches To enhance signal discrimination, we form a multi-stage event discriminant organized to isolate ZH candidates from known SM and instrumental processes (backgrounds) 2
- SignalP 5. 0 improves signal peptide predictions using deep neural networks
We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs Signal peptides (SPs) are found in
- Deep convolutional neural networks for LVCSR - IEEE Xplore
Abstract: Convolutional Neural Networks (CNNs) are an alternative type of neural network that can be used to reduce spectral variations and model spectral correlations which exist in signals Since speech signals exhibit both of these properties, CNNs are a more effective model for speech compared to Deep Neural Networks (DNNs)
- A comprehensive review of signal peptides: Structure, roles, and applications
Signal peptides (SP) are short peptides located in the N-terminal of proteins, carrying information for protein secretion They are ubiquitous to all prokaryotes and eukaryotes SPs have been of special interest in several scientific and industrial fields, including recombinant protein production, disease diagnosis, immunization, and laboratory
- Study on Weak Signal Detection Methods | SpringerLink
Weak signal detection technology refers to a technology which analyzes the noise’s production laws and researches the characteristics and correlation of signals with relevant electronics, physics, information, and computer knowledge and techniques, to detect the weak signals that are submerged by noises
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