iDeep statistics

info info

Citations per year

info

Popular tool citations

chevron_left Protein-binding region prediction chevron_right
info

Tool usage distribution map

Tool usage distribution map
info info

Associated diseases

Associated diseases
Want to access the full stats & trends on this tool?

iDeep specifications

Information


Unique identifier OMICS_13505
Name iDeep
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Stability Stable
Requirements
keras, sklearn
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Hong-Bin Shen

Publication for iDeep

iDeep citations

 (3)
library_books

Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks

2017
Bioinformatics
PMCID: 5905632
PMID: 29155928
DOI: 10.1093/bioinformatics/btx727

[…] rbp individually from 20 parameter trials, yielding the best area under the precision–recall curve (aupr) on the validation set., to compare our approach with the rbp binding site prediction model ideep (), we used the same clip dataset, pre-processing code and model code as , both provided by the authors at https://github.com/xypan1232/ideep. the clip dataset contains 31 clip experiments […]

library_books

RNA protein binding motifs mining with a new hybrid deep learning based cross domain knowledge integration approach

2017
BMC Bioinformatics
PMCID: 5331642
PMID: 28245811
DOI: 10.1186/s12859-017-1561-8

[…] on the sequences, but how to assemble them into the meaningful binding motifs is a topic worth of further investigation., in viewing of these challenges, we propose a deep learning-based framework (ideep) by using a novel hybrid convolutional neural network and deep belief network to predict the rbp interaction sites and motifs on rnas. this new protocol is featured by transforming the original […]

library_books

Improved Techniques for Endoscopic Mucosal Resection (EMR) in Colorectal Adenoma

2014
PMCID: 4513797
PMID: 26286120
DOI: 10.1159/000358243

[…] a synthetic product and may have antigenic potential []., there are other proposals for synthetic substances for injection: tran et al. [] presented an injectable drug-eluting elastomeric polymer (ideep), and chandrasekhara et al. [] described a submucosal lifting gel consisting of a combination of biocompatible components. detailed experience with these materials is missing., in contrast […]


Want to access the full list of citations?
iDeep institution(s)
Department of Veterinary Clinical and Animal Sciences, University of Copenhagen, Copenhagen, Denmark; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China
iDeep funding source(s)
This work was supported by the Science and Technology Commission of Shanghai Municipality (No. 16JC1404300), Fellowship from Faculty of Health and Medical Sciences, University of Copenhagen.

iDeep reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review iDeep