CSI-ANN statistics
Tool stats & trends
Looking to identify usage trends or leading experts?
CSI-ANN specifications
Information
| Unique identifier | OMICS_06228 |
|---|---|
| Name | CSI-ANN |
| Software type | Framework/Library |
| Interface | Command line interface |
| Restrictions to use | None |
| Operating system | Unix/Linux, Mac OS, Windows |
| Programming languages | MATLAB |
| Computer skills | Advanced |
| Stability | Stable |
| Maintained | Yes |
Versioning
No version available
Maintainer
- person_outline Kai Tan
Publication for CSI-ANN
Discover regulatory DNA elements using chromatin signatures and artificial neural network
CSI-ANN citations
(3)Identifying noncoding risk variants using disease relevant gene regulatory networks
[…] Enhancers were predicted using the Chromatin Signature Inference by Artificial Neural Network CSI-ANN algorithm. The input to the algorithm is the normalized ChIP-Seq signals of three histone marks (H3K4me1, H3K4me3, and H3K27ac). The algorithm combines signals of all histone marks and uses an […]
eRFSVM: a hybrid classifier to predict enhancers integrating random forests with support vector machines
[…] n immune precipitation sequencing (ChIP-Seq) datasets [, ], such as the chromatin modification loci and the TF binding sites (TFBs) [, ]. Single classifiers used supervised learning algorithms, e.g., CSI-ANN [] introduced an artificial neural network approach; RFECS [] identified enhancers with RF; ChromaGenSVM [] applied SVMs with a Genetic Algorithm (GA) to optimize the parameters of SVMs; Enhan […]
Progress and challenges in bioinformatics approaches for enhancer identification
[…] In particular, CSI-ANN [] is one of the first enhancer classification systems that rely on an ANN using chromatin signatures as input. Putative enhancers derived from human CD4T cell data from Wang et al. [] based o […]
Citations
Looking to check out a full list of citations?
CSI-ANN reviews
Be the first to review CSI-ANN
