Architectures and accuracy of artificial neural network for disease classification from omics data

Phylogenetic convolutional neural networks in metagenomics

(2018) Diego Fioravanti et al.   BMC BIOINFORMATICS

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

(2018) Travers Ching et al.   PLoS Computational Biology

$\mathtt {Deepr}$: A Convolutional Net for Medical Records

(2017) Phuoc Nguyen et al.   IEEE Journal of Biomedical and Health Informatics

Convolutional neural network architectures for predicting DNA–protein binding

(2016) Haoyang Zeng et al.   BIOINFORMATICS

Sample normalization methods in quantitative metabolomics

(2016) Yiman Wu et al.   JOURNAL OF CHROMATOGRAPHY A

TCGA2STAT: simple TCGA data access for integrated statistical analysis in R

(2015) Ying-Wooi Wan et al.   BIOINFORMATICS

Multi-Layer and Recursive Neural Networks for Metagenomic Classification

(2015) Gregory Ditzler et al.   IEEE TRANSACTIONS ON NANOBIOSCIENCE

Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

(2015) Truyen Tran et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Deep learning

(2015) Yann LeCun et al.   NATURE

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

(2015) Babak Alipanahi et al.   NATURE BIOTECHNOLOGY

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

(2010)   NATURE BIOTECHNOLOGY

An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies

(2009) L. J. Lancashire et al.   BRIEFINGS IN BIOINFORMATICS