Transfer learning with convolutional neural networks for cancer survival prediction using gene-expression data

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

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DeepInsight: A methodology to transform a non-image data to an image for convolution neural network architecture

(2019) Alok Sharma et al.   Scientific Reports

Phylogenetic convolutional neural networks in metagenomics

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An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data

(2018) Yawen Xiao et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Deep Learning-Based Multi-Omics Data Integration Reveals Two Prognostic Subtypes in High-Risk Neuroblastoma

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Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models

(2017) Safoora Yousefi et al.   Scientific Reports

Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks

(2016) David R. Kelley et al.   GENOME RESEARCH

BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences

(2016) Minoru Kanehisa et al.   JOURNAL OF MOLECULAR BIOLOGY

70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer

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KEGG: new perspectives on genomes, pathways, diseases and drugs

(2016) Minoru Kanehisa et al.   NUCLEIC ACIDS RESEARCH

Identification and Construction of Combinatory Cancer Hallmark–Based Gene Signature Sets to Predict Recurrence and Chemotherapy Benefit in Stage II Colorectal Cancer

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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

Predicting effects of noncoding variants with deep learning–based sequence model

(2015) Jian Zhou et al.   NATURE METHODS

Ensembl 2016

(2015) Andrew Yates et al.   NUCLEIC ACIDS RESEARCH

Machine learning applications in cancer prognosis and prediction

(2015) Konstantina Kourou et al.   Computational and Structural Biotechnology Journal

Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent

(2015) Noah Simon et al.   Journal of Statistical Software

Random survival forests for competing risks

(2014) H. Ishwaran et al.   BIOSTATISTICS

A Multigene Expression Assay to Predict Local Recurrence Risk for Ductal Carcinoma In Situ of the Breast

(2013) L. J. Solin et al.   JNCI-Journal of the National Cancer Institute

The Cancer Genome Atlas Pan-Cancer analysis project

(2013) John N Weinstein et al.   NATURE GENETICS

Hallmarks of Cancer: The Next Generation

(2011) Douglas Hanahan et al.   CELL

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

RNA-Seq: a revolutionary tool for transcriptomics

(2008) Zhong Wang et al.   NATURE REVIEWS GENETICS