PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data
Authors
Keywords
Sparse deep neural network, Prognosis prediction, Long-term survival prediction, Pathway-based analysis, Glioblastoma multiforme, TCGA
Journal
BMC BIOINFORMATICS
Volume 19, Issue 1, Pages -
Publisher
Springer Nature
Online
2018-12-17
DOI
10.1186/s12859-018-2500-z
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Prediction of Long-Term Survival After Lung Cancer Surgery for Elderly Patients in The Society of Thoracic Surgeons General Thoracic Surgery Database
- (2018) Mark W. Onaitis et al. ANNALS OF THORACIC SURGERY
- Opportunities and obstacles for deep learning in biology and medicine
- (2018) Travers Ching et al. Journal of the Royal Society Interface
- Using deep learning to model the hierarchical structure and function of a cell
- (2018) Jianzhu Ma et al. NATURE METHODS
- Current state of immunotherapy for glioblastoma
- (2018) Michael Lim et al. Nature Reviews Clinical Oncology
- Training neural networks on high-dimensional data using random projection
- (2018) Piotr Iwo Wójcik et al. PATTERN ANALYSIS AND APPLICATIONS
- Pathway aggregation for survival prediction via multiple kernel learning
- (2018) Jennifer A. Sinnott et al. STATISTICS IN MEDICINE
- VEGF as a modulator of the innate immune response in glioblastoma
- (2017) Kati Turkowski et al. GLIA
- Prediction of long‑term survival rates in patients undergoing curative resection for solitary hepatocellular carcinoma
- (2017) Yi Cao et al. Oncology Letters
- Heterogeneity of tumor-infiltrating lymphocytes ascribed to local immune status rather than neoantigens by multi-omics analysis of glioblastoma multiforme
- (2017) Lin Feng et al. Scientific Reports
- A Review of Pathway-Based Analysis Tools That Visualize Genetic Variants
- (2017) Elisa Cirillo et al. Frontiers in Genetics
- Recursive random forest algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways
- (2017) Wenping Deng et al. PLoS One
- Hijacking GPCRs by viral pathogens and tumor
- (2016) Junjie Zhang et al. BIOCHEMICAL PHARMACOLOGY
- Convolutional neural network architectures for predicting DNA–protein binding
- (2016) Haoyang Zeng et al. BIOINFORMATICS
- Bottom-up GGM algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways or processes
- (2016) Sapna Kumari et al. BMC BIOINFORMATICS
- Deep learning in bioinformatics
- (2016) Seonwoo Min et al. BRIEFINGS IN BIOINFORMATICS
- Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters
- (2016) Yifeng Li et al. JOURNAL OF COMPUTATIONAL BIOLOGY
- The role of AKT isoforms in glioblastoma: AKT3 delays tumor progression
- (2016) Anna Joy et al. JOURNAL OF NEURO-ONCOLOGY
- Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian Hierarchical Approach
- (2016) Lisa M. Pham et al. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
- Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis
- (2016) Sijia Huang et al. Genome Medicine
- Molecular Predictors of Long-Term Survival in Glioblastoma Multiforme Patients
- (2016) Jie Lu et al. PLoS One
- Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure
- (2015) Yanming Li et al. BIOMETRICS
- G protein-coupled receptors in stem cell maintenance and somatic reprogramming to pluripotent or cancer stem cells
- (2015) Hye Yeon Choi et al. BMB Reports
- Analysis of the gene-protein interaction network in glioma
- (2015) C. Zhou et al. GENETICS AND MOLECULAR RESEARCH
- Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach
- (2015) Muxuan Liang et al. IEEE-ACM Transactions on Computational Biology and Bioinformatics
- 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
- The Molecular Signatures Database Hallmark Gene Set Collection
- (2015) Arthur Liberzon et al. Cell Systems
- Validation of prediction models based on lasso regression with multiply imputed data
- (2014) Jammbe Z Musoro et al. BMC Medical Research Methodology
- Astrocyte Elevated Gene-1 Interacts with Akt Isoform 2 to Control Glioma Growth, Survival, and Pathogenesis
- (2014) B. Hu et al. CANCER RESEARCH
- G protein-coupled receptors as oncogenic signals in glioma: Emerging therapeutic avenues
- (2014) A.E. Cherry et al. NEUROSCIENCE
- Pathway-based Analysis Tools for Complex Diseases: A Review
- (2014) Lv Jin et al. GENOMICS PROTEOMICS & BIOINFORMATICS
- Pathway-based personalized analysis of cancer
- (2013) Y. Drier et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Pathway-based classification of cancer subtypes
- (2012) Shinuk Kim et al. Biology Direct
- Random lasso
- (2011) Sijian Wang et al. Annals of Applied Statistics
- Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via logistic mixed models
- (2008) Dawei Liu et al. BMC BIOINFORMATICS
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now