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Semisupervised Profiling of Gene Expressions and Clinical Data [chapter]

Silvano Paoli, Giuseppe Jurman, Davide Albanese, Stefano Merler, Cesare Furlanello
2006 Lecture Notes in Computer Science  
The procedure allows identification of noisy cases, whose removal is shown to improve predictive accuracy and the stability of derived gene profiles.  ...  We present an application of BioDCV, a computational environment for semisupervised profiling with Support Vector Machines, aimed at detecting outliers and deriving informative subtypes of patients with  ...  GJ is supported by the FUPAT post-graduate project "Algorithms and software environments for microarray gene expression experiments". We thank S.  ... 
doi:10.1007/11676935_35 fatcat:4repyl3dynhobliftjok3utqyu

Integrating gene expression profiling and clinical data

Silvano Paoli, Giuseppe Jurman, Davide Albanese, Stefano Merler, Cesare Furlanello
2008 International Journal of Approximate Reasoning  
We propose a combination of machine learning techniques to integrate predictive profiling from gene expression with clinical and epidemiological data.  ...  Sampletracking allows also the identification of outlier cases, whose removal is shown to improve predictive accuracy and stability of derived gene profiles.  ...  Dzerosky for helpful indication of this application. We particularly thank the Egrid Project at ICTP Trieste and R. Flor at FBK-irst for guidance in developing the Grid implementation of BioDCV.  ... 
doi:10.1016/j.ijar.2007.03.012 fatcat:56jmhyijsfad5naab26dyqthyu

Novel Molecular Subtypes of Serous and Endometrioid Ovarian Cancer Linked to Clinical Outcome

R. W. Tothill, A. V. Tinker, J. George, R. Brown, S. B. Fox, S. Lade, D. S. Johnson, M. K. Trivett, D. Etemadmoghadam, B. Locandro, N. Traficante, S. Fereday (+6 others)
2008 Clinical Cancer Research  
Conclusion: Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.  ...  Purpose: The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical and pathologic features.  ...  ) for kindly providing tissue samples used in this study; the study nurses and research assistants for their contribution; and all the women who participated in the study.  ... 
doi:10.1158/1078-0432.ccr-08-0196 pmid:18698038 fatcat:zkx525dfprbx7hje5bgvrn7oua

A comparison of Methods for Data-Driven Cancer Outlier Discovery, and An Application Scheme to Semisupervised Predictive Biomarker Discovery

Seppo Karrila, Julian Hock Ean Lee, Greg Tucker-Kellogg
2011 Cancer Informatics  
A core component in translational cancer research is biomarker discovery using gene expression profiling for clinical tumors.  ...  Outlier detection is a key enabling technology of the workflow, and aids in identifying the focus genes.  ...  Acknowledgements The authors gratefully acknowledge the support of their employer, Lilly Singapore Centre for Drug Discovery, a wholly owned subsidiary of Eli Lilly and Company.  ... 
doi:10.4137/cin.s6868 pmid:21584264 pmcid:PMC3091411 fatcat:turx53fyf5g2jk66cv6mcebp2y

Identifying Cancer Biomarkers From Microarray Data Using Feature Selection and Semisupervised Learning

Debasis Chakraborty, Ujjwal Maulik
2014 IEEE Journal of Translational Engineering in Health and Medicine  
Microarray data sets containing expression profiles of a number of miRNAs or genes are used to identify biomarkers, which have dysregulation in normal and malignant tissues.  ...  In a micro-RNA (miRNA) or gene-expression profiling experiment, the expression levels of thousands of genes/miRNAs are simultaneously monitored to study the effects of certain treatments, diseases, and  ...  Large number of gene expression/miRNA data and their diverse expression patterns indicate that they are likely to be involved in a broad spectrum of human diseases.  ... 
doi:10.1109/jtehm.2014.2375820 pmid:27170887 pmcid:PMC4848046 fatcat:exqtnapsifcb7pla7gclygwfgm

A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network

Erkhembayar Jadamba, Miyoung Shin
2016 BioMed Research International  
expression profiles, and chemical structure data.  ...  Specifically, we first obtain experimental genomic knowledge from disease gene expression profiles and pharmaceutical knowledge from drug phenotype expression profiles and construct a pathway-drug network  ...  Acknowledgments This study was supported by the BK21 Plus project funded by the Ministry of Education, Korea (21A20131600011).  ... 
doi:10.1155/2016/7147039 pmid:28127549 pmcid:PMC5233404 fatcat:duftqnrx4nguzc2nc5upg5dnaa

Accurate Cancer Classification Using Expressions of Very Few Genes

N. Revathy, Dr.R. Amalraj
2011 International Journal of Computer Applications  
Genome-wide expression profiles containing p genes and n samples with every sample subsequent to one of two classes, C 1 , C 2 , the expression of the j th gene in the i th sample is ; 2.  ...  ., [1] proposed a multiclass cancer classification using semisupervised ellipsoid ARTMAP and particle swarm optimization with gene expression data [7, 9] .  ... 
doi:10.5120/1832-2452 fatcat:l5dclyjqozfrnb52fzqv3ly5dq

Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma

Hongjuan Zhao, Börje Ljungberg, Kjell Grankvist, Torgny Rasmuson, Robert Tibshirani, James D Brooks, Francesco Marincola
2005 PLoS Medicine  
Methods and Findings Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays.  ...  We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors.  ...  Acknowledgments The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  ... 
doi:10.1371/journal.pmed.0030013 pmid:16318415 pmcid:PMC1298943 fatcat:mrm33pzdazbcrczvo5eyrqquxu

A combined comparative genomic hybridization and expression microarray analysis of gastric cancer reveals novel molecular subtypes

Su Ting Tay, Siew Hong Leong, Kun Yu, Amit Aggarwal, Soo Yong Tan, Chee How Lee, Keith Wong, Jaya Visvanathan, Dennis Lim, Wai Keong Wong, Khee Chee Soo, Oi Lian Kon (+1 others)
2003 Cancer Research  
We identified a number of novel genomic aberrations associated with gastric cancer and discovered that gastric tumors could be grouped by their expression profiles into three broad classes: "tumorigenic  ...  Comparative genomic hybridization (CGH), microsatellite instability (MSI) assays, and expression microarrays were used to molecularly subclassify a common set of gastric tumor samples.  ...  Research Council and National Cancer Centre for financial support, the Lee Foundation for the purchase of clones, and Pulivarthi Rao for CGH training.  ... 
pmid:12810664 fatcat:daaj75kamvcfnopj7opqj37leu

Interactive Semisupervised Learning for Microarray Analysis

Yijuan Lu, Qi Tian, Feng Liu, Maribel Sanchez, Yufeng Wang
2007 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
However, the discrepancy between the rich expression profiles and the limited knowledge of gene functions has been a major hurdle to the understanding of cellular networks.  ...  Microarray technology has generated vast amounts of gene expression data with distinct patterns.  ...  Tian and US National Institutes of Health (NIH) 1R21AI067543-01A1, San Antonio Area Foundation, and a University of Texas San Antonio Faculty Research Award to Y. Wang. Y.  ... 
doi:10.1109/tcbb.2007.070206 pmid:17473313 fatcat:27wbtrq7nndjlcgwxygri4ucju

Prognostic gene signatures for non-small-cell lung cancer

Paul C. Boutros, Suzanne K. Lau, Melania Pintilie, Ni Liu, Frances A. Shepherd, Sandy D. Der, Ming-Sound Tsao, Linda Z. Penn, Igor Jurisica
2009 Proceedings of the National Academy of Sciences of the United States of America  
A 6-gene signature was identified and validated in 4 independent public microarray datasets that represent a range of tumor histologies and stages.  ...  Molecular classification by using mRNA expression profiles has led to multiple, poorly overlapping signatures.  ...  The 3 omitted studies include 1 where the raw array data has not yet been deposited in a public database (18) and 2 where identifiers to link the expression data to clinical covariates do not appear to  ... 
doi:10.1073/pnas.0809444106 pmid:19196983 pmcid:PMC2636731 fatcat:f6m5h4f52fc5vcbslzex6otqzi

Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization

Yong Liang, Hua Chai, Xiao-Ying Liu, Zong-Ben Xu, Hai Zhang, Kwong-Sak Leung
2016 BMC Medical Genomics  
One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles.  ...  The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets.  ...  Background An important objective of clinical cancer research is to develop tools to accurately predict the survival time and risk profile of patients based on the DNA microarray data and various clinical  ... 
doi:10.1186/s12920-016-0169-6 pmid:26932592 pmcid:PMC4774162 fatcat:2ivzlxzwgnamhlaxrcuy7kjnwi

Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data

Rui Xu, Georgios Anagnostopoulos, Donald Wunsch
2007 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
With the emergence and rapid advancement of DNA microarray technologies, constructing gene expression profiles for different cancer types has already become a promising means for cancer classification.  ...  Here, we use Semisupervised Ellipsoid ARTMAP (ssEAM) for multiclass cancer discrimination and particle swarm optimization for informative gene selection. ssEAM is a neural network architecture rooted in  ...  The authors would also like to thank the associate editor and the anonymous reviewers for their valuable comments.  ... 
doi:10.1109/tcbb.2007.1009 pmid:17277414 fatcat:nifjtrqtoncnzie2m5pexwlsuq

Integrative Gene Network Construction to Analyze Cancer Recurrence Using Semi-Supervised Learning

Chihyun Park, Jaegyoon Ahn, Hyunjin Kim, Sanghyun Park, Peter Csermely
2014 PLoS ONE  
We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs  ...  The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes.  ...  Bair et al. proposed using both available clinical data and gene expression data to identify the subset of the genes used to perform semisupervised clustering [13] .  ... 
doi:10.1371/journal.pone.0086309 pmid:24497942 pmcid:PMC3908883 fatcat:hbraslpwfnehjki5fwqra6wkji

Predicting chemotherapy response using a variational autoencoder approach [article]

Qi Wei, Stephen A Ramsey
2021 bioRxiv   pre-print
(AUROC) classification performance than either the original gene expression profile or the PCA principal components of the gene expression profile, in four out of five cancer types that we tested.  ...  While tumor transcriptome profiles are publicly available for thousands of tumors for many cancer types, a relatively modest number of tumor profiles are clinically annotated for the response to chemotherapy  ...  (A) Original gene expression data of the top 5,000 most variable genes. (B) VAE compressed gene expression data.  ... 
doi:10.1101/2021.01.04.425288 fatcat:33t4tpactbef5oajl4yyd2rb3u
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