Optimization models for cancer classification: extracting gene interaction information from microarray expression data

Bioinformatics ◽

10.1093/bioinformatics/btg462 ◽

2004 ◽

Vol 20 (5) ◽

pp. 644-652 ◽

Author(s):

A. V. Antonov ◽

I. V. Tetko ◽

M. T. Mader ◽

J. Budczies ◽

H. W. Mewes

Keyword(s):

Gene Interaction ◽

Cancer Classification ◽

Optimization Models ◽

Expression Data ◽

Interaction Information ◽

Microarray Expression Data ◽

Microarray Expression

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Correlated Discretized Expression Score: A Method for Identifying Gene Interaction Networks from Time Course Microarray Expression Data

2006 International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/iembs.2006.259256 ◽

2006 ◽

Author(s):

Peter Larsen ◽

Eyad Almasri ◽

Guanrao Chen ◽

Yang Dai

Keyword(s):

Time Course ◽

Gene Interaction ◽

Interaction Networks ◽

Expression Data ◽

Microarray Expression Data ◽

Gene Interaction Networks ◽

Microarray Expression ◽

Expression Score

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Ensemble feature selection for stable biomarker identification and cancer classification from microarray expression data

Computers in Biology and Medicine ◽

10.1016/j.compbiomed.2021.105208 ◽

2022 ◽

pp. 105208

Author(s):

Aiguo Wang ◽

Huanchen Liu ◽

Jing Yang ◽

Guilin Chen

Keyword(s):

Feature Selection ◽

Cancer Classification ◽

Expression Data ◽

Biomarker Identification ◽

Microarray Expression Data ◽

Selection For ◽

Microarray Expression

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Informative Gene Discovery for Cancer Classification from Microarray Expression Data

2005 IEEE Workshop on Machine Learning for Signal Processing ◽

10.1109/mlsp.2005.1532935 ◽

2006 ◽

Author(s):

Manfred Ng ◽

Laiwan Chan

Keyword(s):

Gene Discovery ◽

Cancer Classification ◽

Expression Data ◽

Informative Gene ◽

Microarray Expression Data ◽

Microarray Expression

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Feature Selection for Cancer Classification on Microarray Expression Data

2008 Eighth International Conference on Intelligent Systems Design and Applications ◽

10.1109/isda.2008.198 ◽

2008 ◽

Author(s):

Hui-Huang Hsu ◽

Ming-Da Lu

Keyword(s):

Feature Selection ◽

Cancer Classification ◽

Expression Data ◽

Microarray Expression Data ◽

Selection For ◽

Microarray Expression

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Correlated Discretized Expression Score: A Method for Identifying Gene Interaction Networks from Time Course Microarray Expression Data

2006 International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/iembs.2006.4398786 ◽

2006 ◽

Author(s):

Peter Larsen ◽

Eyad Almasri ◽

Guanrao Chen ◽

Yang Dai

Keyword(s):

Time Course ◽

Gene Interaction ◽

Interaction Networks ◽

Expression Data ◽

Microarray Expression Data ◽

Gene Interaction Networks ◽

Microarray Expression ◽

Expression Score

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Granular SVM-RFE Gene Selection Algorithm for Reliable Prostate Cancer Classification on Microarray Expression Data

Fifth IEEE Symposium on Bioinformatics and Bioengineering (BIBE'05) ◽

10.1109/bibe.2005.34 ◽

2006 ◽

Author(s):

Yuchun Tang ◽

Yan-Qing Zhang ◽

Zhen Huang ◽

Xiaohua Hu

Keyword(s):

Prostate Cancer ◽

Gene Selection ◽

Cancer Classification ◽

Expression Data ◽

Selection Algorithm ◽

Microarray Expression Data ◽

Microarray Expression ◽

Gene Selection Algorithm ◽

Prostate Cancer Classification

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Faculty Opinions recommendation of A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1162449.623967 ◽

2009 ◽

Author(s):

Nicola Mulder

Keyword(s):

Meta Analysis ◽

Expression Data ◽

Microarray Expression Data ◽

Gene Functions ◽

Unknown Gene ◽

Microarray Expression

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An empirical study of supervised learning for biological sequence profiling and microarray expression data analysis

2008 IEEE International Conference on Information Reuse and Integration ◽

10.1109/iri.2008.4583007 ◽

2008 ◽

Author(s):

Abu H. M. Kamal ◽

Xingquan Zhu ◽

Abhijit S. Pandya ◽

Sam Hsu ◽

Yong Shi

Keyword(s):

Data Analysis ◽

Empirical Study ◽

Supervised Learning ◽

Expression Data ◽

Biological Sequence ◽

Microarray Expression Data ◽

Microarray Expression

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LipGene: Lipschitz continuity guided adaptive learning rates for fast convergence on Microarray Expression Data Sets

IEEE/ACM Transactions on Computational Biology and Bioinformatics ◽

10.1109/tcbb.2021.3110516 ◽

2021 ◽

pp. 1-1

Author(s):

Tejas Prashanth ◽

Snehanshu Saha ◽

Sumedh Basarkod ◽

Suraj Aralihalli ◽

Soma S Dhavala ◽

...

Keyword(s):

Adaptive Learning ◽

Lipschitz Continuity ◽

Fast Convergence ◽

Data Sets ◽

Expression Data ◽

Microarray Expression Data ◽

Learning Rates ◽

Microarray Expression

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Finite mixture model analysis of microarray expression data on samples of uncertain biological type with application to reproductive efficiency

Veterinary Immunology and Immunopathology ◽

10.1016/j.vetimm.2005.02.008 ◽

2005 ◽

Vol 105 (3-4) ◽

pp. 187-196 ◽

Author(s):

Nan Bing ◽

Ina Hoeschele ◽

Keying Ye ◽

Kenneth J. Eilertsen

Keyword(s):

Mixture Model ◽

Finite Mixture Model ◽

Model Analysis ◽

Finite Mixture ◽

Reproductive Efficiency ◽

Expression Data ◽

Microarray Expression Data ◽

Microarray Expression

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