Assessment of Modeling Techniques and Feature Selection for Predicting Drug Response from Gene Expression Data for Cytotoxic Anticancer Agents

Joshua D. Mannheimer; Ashok Prasad; Dawn L. Duval; Daniel L. Gustafson

doi:10.1096/fasebj.2018.32.1_supplement.566.5

Assessment of Modeling Techniques and Feature Selection for Predicting Drug Response from Gene Expression Data for Cytotoxic Anticancer Agents

The FASEB Journal ◽

10.1096/fasebj.2018.32.1_supplement.566.5 ◽

2018 ◽

Vol 32 (S1) ◽

Author(s):

Joshua D. Mannheimer ◽

Ashok Prasad ◽

Dawn L. Duval ◽

Daniel L. Gustafson

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Anticancer Agents ◽

Drug Response ◽

Expression Data ◽

Modeling Techniques ◽

Selection For

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Feature Selection for Gene Expression Data Analysis – A Review

International Journal of Psychosocial Rehabilitation ◽

10.37200/ijpr/v24i5/pr2020695 ◽

2020 ◽

Vol 24 (5) ◽

pp. 6955-6964

Author(s):

Dr. Prema R

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Data Analysis ◽

Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Selection For

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Optimal feature selection for sparse linear discriminant analysis and its applications in gene expression data

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2013.04.003 ◽

2013 ◽

Vol 66 ◽

pp. 140-149 ◽

Cited By ~ 10

Author(s):

Cheng Wang ◽

Longbing Cao ◽

Baiqi Miao

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Discriminant Analysis ◽

Linear Discriminant Analysis ◽

Gene Expression Data ◽

Expression Data ◽

Linear Discriminant ◽

Optimal Feature Selection ◽

Selection For ◽

Optimal Feature

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Unsupervised Feature Selection for Biomarker Identification in Chromatography and Gene Expression Data

Artificial Neural Networks in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/11829898_25 ◽

2006 ◽

pp. 274-285 ◽

Cited By ~ 1

Author(s):

Marc Strickert ◽

Nese Sreenivasulu ◽

Silke Peterek ◽

Winfriede Weschke ◽

Hans-Peter Mock ◽

...

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Expression Data ◽

Unsupervised Feature Selection ◽

Biomarker Identification ◽

Selection For

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A hybrid filter/wrapper approach of feature selection for gene expression data

2008 IEEE International Conference on Systems, Man and Cybernetics ◽

10.1109/icsmc.2008.4811698 ◽

2008 ◽

Cited By ~ 1

Author(s):

Chao-Hsuan Ke ◽

Cheng-Hong Yang ◽

Li-Yeh Chuang ◽

Cheng-San Yang

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Expression Data ◽

Hybrid Filter ◽

Wrapper Approach ◽

Selection For

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Robust feature selection for high-dimensional and small-sized gene expression data

10.32657/10356/48641 ◽

2011 ◽

Author(s):

Feng Yang

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

High Dimensional ◽

Expression Data ◽

Selection For

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The Painter's Feature Selection for Gene Expression Data

2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/iembs.2007.4353269 ◽

2007 ◽

Cited By ~ 2

Author(s):

Daniele Apiletti ◽

Elena Baralis ◽

Giulia Bruno ◽

Alessandro Fiori

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Expression Data ◽

Selection For

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Multi-Round Random Subspace Feature Selection for Incomplete Gene Expression Data

2019 IEEE Congress on Evolutionary Computation (CEC) ◽

10.1109/cec.2019.8790237 ◽

2019 ◽

Cited By ~ 2

Author(s):

Will Pearson ◽

Cao Truong Tran ◽

Mengjie Zhang ◽

Bing Xue

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Random Subspace ◽

Expression Data ◽

Selection For

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K-Means Clustering with Infinite Feature Selection for Classification Tasks in Gene Expression Data

Advances in Intelligent Systems and Computing - 11th International Conference on Practical Applications of Computational Biology & Bioinformatics ◽

10.1007/978-3-319-60816-7_7 ◽

2017 ◽

pp. 50-57

Author(s):

Muhammad Akmal Remli ◽

Kauthar Mohd Daud ◽

Hui Wen Nies ◽

Mohd Saberi Mohamad ◽

Safaai Deris ◽

...

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Expression Data ◽

Classification Tasks ◽

Selection For

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Variance-based Feature Selection for Classification of Cancer Subtypes Using Gene Expression Data

2018 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2018.8489279 ◽

2018 ◽

Author(s):

Aedan G. K. Roberts ◽

Daniel R. Catchpoole ◽

Paul J. Kennedy

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Expression Data ◽

Cancer Subtypes ◽

Selection For

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PSO based feature selection for clustering gene expression data

2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES) ◽

10.1109/spices.2015.7091510 ◽

2015 ◽

Cited By ~ 3

Author(s):

P S Deepthi ◽

Sabu M Thampi

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Expression Data ◽

Selection For

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