research-article

Discretization in gene expression data analysis: a selected survey

Authors:

Priyakshi Mahanta,

Hasin Afzal Ahmed,

Jugal K. Kalita,

Dhruba K. BhattacharyyaAuthors Info & Claims

CCSEIT '12: Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology

Pages 69 - 75

https://doi.org/10.1145/2393216.2393229

Published: 26 October 2012 Publication History

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Abstract

Discretization techniques are widely used as preprocessing task in different classification techniques specially in the area of machine learning. These techniques have also been used as a preprocessing task for computational construction of regulatory networks in gene expression data analysis. We analyze the use of some widely used discretization techniques in other gene expression data analysis tasks such as gene functional prediction. This paper evaluates the performance of these discretization techniques as a preprocessing task by applying the discretized gene expression data on different clustering algorithms. The results generated by the clustering algorithms are internally and externally validated against different discretization techniques. Finally, we introduce some of the important issues and research challenges.

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Esme E(2023)Enhancing classification accuracy through feature extraction: a comparative study of discretization and clustering approaches on sensor-based datasetsKnowledge and Information Systems10.1007/s10115-023-01960-066:1(339-356)Online publication date: 27-Aug-2023
https://doi.org/10.1007/s10115-023-01960-0
Placzek APluciennik AKotecka-Blicharz AJarzab MMrozek D(2020)Bayesian Assessment of Diagnostic Strategy for a Thyroid Nodule Involving a Combination of Clinical Synthetic Features and Molecular DataIEEE Access10.1109/ACCESS.2020.30263158(175125-175139)Online publication date: 2020
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Hayama Nishida CBianchi RReali Costa A(2020)A Framework to Shift Basins of Attraction of Gene Regulatory Networks through Batch Reinforcement LearningArtificial Intelligence in Medicine10.1016/j.artmed.2020.101853(101853)Online publication date: May-2020
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Discretization in gene expression data analysis: a selected survey
1. General and reference
  1. Document types
    1. Surveys and overviews

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Published In

CCSEIT '12: Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology

October 2012

800 pages

ISBN:9781450313100

DOI:10.1145/2393216

General Chairs:
Natarajan Meghanathan
Jackson State University
,
Michal Wozniak
Wroclaw University of Technology, Poland

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Published: 26 October 2012

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CCSEIT '12: The Second International Conference on Computational Science, Engineering

October 26 - 28, 2012

Coimbatore UNK, India

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Esme E(2023)Enhancing classification accuracy through feature extraction: a comparative study of discretization and clustering approaches on sensor-based datasetsKnowledge and Information Systems10.1007/s10115-023-01960-066:1(339-356)Online publication date: 27-Aug-2023
https://doi.org/10.1007/s10115-023-01960-0
Placzek APluciennik AKotecka-Blicharz AJarzab MMrozek D(2020)Bayesian Assessment of Diagnostic Strategy for a Thyroid Nodule Involving a Combination of Clinical Synthetic Features and Molecular DataIEEE Access10.1109/ACCESS.2020.30263158(175125-175139)Online publication date: 2020
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https://doi.org/10.1016/j.artmed.2020.101853
Larmuseau MVerbeke LMarchal K(2019)Associating expression and genomic data using co-occurrence measuresBiology Direct10.1186/s13062-019-0240-214:1Online publication date: 9-May-2019
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Tran BXue BZhang M(2018)A New Representation in PSO for Discretization-Based Feature SelectionIEEE Transactions on Cybernetics10.1109/TCYB.2017.271414548:6(1733-1746)Online publication date: Jun-2018
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Tran BXue BZhang M(2016)Bare-Bone Particle Swarm Optimisation for Simultaneously Discretising and Selecting Features for High-Dimensional ClassificationApplications of Evolutionary Computation10.1007/978-3-319-31204-0_45(701-718)Online publication date: 15-Mar-2016
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Gallo CCecchini RCarballido JMicheletto SPonzoni I(2015)Discretization of gene expression data revisedBriefings in Bioinformatics10.1093/bib/bbv07417:5(758-770)Online publication date: 22-Sep-2015
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Qu JZhang JHuang CXie BWang YZhang X(2013)A novel discretization method for processing digital gene expression profiles2013 7th International Conference on Systems Biology (ISB)10.1109/ISB.2013.6623808(134-138)Online publication date: Aug-2013
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Mahanta PBhattacharyya DGhosh A(2013)A Subspace Module Extraction Technique for Gene Expression DataPattern Recognition and Machine Intelligence10.1007/978-3-642-45062-4_89(635-640)Online publication date: 2013
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Noise-robust algorithm for identifying functionally associated biclusters from gene expression data

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