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Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures

Meng P Tan, Erin N Smith, James R Broach, Christodoulos A Floudas
2008 BMC Bioinformatics  
In this study, we describe an iterative clustering approach to uncover biologically coherent structures from DNA microarray data based on a novel clustering algorithm EP_GOS_Clust.  ...  Results: We apply our proposed iterative algorithm to three sets of experimental DNA microarray data from experiments with the yeast Saccharomyces cerevisiae and show that the proposed iterative approach  ...  This work was supported by grants from the National Science Foundation to CAF and JRB, a National Institutes of Health Center of Excellence grant (P50 GM71508), an NIH grant (GM76562) to JRB, and a grant  ... 
doi:10.1186/1471-2105-9-268 pmid:18538024 pmcid:PMC2442101 fatcat:fhq4hvndtbhmbd4w3mbjgqrgqi

DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

Alain B. Tchagang, Ahmed H. Tewfik
2006 EURASIP Journal on Advances in Signal Processing  
coherent values from a set of data in a timely manner and without solving any optimization problem.  ...  Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth.  ...  Therefore, to obtain perfect biclusters with coherent values from a DNA microarray experimental data, one of the following three approaches can be used.  ... 
doi:10.1155/asp/2006/59809 fatcat:oelk6zbuwrfubd33u6dkrix7ye

A review of independent component analysis application to microarray gene expression data

Wei Kong, Charles R. Vanderburg, Hiromi Gunshin, Jack T. Rogers, Xudong Huang
2008 BioTechniques  
As a technique of higher-order statistical analysis, ICA is capable of extracting biologically relevant gene expression features from microarray data.  ...  Independent component analysis (ICA) methods have received growing attention as effective data-mining tools for microarray gene expression data.  ...  and discover novel underlying biological information from large microarray data sets.  ... 
doi:10.2144/000112950 pmid:19007336 pmcid:PMC3005719 fatcat:vcdoxu4ecjginfjj7pkrqvc7v4

A Bayesian Approach to Pathway Analysis by Integrating Gene–Gene Functional Directions and Microarray Data

Yifang Zhao, Ming-Hui Chen, Baikang Pei, David Rowe, Dong-Guk Shin, Wangang Xie, Fang Yu, Lynn Kuo
2011 Statistics in Biosciences  
We propose two novel Bayesian models to integrate the microarray data with the putative pathway structures obtained from the KEGG database and the directional gene-gene interactions in the medical literature  ...  Finally, we apply the methodology to a real microarray data set to understand the gene expression profile of osteoblast lineage at defined stages of differentiation.  ...  by literature mining as in PrimeDB and the microarray gene expression data.  ... 
doi:10.1007/s12561-011-9046-1 pmid:23482678 pmcid:PMC3592971 fatcat:v7cmskovkbho5en4zpep3qmgzm

A Survey of Graph Mining Techniques for Biological Datasets [chapter]

S. Parthasarathy, S. Tatikonda, D. Ucar
2010 Managing and Mining Graph Data  
Mining structured information has been the source of much research in the data mining community over the last decade.  ...  Examples abound ranging from the analysis of protein interaction networks to the analysis of phylogenetic data.  ...  Acknowledgments The authors wish to acknowledge the support of NSF CAREER Grant IIS-0347662.  ... 
doi:10.1007/978-1-4419-6045-0_18 dblp:series/ads/ParthasarathyTU10 fatcat:aeu53r3dbzd67d5whkjypv64uq

Review on Analysis of Gene Expression Data Using Biclustering Approaches

S. Anitha, Dr.C.P. Chandran
2016 Bonfring International Journal of Data Mining  
In this paper, survey on biclustering approaches for Gene Expression Data (GED) is carried out. Some of the issues are Correlation, Class discovery, Coherent biclusters and coregulated biclusters.  ...  Given a gene expression data matrix D=G×C= {d  ...  Gaurav Pandey [40] saved that a novel association analysis framework for exhaustively and efficiently mining "range support" patterns from such a data set.  ... 
doi:10.9756/bijdm.8135 fatcat:xuv25tllmzd3zljhedg7dvrhjy

An association analysis approach to biclustering

Gaurav Pandey, Gowtham Atluri, Michael Steinbach, Chad L. Myers, Vipin Kumar
2009 Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '09  
In this paper, we propose a novel association analysis framework for exhaustively and efficiently mining "range support" patterns from such a data set.  ...  On one hand, this framework reduces the loss of information incurred by the binarization-and discretization-based approaches, and on the other, it enables the exhaustive discovery of coherent biclusters  ...  Some approaches have also been proposed to mine association patterns directly from real-valued data [18, 35, 16] .  ... 
doi:10.1145/1557019.1557095 dblp:conf/kdd/PandeyASMK09 fatcat:bhdjbzfvg5dhrb4mm6wbfixuja

Hierarchical Biological Pathway Data Integration and Mining [chapter]

Shubhalaxmi Kher, Jianling Peng, Eve Syrkin, Julie Dickerso
2012 Bioinformatics  
M@cBETH (2005) (a Microarray Classification Benchmarking Tool on a host server):Web service offers the microarray community a simple tool for making optimal two class predictions.  ...  Some conventional bioinformatics approaches identify hypothetical interactions between proteins based on their three dimensional structures or by applying text mining techniques.  ... 
doi:10.5772/49974 fatcat:wo3ris5q5vfdjjdloan7phhche

Gene mining: a novel and powerful ensemble decision approach to hunting for disease genes using microarray expression profiling

X. Li
2004 Nucleic Acids Research  
An application of this approach to analyze two publicly available data sets (colon data and leukemia data) identi®ed 20 highly signi®cant colon cancer genes and 23 highly signi®cant molecular signatures  ...  Furthermore, the globally optimal gene subsets identi®ed by the novel approach have so far achieved the highest accuracy for classi®cation of colon cancer tissue types.  ...  a data structure.  ... 
doi:10.1093/nar/gkh563 pmid:15148356 pmcid:PMC419591 fatcat:dujbxj2p3bbsfi3nsatsogmwo4

Novel Data Mining Techniques in aCGH based Breast Cancer Subtypes Profiling: the Biological Perspective

F. Menolascina, S. Tommasi, A. Paradiso, M. Cortellino, V. Bevilacqua, G. Mastronardi
2007 2007 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology  
In this paper we present a comparative study among well established data mining algorithm (namely J48 and Naïve Bayes Tree) and novel machine learning paradigms like Ant Miner and Gene Expression Programming  ...  Results returned by this approach seem to encourage new efforts in this field.  ...  Novel biologically inspired data mining techniques, then, seem to be competitive complementary tools in cancer research being GEP, probably, the less explored.  ... 
doi:10.1109/cibcb.2007.4221198 fatcat:mhazk5h56vaypcj4obaheua43m

Mining gene expression data by interpreting principal components

Joseph C Roden, Brandon W King, Diane Trout, Ali Mortazavi, Barbara J Wold, Christopher E Hart
2006 BMC Bioinformatics  
To enable easy use of our methods, we have developed a data analysis package that facilitates visualization and subsequent data mining of the independent sources of significant variation present in gene  ...  In test uses, this method, based on publicly available gene annotations, appears to identify numerous sets of biologically relevant genes.  ...  We acknowledge that the GNF gene microarray expression data presented herein was obtained from Genomics Institute of the Novartis Research Foundation, and is © 2003-2005 GNF.  ... 
doi:10.1186/1471-2105-7-194 pmid:16600052 pmcid:PMC1501050 fatcat:h63adj2jdrguzf72xtu7uhxi24

Dual activation of pathways regulated by steroid receptors and peptide growth factors in primary prostate cancer revealed by Factor Analysis of microarray data

Juan Jose Lozano, Marta Soler, Raquel Bermudo, David Abia, Pedro L Fernandez, Timothy M Thomson, Angel R Ortiz
2005 BMC Genomics  
We use an approach based on Factor Analysis to analyze datasets generated for transcriptional profiling.  ...  We tested the approach with a published dataset of microarray experiments in yeast. Upon validation with the yeast dataset, we applied the technique to a prostate cancer dataset.  ...  JJL was partly supported by a NATO postdoctoral fellowship.  ... 
doi:10.1186/1471-2164-6-109 pmid:16107210 pmcid:PMC1239914 fatcat:4sq7yv6zdnadzn4zjdjhmuicbu

A Novel Clustering Approach: Global Optimum Search with Enhanced Positioning [chapter]

Meng Piao Tan, Christodoulos A. Floudas
2009 Clustering Challenges in Biological Networks  
We also propose an extension to iteratively uncover the optimal biologically coherent structures.  ...  Cluster analysis of DNA expression data is a useful tool for identifying biologically relevant gene groupings.  ...  Conclusions In our study, we propose a novel clustering algorithm (EP_GOS_Clust) based on an MINLP formulation, and apply a novel decomposition technique to solve the MINLP optimization problem.  ... 
doi:10.1142/9789812771667_0016 fatcat:fp32eh6st5bz5k3ccnvlornj2e

Frequent pattern mining: current status and future directions

Jiawei Han, Hong Cheng, Dong Xin, Xifeng Yan
2007 Data mining and knowledge discovery  
However, there are still some challenging research issues that need to be solved before frequent pattern mining can claim a cornerstone approach in data mining applications.  ...  Frequent pattern mining has been a focused theme in data mining research for over a decade.  ...  Zhu et al. (2007) investigated a novel mining approach, called Pattern-Fusion, to efficiently find a good approximation to colossal patterns.  ... 
doi:10.1007/s10618-006-0059-1 fatcat:fpblaafhurfbtiimurret4idde

Query-based Biclustering using Formal Concept Analysis [chapter]

Faris Alqadah, Joel S. Bader, Rajul Anand, Chandan K. Reddy
2012 Proceedings of the 2012 SIAM International Conference on Data Mining  
Our novel approach provides a mechanism to generalize query-based biclustering to sparse high-dimensional data such as information networks and bag of words.  ...  To this end, query-based biclustering algorithms that are recently developed in the context of microarray data utilize a set of seed genes provided by the user which are assumed to be tightly co-expressed  ...  A novel formulation of query-based biclustering is proposed, in this paper, to generalize previous approaches to sparse and very high-dimensional data.  ... 
doi:10.1137/1.9781611972825.56 dblp:conf/sdm/AlqadahBAR12 fatcat:pijhjy6gdbhhnlb6dxrtg55gfi
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