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Model based essential interactions cluster mining in multivariate time

V. Saravanan, S. Chitra
2014 International Conference on Information Communication and Embedded Systems (ICICES2014)  
The Essential clusters (EC) are then clustered again based on their dependencies on various brain regions. These EC's are grouped under specific models.  ...  The changes detected are mined based on the type of cluster grouped under a certain model.  ...  interaction patterns among brain regions using essential clustering, fast mining and easy to identify Disorders.  ... 
doi:10.1109/icices.2014.7033932 fatcat:d7sb26flafbbvagz7v6eopqzoy


1956 American Journal of Psychiatry  
To understand the complex interaction patterns among brain regions our system proposes a novel clustering technique.  ...  Handling of feature selection and clustering is a complicated process in Interaction patterns of brain datasets.  ...  INTRODUCTION Feature selection for interaction based clustering in interaction patterns among brain images by using feature subset selection algorithm.  ... 
doi:10.1176/ajp.113.2.138 pmid:13340014 fatcat:s7xwe3vt5bcblon3znj7nw6yxu

Identification of the Bona fide Differentially Methylated Gene Markers among Cancers

Hongbo Liu, Zhe Li, Jing Ding, Jie Liu, Yan Zhang
2013 Computational Molecular Biology  
In the end, we identified potential cancer-related genes by extracting protein interaction sub-network.  ...  This study provides a new framework for mining the potential cancer-specific methylation markers and oncogenes.  ...  The hierarchical clustering in all 297 samples shows the similar methylation pattern among the samples representing the same tissue or cancer.  ... 
doi:10.5376/cmb.2013.03.0002 fatcat:57etp3clqbdqfoxpk6bsxds5xq

A review of heterogeneous data mining for brain disorder identification

Bokai Cao, Xiangnan Kong, Philip S. Yu
2015 Brain Informatics  
Furthermore, brain connectivity networks can be constructed from the tensor data, embedding subtle interactions between brain regions.  ...  They have achieved great success in various applications, such as tensor-based modeling, subgraph pattern mining, and multi-view feature analysis.  ...  Acknowledgments This work is supported in part by NSF through grants III-1526499, CNS-1115234, and OISE-1129076, and Google Research Award.  ... 
doi:10.1007/s40708-015-0021-3 pmid:27747561 pmcid:PMC4883173 fatcat:rhvqh4vmeffnnoxts7esxwxlsq

A review of heterogeneous data mining for brain disorders [article]

Bokai Cao, Xiangnan Kong, Philip S. Yu
2015 arXiv   pre-print
Furthermore, brain connectivity networks can be constructed from the tensor data, embedding subtle interactions between brain regions.  ...  They have achieved great success in various applications, such as tensor-based modeling, subgraph pattern mining, multi-view feature analysis.  ...  A subgraph pattern, in a brain network, represents a collection of brain regions and their connections.  ... 
arXiv:1508.01023v1 fatcat:e6nscurzmbc23f26p2q42ccbrm

Page 2259 of The Journal of Neuroscience Vol. 25, Issue 9 [page]

2005 The Journal of Neuroscience  
Nucleus accumbens This brain region showed complex ethanol-responsive patterns with multiple clusters of genes (Fig. 4, clusters 3, 7, 6, 8, 11).  ...  . @ Brain Region Ethanol Expression Networks 70) © Up-regulated ™ Down-regulated 60 - Number of Genes Figure 3. Number of ethanol-regulated genes by mouse strain and brain region.  ... 

Spatio-Temporal Data Mining: A Survey of Problems and Methods [article]

Gowtham Atluri, Anuj Karpatne, Vipin Kumar
2017 arXiv   pre-print
Based on the nature of the data mining problem studied, we classify literature on spatio-temporal data mining into six major categories: clustering, predictive learning, change detection, frequent pattern  ...  mining, anomaly detection, and relationship mining.  ...  ., a memory task), the similarity structure among the time-series at brain regions could be different.  ... 
arXiv:1711.04710v2 fatcat:di3fxigwobeb3db5kcdvlhbe7i

Visual Systems for Interactive Exploration and Mining of Large-Scale Neuroimaging Data Archives

Ian Bowman, Shantanu H. Joshi, John D. Van Horn
2012 Frontiers in Neuroinformatics  
Using a collection of cortical surface metrics and means for examining brain similarity, INVIZIAN graphically displays brain surfaces as points in a coordinate space and enables classification of clusters  ...  As an initial step toward addressing the need for such user-friendly tools, INVIZIAN provides a highly unique means to interact with large quantities of electronic brain imaging archives in ways suitable  ...  ACKNOWLEDGMENTS This work is supported in part by NIH grants RC1 MH088194 and P41 RR013642.  ... 
doi:10.3389/fninf.2012.00011 pmid:22536181 pmcid:PMC3332235 fatcat:c3mgktgsj5hunlloxunizevqxm

Identification of a set of genes showing regionally enriched expression in the mouse brain

Cletus A D'Souza, Vikramjit Chopra, Richard Varhol, Yuan-Yun Xie, Slavita Bohacec, Yongjun Zhao, Lisa LC Lee, Mikhail Bilenky, Elodie Portales-Casamar, An He, Wyeth W Wasserman, Daniel Goldowitz (+4 others)
2008 BMC Neuroscience  
in a similar pattern in the mouse brain.  ...  These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region.  ...  This pattern of tissue clustering appears to be borne out by unique tissue composition at the very least.  ... 
doi:10.1186/1471-2202-9-66 pmid:18625066 pmcid:PMC2483290 fatcat:5r5ymliktbg7zcszwsq3amd7ti

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network

Hao Guo, Mengna Qin, Junjie Chen, Yong Xu, Jie Xiang
2017 Computational and Mathematical Methods in Medicine  
High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions.  ...  Accordingly, such networks are widely used to classify brain diseases.  ...  Acknowledgments This study was supported by research grants from the National Natural Science Foundation of China (61373101, 61472270, 61402318, and 61672374), the Natural Science Foundation of Shanxi  ... 
doi:10.1155/2017/4820935 pmid:29387141 pmcid:PMC5745775 fatcat:tiqznr2dd5awtjjjodwno376h4

Image mining framework and techniques: a review

Nilanjan Dey, Wahiba Ben Abdessalem Karâa, Sayan Chakraborty, Sukanya Banerjee, Mohammed A.M. Salem, Ahmad Taher Azar
2015 International Journal of Image Mining  
The image mining technique can extract knowledge and exciting patterns which are not stored in the database by analysing the images using various tools.  ...  Image mining refers to a data mining technique where images are used as data.  ...  Image indexing handles data and images in region, objects and visual patterns level.  ... 
doi:10.1504/ijim.2015.070028 fatcat:kszujsxburaxxkbqjeh5gwbmbi

Combining Multiple Network Features for Mild Cognitive Impairment Classification

Lipeng Wang, Fei Fei, Biao Jie, Daoqiang Zhang
2014 2014 IEEE International Conference on Data Mining Workshop  
., the correlation between paired brain regions), which can not fully reflect the topological information among multiple brain regions.  ...  Specifically, two different types of network features (i.e., brain region and subgraph) are respectively used to quantify two different properties of networks, where two kinds of feature selection methods  ...  And this paper is supported by National Natural Science  ... 
doi:10.1109/icdmw.2014.98 dblp:conf/icdm/WangFJZ14 fatcat:aowjofxitbhqrjepkl2eyndmsm

Change Detection and Visualization of Functional Brain Networks using EEG Data

R. Vijayalakshmi, Naga Dasari, D. Nandagopal, R. Subhiksha, Bernie Cocks, Nabaraj Dahal, M. Thilaga
2014 Procedia Computer Science  
Mining dynamic and non-trivial patterns of interactions of functional brain networks has gained significance due to the recent advances in the field of computational neuroscience.  ...  neuronal patterns during various states of the brain activity using augmented/customised Topoplots and Headplots.  ...  It shows a clear distinction among the brain regions surrounded by Fz, F4, and Fcz.  ... 
doi:10.1016/j.procs.2014.05.060 fatcat:ovdffytktvh4deopkpda2axkia

Microglial brain region−dependent diversity and selective regional sensitivities to aging

Kathleen Grabert, Tom Michoel, Michail H Karavolos, Sara Clohisey, J Kenneth Baillie, Mark P Stevens, Tom C Freeman, Kim M Summers, Barry W McColl
2016 Nature Neuroscience  
Immune function correlated with regional transcriptional patterns.  ...  Augmentation of the distinct cerebellar immunophenotype and a contrasting loss in distinction of the hippocampal phenotype among forebrain regions were key features during ageing.  ...  an interaction between age and brain region (Fig 7b) .  ... 
doi:10.1038/nn.4222 pmid:26780511 pmcid:PMC4768346 fatcat:l5hhtjckibhvbgxgti3mrc45d4

Big Data and Causality

Hossein Hassani, Xu Huang, Mansi Ghodsi
2017 Annals of Data Science  
Specific Tested Subjects&Regions Purpose and Function Entity Extraction [22-25, 27, 29, 31-42, 48-54, 56-59, 61] lexico-syntactic patterns discovery, ambiguous patterns ranking by semantic constraints,  ...  Data Mining, the process of uncovering hidden information from Big Data is now an important tool for causality analysis, and has been extensively exploited by scholars around the world.  ...  relationship among regions.  ... 
doi:10.1007/s40745-017-0122-3 fatcat:y5fixid4ujgsjlgrcfceq5nosu
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