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Network neighborhood analysis with the multi-node topological overlap measure

A. Li, S. Horvath
2006 Bioinformatics  
Availability: A executable Windows program and tutorial for multinode topological overlap measure (MTOM) based analysis can be downloaded from the following webpage:  ...  Since the use of multiple nodes in the seed set may lead to more informative neighborhoods, it can be advantageous to define multi-node similarity measures.  ...  ACKNOWLEDGMENT The authors would like to thank our collaborators Jun Dong, Dan Geschwind, Peter Langfelder, Jake Lusis, Paul Mischel, Stan Nelson, Mike Oldham, Anja Presson, Lin Wang and Wei Zhao.  ... 
doi:10.1093/bioinformatics/btl581 pmid:17110366 fatcat:zfyfdyvggvcodcslfl3brnoegi

Network module detection: Affinity search technique with the multi-node topological overlap measure

Ai Li, Steve Horvath
2009 BMC Research Notes  
In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis.  ...  Findings: We adapt network neighborhood analysis for the use of module detection.  ...  The authors would like to thank UCLA collaborators Peter Langfelder, Jun Dong, Tova Fuller, Jake Lusis, Tom Drake, Dan Geschwind, Wen Lin, Paul Mischel, Mike Oldham, Anja Presson, and Wei Zhao for useful  ... 
doi:10.1186/1756-0500-2-142 pmid:19619323 pmcid:PMC2727520 fatcat:csncrstb7nahbjwsi2646wepza

Gene network interconnectedness and the generalized topological overlap measure

Andy M Yip, Steve Horvath
2007 BMC Bioinformatics  
For example, the topological overlap measure by Ravasz et al. [1] can be interpreted as a measure of agreement between the m = 1 step neighborhoods of 2 nodes.  ...  Results: We generalize the topological overlap measure from m = 1 step neighborhoods to m ≥ 2 step neighborhoods.  ...  Acknowledgements The authors would like to thank Marc Carlson, Jun Dong, Dan Geschwind, Peter Langfelder, Ai Li, Paul Mischel, Stan Nelson, Mike Oldham, Anja Presson for helpful comments.  ... 
doi:10.1186/1471-2105-8-22 pmid:17250769 pmcid:PMC1797055 fatcat:i36lg3rhafgj3msrkuvbg5p5la

Detecting recurrent gene mutation in interaction network context using multi-scale graph diffusion

Sepideh Babaei, Marc Hulsman, Marcel Reinders, Jeroen de Ridder
2013 BMC Bioinformatics  
Importantly, the putative cancer genes and networks detected in this study are found to be significant at different diffusion scales, confirming the necessity of a multi-scale analysis.  ...  Using multi-scale diffusion kernel, various infrequently mutated genes are found to harbor significant numbers of mutations in their interaction network neighborhood.  ...  Acknowledgements This work is part of the BioRange program of the Netherlands Bioinformatics Centre (NBIC), which is supported by the Netherlands Genomics Initiative (NGI).  ... 
doi:10.1186/1471-2105-14-29 pmid:23343428 pmcid:PMC3626877 fatcat:iioqaeqkcjgz3clevuglngz5su

Multi-relational Link Prediction in Heterogeneous Information Networks

Darcy Davis, Ryan Lichtenwalter, Nitesh V. Chawla
2011 2011 International Conference on Advances in Social Networks Analysis and Mining  
In this paper, we introduce a novel probabilistically weighted extension of the Adamic/Adar measure for heterogenous information networks, which we use to demonstrate the potential benefits of diverse  ...  Link prediction in such networks must model the influences between heterogenous relationships and distinguish the formation mechanisms of each link type, a task which is beyond the simple topological features  ...  The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.  ... 
doi:10.1109/asonam.2011.107 dblp:conf/asunam/DavisLC11 fatcat:vcvyjqrzgjg3jkdyxzea6a67ka

Systematic Functional Annotation and Visualization of Biological Networks

Anastasia Baryshnikova
2016 Cell Systems  
This method, named Spatial Analysis of Functional Enrichment (SAFE), detects network regions that are statistically overrepresented for a functional group or a quantitative phenotype of interest, and provides  ...  These results demonstrate that SAFE is a powerful new tool for examining biological networks and advancing our understanding of the functional organization of the cell.  ...  (G) Analysis of the overlap between the SAFE-based and the manual (Costanzo et al., 2010) annotations of the network. Significance of overlap was measured by Fisher's exact test.  ... 
doi:10.1016/j.cels.2016.04.014 pmid:27237738 fatcat:tqswfbzplrgzvf5douepdcaaaa

Systematic Functional Annotation and Visualization of Biological Networks [article]

Anastasia Baryshnikova
2015 bioRxiv   pre-print
This method, named Spatial Analysis of Functional Enrichment (SAFE), detects network regions that are statistically overrepresented for a functional group or a quantitative phenotype of interest, and provides  ...  These results demonstrate that SAFE is a powerful new tool for examining biological networks and advancing our understanding of the functional organization of the cell.  ...  (G) Analysis of the overlap between the SAFE-based and the manual (Costanzo et al., 2010) annotations of the network. Significance of overlap was measured by Fisher's exact test.  ... 
doi:10.1101/030551 fatcat:kynvgewhbbdhpmoqbhahahluyq

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells

F. Alexander Wolf, Fiona K. Hamey, Mireya Plass, Jordi Solana, Joakim S. Dahlin, Berthold Göttgens, Nikolaus Rajewsky, Lukas Simon, Fabian J. Theis
2019 Genome Biology  
PAGA maps preserve the global topology of data, allow analyzing data at different resolutions, and result in much higher computational efficiency of the typical exploratory data analysis workflow.  ...  We demonstrate the method by inferring structure-rich cell maps with consistent topology across four hematopoietic datasets, adult planaria and the zebrafish embryo and benchmark computational performance  ...  PAGA's multi-resolution capabilities directly address the typical practice of exploratory data analysis, in particular for single-cell data: data is typically reclustered in certain regions where a higher  ... 
doi:10.1186/s13059-019-1663-x pmid:30890159 pmcid:PMC6425583 fatcat:vn5exscyl5bhxevezn2kvsymiu

An integrative approach for a network based meta-analysis of viral RNAi screens

Sandeep S Amberkar, Lars Kaderali
2015 Algorithms for Molecular Biology  
However, the analysis of data resulting from such screens is difficult, with often low overlap between hit lists, even when comparing screens targeting the same virus.  ...  Modules passing all these criteria are finally interpreted for their biological significance using enrichment analysis, and interesting candidate genes can be selected from the modules.  ...  Kiani as well as two anonymous referees for useful comments and suggestions.  ... 
doi:10.1186/s13015-015-0035-7 pmid:25691914 pmcid:PMC4331137 fatcat:yr52jlxahvcg3ct5whkjtkywze

Identification of protein complexes from multi-relationship protein interaction networks

Xueyong Li, Jianxin Wang, Bihai Zhao, Fang-Xiang Wu, Yi Pan
2016 Human Genomics  
PPI network topology with gene ontology annotation information.  ...  Considering that the influences of different types of interactions are not the same weight for protein complex prediction, we construct a multi-relationship protein interaction network (MPIN) by integrating  ...  Acknowledgements This work is supported in part by the National Natural Science Foundation of China under Grant No. 61472133, No. 31560317, and No. 61428209  ... 
doi:10.1186/s40246-016-0069-z pmid:27461193 pmcid:PMC4965713 fatcat:nv2rklkfqjdkrfex5jaktowecy

Using Self-Organizing Maps to Visualize, Filter and Cluster Multidimensional Bio-Omics Data [chapter]

Ji Zhang, Hai Fang
2012 Applications of Self-Organizing Maps  
The self-organizing map (SOM), as a learning algorithm [16] , appears to be suitable for topology-preserving analysis of multi-dimensional data.  ...  For the temporal change measure, the dominant eigenvectors identified by SOM-SVD analysis can be used (top-left corner).  ... 
doi:10.5772/51702 fatcat:ic6d6rurcbf73ldmj56iioo6ca

Mapping Condition-Dependent Regulation of Lipid Metabolism in Saccharomyces cerevisiae

Michael C. Jewett, Christopher T. Workman, Intawat Nookaew, Francisco A. Pizarro, Eduardo Agosin, Lars I. Hellgren, Jens Nielsen
2013 G3: Genes, Genomes, Genetics  
Correlation analysis across eight environmental conditions revealed 2279 gene expression level-metabolite/lipid relationships that characterize the extent of transcriptional regulation in lipid metabolism  ...  To query this network, we developed integrative methods for correlation of multi-omics datasets that elucidate global regulatory signatures.  ...  Gray indicates the lack of a measurement for that node.  ... 
doi:10.1534/g3.113.006601 pmid:24062529 pmcid:PMC3815060 fatcat:cqia4r6mhjerjaune3ek6kcxsi

WGCNA: an R package for weighted correlation network analysis

Peter Langfelder, Steve Horvath
2008 BMC Bioinformatics  
For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples.  ...  Conclusion: The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data.  ...  The work was supported in part by grants P50CA092131, 5P30CA016042-28, and NS050151-01.  ... 
doi:10.1186/1471-2105-9-559 pmid:19114008 pmcid:PMC2631488 fatcat:wbkhvqxm2napppgmaxin66upgm

Supervised methods for multi-relational link prediction

Darcy Davis, Ryan Lichtenwalter, Nitesh V. Chawla
2012 Social Network Analysis and Mining  
In this paper, we introduce a novel probabilistically weighted extension of the Adamic/Adar measure for heterogenous information networks, which we use to demonstrate the potential benefits of diverse  ...  Link prediction in such networks must model the influences between heterogenous relationships and distinguish the formation mechanisms of each link type, a task which is beyond the simple topological features  ...  The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.  ... 
doi:10.1007/s13278-012-0068-6 fatcat:mvqo6so5rnbbhcj6nsyq6humfu

Uncovering disease-disease relationships through the incomplete interactome

J. Menche, A. Sharma, M. Kitsak, S. D. Ghiassian, M. Vidal, J. Loscalzo, A.-L. Barabasi
2015 Science  
on the network methods and Gabriele Musella for figure design.  ...  Acknowledgments The authors would like to thank Anne-Ruxandra Carvunis, Sam Pevzner, and Thomas Rolland for providing invaluable insights into the y2h dataset, Jim Bagrow and Filippo Simini for many discussions  ...  Both measures lie in the range [0,1] with J,C = 0 for no common genes.  ... 
doi:10.1126/science.1257601 pmid:25700523 pmcid:PMC4435741 fatcat:o6sil3xhqvcfbgkzjkuo6mu3yy
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