Filters








3,146 Hits in 4.5 sec

Protein subnetwork markers improve prediction of cancer outcome

Charles Auffray
2007 Molecular Systems Biology  
Gene expression profiles from metastatic and nonmetastatic tumor sample are overlayed onto a protein-protein interaction network.  ...  The novel strategy described by Trey Ideker and co-workers (Chuang et al, 2007) is based on the identification of protein interaction subnetworks with coherent expression patterns of their component  ... 
doi:10.1038/msb4100183 pmid:17940531 pmcid:PMC2063583 fatcat:uh5iudeflza73p3ctkrrpmjrti

GSNFS: Gene subnetwork biomarker identification of lung cancer expression data

Narumol Doungpan, Worrawat Engchuan, Jonathan H. Chan, Asawin Meechai
2016 BMC Medical Genomics  
In addition, using pathway data and protein-protein interaction as network data in order to consider the interaction among significant genes were discussed.  ...  Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account  ...  Availability of data and materials Data analyzed and the source code for the GSNFS can be accessed by request to the author.  ... 
doi:10.1186/s12920-016-0231-4 pmid:28117655 pmcid:PMC5260788 fatcat:4lrutmzwyzgjzp4c6bvrwrlukq

Identification of differentially expressed sub-networks based on multivariate ANOVA scoring method

Taeyoung Hwang, Taesung Park
2009 BMC Bioinformatics  
Since high-throughput protein-protein interaction (PPI) data has recently become available for humans, there has been a growing interest in combining PPI data with other genomewide data.  ...  In particular, the identification of phenotype-related PPI subnetworks using gene expression data has been of great concern.  ...  This work was supported by the National Research Laboratory Program of the Korea Science and Engineering Foundation (M10500000126) and a fellowship for a Seoul citizen in Science.  ... 
doi:10.1186/1471-2105-10-128 pmid:19405941 pmcid:PMC2696448 fatcat:rrzftfcu6fhwvgoq6yptglpsxu

Identifying protein interaction subnetworks by a bagging Markov random field-based method

Li Chen, Jianhua Xuan, Rebecca B. Riggins, Yue Wang, Robert Clarke
2012 Nucleic Acids Research  
Identification of differentially expressed subnetworks from protein-protein interaction (PPI) networks has become increasingly important to our global understanding of the molecular mechanisms that drive  ...  To improve their robustness across data sets, a bagging scheme based on bootstrapping samples is implemented to statistically select high confidence subnetworks.  ...  Figure 1 . 1 Framework of BMRF-based subnetwork identification from microarray gene expression profiles and PPI network. (34) by the BMRF-based method.  ... 
doi:10.1093/nar/gks951 pmid:23161673 pmcid:PMC3553975 fatcat:a5ohkvzofvajlfioe6jcow6hou

Comparison of statistical methods for subnetwork detection in the integration of gene expression and protein interaction network

Hao He, Dongdong Lin, Jigang Zhang, Yu-ping Wang, Hong-wen Deng
2017 BMC Bioinformatics  
Results: First, taking into account the dependence of genes given a protein-protein interaction (PPI) network, we simulated microarray gene expression data under case and control conditions.  ...  Then each method was applied to the simulated data for subnetwork identification. Second, a large microarray data set of prostate cancer was used to assess the practical performance of each method.  ...  Bagging Markov random field (BMRF) approach is a BMRF-based method for subnetwork identification in the integration PPI data and microarray data with two different phenotypes (case/control).  ... 
doi:10.1186/s12859-017-1567-2 pmid:28253853 pmcid:PMC5335754 fatcat:mgxsvtgaxzgldkyzqq6b3ifivy

Identification of Interconnected Markers for T-Cell Acute Lymphoblastic Leukemia

Emine Guven Maiorov, Ozlem Keskin, Ozden Hatirnaz Ng, Ugur Ozbek, Attila Gursoy
2013 BioMed Research International  
We provide new suggestions for pathways involved in the cause of T-ALL and show that network-based classification techniques produce fewer genes with more meaningful and successful results than expression-based  ...  We conclude that transcription factors, zinc-ion-binding proteins, and tyrosine kinases are the important protein families to trigger T-ALL.  ...  GSE46170 from GEO. This dataset includes 31 patients and 7 healthy samples. Human Protein Interaction Network. The human PPI network is obtained from Human Protein Reference Database.  ... 
doi:10.1155/2013/210253 pmid:23956970 pmcid:PMC3727179 fatcat:jlie53zkqzanzblo2warop6i5i

Hub-Based Reliable Gene Expression Algorithm toClassify ER+ and ER- Breast Cancer Subtypes

Ashish Saini, Jingyu Hou, Wanlei Zhou
2013 International Journal of Bioscience Biochemistry and Bioinformatics  
Subnetwork-based approaches have shown to be a robust classification method that uses interaction datasets such as protein-protein interaction datasets.  ...  the subnetwork based gene signatures for ER+ and ER-breast cancer subtypes.  ...  information are used, [10] is based on SVM framework that directly incorporates the interaction data in an algorithm for the microarray classification, [4] uses protein interaction data that incorporates  ... 
doi:10.7763/ijbbb.2013.v3.156 fatcat:f4yknx7vhfgq3nsl54xftu6mdu

Identifying reliable subnetwork markers in protein-protein interaction network for classification of breast cancer metastasis

Junjie Su, Byung-Jun Yoon
2010 2010 IEEE International Conference on Acoustics, Speech and Signal Processing  
To overcome this problem, we propose a new method for identifying effective subnetwork markers by overlaying the gene expression data with a genome-scale protein-protein interaction network.  ...  Due to the inherent measurement noise in microarray experiments, heterogeneity across samples, and limited sample size, it is often hard to find reliable gene markers for classification.  ...  Recently, there have been research efforts to identify subnetwork markers by overlaying the gene expression data with a protein-protein interaction network [5] .  ... 
doi:10.1109/icassp.2010.5495633 dblp:conf/icassp/SuY10 fatcat:63q2oqbehnaqbapn7jwxj5xfgq

Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers

Hao Chen, Zhitu Zhu, Yichun Zhu, Jian Wang, Yunqing Mei, Yunfeng Cheng
2015 Journal of Cellular and Molecular Medicine  
The network biomarkers and dynamic network biomarkers (DNBs) represent new types of biomarkers with protein-protein or gene-gene interactions that can be monitored and evaluated at different stages and  ...  Annotated molecular networks offer new opportunities to understand diseases within a systems biology framework and provide an excellent substrate for network-based identification of biomarkers.  ...  Acknowledgements This work was supported by Pujiang talent research grant from the Shanghai Committee of Science and Technology (10PJ1403600), National Natural Science Foundation of China (30972737, 81170473  ... 
doi:10.1111/jcmm.12447 pmid:25560835 pmcid:PMC4407592 fatcat:bm6le6xdffggdcbcdbxg5b4ide

Identifying network-based biomarkers of complex diseases from high-throughput data

Zhi-Ping Liu
2016 Biomarkers in Medicine  
Networks are often employed to organize these profiles in the identification of biomarkers to deal with complex diseases in diagnosis, prognosis and therapy as well as mechanism deciphering from systematic  ...  In this work, we review the main available computational methods of identifying biomarkers of complex diseases from high-throughput data.  ...  The differential interactions form subnetworks and can significantly distinguish control from disease samples.  ... 
doi:10.2217/bmm-2015-0035 pmid:26786840 fatcat:kfqwd3j37baylovytoqlfj3jcu

BMRF-Net: a software tool for identification of protein interaction subnetworks by a bagging Markov random field-based method: Fig. 1

Xu Shi, Robert O. Barnes, Li Chen, Ayesha N. Shajahan-Haq, Leena Hilakivi-Clarke, Robert Clarke, Yue Wang, Jianhua Xuan
2015 Bioinformatics  
By integrating gene expression data and protein-protein interaction data, this software tool can be used to identify biologically meaningful subnetworks.  ...  In this paper, we develop a BMRF-Net package, implemented in Java and Cþþ, to identify protein interaction subnetworks based on a bagging Markov random field (BMRF) framework.  ...  Funding National Institutes of Health, under Grants CA149653, CA149147, CA164384, CA184902 and NS294525-18A1 in part. Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btv137 pmid:25755273 pmcid:PMC4495295 fatcat:x45x6p6nnjcnflyzf4bngogizi

Identifying cancer biomarkers by network-constrained support vector machines

Li Chen, Jianhua Xuan, Rebecca B Riggins, Robert Clarke, Yue Wang
2011 BMC Systems Biology  
The netSVM approach is specifically designed for network biomarker identification by integrating gene expression data and protein-protein interaction data.  ...  Many traditional statistical methods, based on microarray gene expression data alone and individual genes' discriminatory power, often fail to identify biologically meaningful biomarkers thus resulting  ...  Acknowledgements This research was supported in part by NIH Grants (CA139246, CA149653, CA149147, CA142009, EB000830, CA109872 and CA096483), an NIH contract (HHSN261200800001E), a Susan G.  ... 
doi:10.1186/1752-0509-5-161 pmid:21992556 pmcid:PMC3214162 fatcat:56jpye4zu5edtgudygpuqldfpa

Network-based classification of breast cancer metastasis

Han-Yu Chuang, Eunjung Lee, Yu-Tsueng Liu, Doheon Lee, Trey Ideker
2007 Molecular Systems Biology  
Here, we apply a proteinnetwork-based approach that identifies markers not as individual genes but as subnetworks extracted from protein interaction databases.  ...  We find that the subnetwork markers are more reproducible than individual marker genes selected without network information, and that they achieve higher accuracy in the classification of metastatic versus  ...  EL and DL were supported by the Korean National Research Laboratory Grant (2005-01450) from the Ministry of Science and Technology.  ... 
doi:10.1038/msb4100180 pmid:17940530 pmcid:PMC2063581 fatcat:x2j5b4cgovfz7mwrmdyp44ptbq

BMRF-MI: integrative identification of protein interaction network by modeling the gene dependency

Xu Shi, Xiao Wang, Ayesha Shajahan, Leena Hilakivi-Clarke, Robert Clarke, Jianhua Xuan
2015 BMC Genomics  
Several methods have been developed to integrate protein-protein interaction (PPI) data with gene expression data for network identification.  ...  Identification of protein interaction network is a very important step for understanding the molecular mechanisms in cancer.  ...  Acknowledgements This work is supported by National Institutes of Health (NIH) [CA149653, CA149147, CA164384, and NS29525-18A, in part].  ... 
doi:10.1186/1471-2164-16-s7-s10 pmid:26099273 pmcid:PMC4474537 fatcat:xoa2ywy66fagdjelsc5ip6l7fq

PhenoNet: identification of key networks associated with disease phenotype

Rotem Ben-Hamo, Moriah Gidoni, Sol Efroni
2014 Bioinformatics  
PhenoNet uses two types of input data: gene expression data (RMA, RPKM, FPKM, etc.) and phenotypic information, and integrates these data with curated pathways and protein-protein interaction information  ...  Comprehensive iterations across all possible pathways and subnetworks result in the identification of key pathways or subnetworks that distinguish between the two phenotypes.  ...  ACKNOWLEDGEMENTS The results published here are fully or partially based on data generated by The Cancer Genome Atlas pilot project established by the NCI and NHGRI.  ... 
doi:10.1093/bioinformatics/btu199 pmid:24812342 fatcat:7lzculwmfjhmvexb5auakeqa7a
« Previous Showing results 1 — 15 out of 3,146 results