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Extracting gene expression profiles common to colon and pancreatic adenocarcinoma using simultaneous nonnegative matrix factorization

Liviu Badea
2008 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
We have applied our simultaneous factorization algorithm looking for gene expression profiles that are common between the more homogeneous pancreatic ductal adenocarcinoma (PDAC) and the more heterogeneous  ...  The siNMF algorithm simultaneously searches for two factorizations that share the same gene expression profiles.  ...  Popescu for the Pacific Symposium on Biocomputing 13:279-290(2008) collaboration in these projects and to the reviewers for some very useful suggestions for improving this work.  ... 
pmid:18229692 fatcat:hx7mm7c6kvbzrmcrvitwd3ftua

Application of non-negative matrix factorization in oncology: one approach for establishing precision medicine

Ryuji Hamamoto, Ken Takasawa, Hidenori Machino, Kazuma Kobayashi, Satoshi Takahashi, Amina Bolatkan, Norio Shinkai, Akira Sakai, Rina Aoyama, Masayoshi Yamada, Ken Asada, Masaaki Komatsu (+3 others)
2022 Briefings in Bioinformatics  
Non-negative matrix factorization (NMF) is a machine learning technique used for image analysis, speech recognition, and language processing; recently, it is being applied to medical research.  ...  , providing examples of how NMF can be used to establish precision medicine, and presenting the challenges of NMF.  ...  The extraction of useful information (i) , i = 1, 2, . . . , S, and G common genes to be meta-analyzed.  ... 
doi:10.1093/bib/bbac246 pmid:35788277 pmcid:PMC9294421 fatcat:l5jpplwrnbbohmfk74vex6h5bm

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network

Jianing Xi, Minghui Wang, Ao Li
2018 BMC Bioinformatics  
Results: To incorporate prior information from both interaction network and mRNA expressions, we propose a robust and sparse co-regularized nonnegative matrix factorization to discover driver genes from  ...  a robust and sparse co-regularized matrix factorization framework.  ...  Acknowledgements We would like to thank the reviewers for their valuable comments and helpful suggestions that helped us to improve the manuscript.  ... 
doi:10.1186/s12859-018-2218-y pmid:29871594 pmcid:PMC5989443 fatcat:ehyrch5xnbavtkgdrdpmek2p2m

Exploring background mutational processes to decipher cancer genetic heterogeneity

Alexander Goncearenco, Stephanie L. Rager, Minghui Li, Qing-Xiang Sang, Igor B. Rogozin, Anna R. Panchenko
2017 Nucleic Acids Research  
processes including those related to infidelity of DNA replication and repair machinery, and various other endogenous and exogenous mutagenic factors.  ...  As a result, the combination of mutagenic processes can be identified in any query sample with subsequent comparison to mutational profiles derived from malignant and benign samples.  ...  Author Contributions: A.G. and A.R.P. designed the analysis and wrote the paper. A.G. developed the framework. S.L.R, M.L., Q.X.S. and I.B.R. applied the framework to the analysis of cancer genomes.  ... 
doi:10.1093/nar/gkx367 pmid:28472504 pmcid:PMC5793731 fatcat:zrliuqo4l5godawceqfhsfqfyu

Multi-omics Data Integration, Interpretation, and Its Application

Indhupriya Subramanian, Srikant Verma, Shiva Kumar, Abhay Jere, Krishanpal Anamika
2020 Bioinformatics and Biology Insights  
We provide the methodology, use-cases, and limitations of these tools; brief account of multi-omics data repositories and visualization portals; and challenges associated with multi-omics data integration  ...  To study complex biological processes holistically, it is imperative to take an integrative approach that combines multi-omics data to highlight the interrelationships of the involved biomolecules and  ...  Authors would also like to thank Pratap Sanap for his input on tools categorization. We thank the anonymous reviewers for their useful comments and valuable suggestions.  ... 
doi:10.1177/1177932219899051 pmid:32076369 pmcid:PMC7003173 fatcat:dchnmbmzh5di7jcuc7ilxjsk3e

Pattern discovery and cancer gene identification in integrated cancer genomic data

Qianxing Mo, Sijian Wang, Venkatraman E. Seshan, Adam B. Olshen, Nikolaus Schultz, Chris Sander, R. Scott Powers, Marc Ladanyi, Ronglai Shen
2013 Proceedings of the National Academy of Sciences of the United States of America  
A key aspect of the method is to use generalized linear regression for the formulation of a joint model, with respect to a common set of latent variables that we propose represents distinct driving factors  ...  The method was recently used in a landmark study to predict novel breast cancer subtypes with distinct clinical outcomes (9), and it was found that the joint clustering of copy number and gene expression  ...  supported in part by Genome Data Analysis Center Type B Grant U24 CA143840, awarded as part of the National Cancer Institute/National Human Genome Research Institute-funded Cancer Genome Atlas project, and  ... 
doi:10.1073/pnas.1208949110 pmid:23431203 pmcid:PMC3600490 fatcat:vx73girquzardhalcomylnxxka

Simultaneous Non-Negative Matrix Factorization for Multiple Large Scale Gene Expression Datasets in Toxicology

Clare M. Lee, Manikhandan A. V. Mudaliar, D. R. Haggart, C. Roland Wolf, Gino Miele, J. Keith Vass, Desmond J. Higham, Daniel Crowther, Ramin Homayouni
2012 PLoS ONE  
Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data.  ...  We discuss the algorithmic issues required to convert the approach into a practical computational tool and apply the technique to new gene expression data quantifying the molecular changes in four tissue  ...  Acknowledgments The computational work reported here made extensive use of the High Performance Computer Facilities of the Faculty of Engineering and Institute of Complex Systems at the University of Strathclyde  ... 
doi:10.1371/journal.pone.0048238 pmid:23272042 pmcid:PMC3522745 fatcat:hyspxwzwezdmxcdkpocpa7gyle

Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis

Otília Menyhárt, Balázs Győrffy
2021 Computational and Structural Biotechnology Journal  
We review some of the most frequently used data integration methods and outline research areas where multi-omics significantly benefit our understanding of the process and outcome of the malignant transformation  ...  Progressive initiatives to enforce the standardization of sample processing and analytical pipelines, multidisciplinary training of experts for data analysis and interpretation are vital to facilitate  ...  Acknowledgements The authors wish to acknowledge the support of ELIXIR Hungary (www.elixir-hungary.org).  ... 
doi:10.1016/j.csbj.2021.01.009 pmid:33613862 pmcid:PMC7868685 fatcat:u7l3qybr5rhr5mcvj2o4q72zue

Applications of single-cell sequencing in cancer research: progress and perspectives

Yalan Lei, Rong Tang, Jin Xu, Wei Wang, Bo Zhang, Jiang Liu, Xianjun Yu, Si Shi
2021 Journal of Hematology & Oncology  
The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions.  ...  AbstractSingle-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell  ...  Recent research revealed that the combination of nonnegative matrix factorization and Bayesian model comparison with current algorithms enables unambiguous assessments of the depth of heterogeneity in  ... 
doi:10.1186/s13045-021-01105-2 pmid:34108022 fatcat:t4tbra5jf5akvgof3utezl3f34

Molecular characteristics of primary pulmonary lymphoepithelioma-like carcinoma based on integrated genomic analyses

Bojiang Chen, Yu Zhang, Sisi Dai, Ping Zhou, Wenxin Luo, Zhoufeng Wang, Xuping Chen, Peng Cheng, Guoya Zheng, Jing Ren, Xiaodong Yang, Weimin Li
2021 Signal Transduction and Targeted Therapy  
Three tumor-associated genes, zinc finger and BTB domain-containing 16 (ZBTB16), peroxisome proliferator activated receptor gamma (PPARG), and transforming growth factor beta receptor 2 (TGFBR2), were  ...  High PD-L1 or p53 expression was associated with extended disease-free survival (DFS). pLELC had 14 frequently mutated genes (FMGs).  ...  In addition, the COSMIC cancer gene census database was used to extract oncogenes/TSGs with tier 1 evidence.  ... 
doi:10.1038/s41392-020-00382-6 pmid:33414372 pmcid:PMC7791019 fatcat:ge5xjnnxxna2dlw3f7wtovltpq

Portrait of a cancer: mutational signature analyses for cancer diagnostics

Arne Van Hoeck, Niels H. Tjoonk, Ruben van Boxtel, Edwin Cuppen
2019 BMC Cancer  
Importantly, the molecular mechanisms underlying specific signatures can now be dissected and coupled to treatment strategies.  ...  In the past decade, systematic and comprehensive analyses of cancer genomes have identified cancer driver genes and revealed unprecedented insight into the molecular mechanisms underlying the initiation  ...  In 2013, Stratton and his team introduced a computational framework that used nonnegative matrix factorization (NMF) to recognize multiple base substitution patterns in human cancers [15, 22] .  ... 
doi:10.1186/s12885-019-5677-2 fatcat:njtypwi7p5hvdfu4yf3jlz6x3y

Molecular subtyping of colorectal cancer: Recent progress, new challenges and emerging opportunities

Wei Wang, Raju Kandimalla, Hao Huang, Lina Zhu, Ying Li, Feng Gao, Ajay Goel, Xin Wang
2018 Seminars in Cancer Biology  
Along the "adenoma-carcinoma" sequence, mutations in several key genes such as KRAS and TP53 have demonstrated prognostic and predictive values.  ...  Also prominent in CRC are mutations in the TP53 tumor suppressor gene, which play a crucial role in cell proliferation and apoptosis [45, 46] .  ...  Acknowledgments The present work was supported by a start-up grant for new faculty (7200455) and a VPRT grant (9610337)  ... 
doi:10.1016/j.semcancer.2018.05.002 pmid:29775690 pmcid:PMC6240404 fatcat:jtfffdfoznenfmigdydgekqxby

Making sense of cancer genomic data

Lynda Chin, William C. Hahn, Gad Getz, Matthew Meyerson
2011 Genes & Development  
Acknowledgments We apologize to colleagues whose studies, algorithms, or portals are not cited in this review due to limitation in space.  ...  ., and M.M. are TCGA-funded investigators (NIH U24CA143845, U24CA144025, and U24CA143867). L.C. and W.C.H. are CTD2 (Cancer Target Discovery and Development) network investigators (NIH RC2CA148268).  ...  clustering (Eisen et al. 1998 ), selforganizing maps , and nonnegative matrix factorization (Kim and Tidor 2003; Brunet et al. 2004) .  ... 
doi:10.1101/gad.2017311 pmid:21406553 pmcid:PMC3059829 fatcat:spixug2h2zgfzh47akcfa44t3e

Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints

Juan Wang, Cong-Hai Lu, Jin-Xing Liu, Ling-Yun Dai, Xiang-Zhen Kong
2019 BMC Bioinformatics  
Then, an affinity matrix is constructed to perform the multi-cancer sample clustering by using a spectral clustering algorithm, i.e., normalized cuts (Ncuts).  ...  Clustering cancer gene expression data from multiple cancers to their own class is a significance solution.  ...  Acknowledgements Thanks go to the editor and the anonymous reviewers for their comments and suggestions.  ... 
doi:10.1186/s12859-019-3231-5 pmid:31888442 pmcid:PMC6936083 fatcat:25guvqmggrcfhpkeynbrnioibe

Dictionary Learning-Based Feature-Level Domain Adaptation for Cross-Scene Hyperspectral Image Classification

Minchao Ye, Yuntao Qian, Jun Zhou, Yuan Yan Tang
2017 IEEE Transactions on Geoscience and Remote Sensing  
To be more specific, if there are a few labeled pixels in the target domain, multitask sparse logistic regression is used to further promote the classification performance.  ...  The basis atoms in the learned dictionary represent the common spectral components, which span a cross-scene feature space to minimize the effect of spectral shift.  ...  Multitask NMF, or called simultaneous NMF, was first proposed by Badea [51] to extract common gene expression profiles that are shared by colon and pancreatic adenocarcinoma.  ... 
doi:10.1109/tgrs.2016.2627042 fatcat:jk5dgw325jd4beo3ijbv6bdwbq
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