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Automation of ReactomeFIViz via CyREST API

Fred Loney, Guanming Wu
2018 F1000Research  
Wu G, Feng X, Stein L: A human functional protein interaction network and its application to cancer data analysis. Genome Biol. 2010; 11(5): R53.  ...  Wu G, Dawson E, Duong A, et al.: ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis [version 2; referees: 2 approved]. F1000Res. 2014; 3: 146.  ...  Best regards, Guanming Wu, Ph.D. No competing interests were disclosed.  ... 
doi:10.12688/f1000research.14776.1 pmid:29946442 pmcid:PMC5998009 fatcat:l2y2r3trdzayxeyb75fcjcosve

Automation of ReactomeFIViz via CyREST API

Fred Loney, Guanming Wu
2018 F1000Research  
Best regards, Guanming Wu, Ph.D. Guanming Wu, Ph.D. No competing interests were disclosed.  ...  I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.Author Response 20 May 2018 , Oregon Health & Science University, USA Guanming Wu Dear  ... 
doi:10.12688/f1000research.14776.2 fatcat:xwe2vhmcffgtha6vdmh6t54ece

A network module-based method for identifying cancer prognostic signatures

Guanming Wu, Lincoln Stein
2012 Genome Biology  
Materials and methods Functional interaction network construction The functional interaction network used in this study was described in Wu et al. [24] .  ...  2.43E+00 95% HR CI 1.06 -5.55 P-value 3.61E-02 GSE13876 HR 2.13E+00 95% HR CI 1.46 -3.10 P-value 8.85E-05 GSE26712 HR 1.56E+00 95% HR CI 1.08 -2.25 P-value 1.75E-02 Wu  ... 
doi:10.1186/gb-2012-13-12-r112 pmid:23228031 pmcid:PMC3580410 fatcat:4cy3s22e4vgcdetislrfot3zpi

AutoQGS: Auto-Prompt for Low-Resource Knowledge-based Question Generation from SPARQL [article]

Guanming Xiong, Junwei Bao, Wen Zhao, Youzheng Wu, Xiaodong He
2022 arXiv   pre-print
This study investigates the task of knowledge-based question generation (KBQG). Conventional KBQG works generated questions from fact triples in the knowledge graph, which could not express complex operations like aggregation and comparison in SPARQL. Moreover, due to the costly annotation of large-scale SPARQL-question pairs, KBQG from SPARQL under low-resource scenarios urgently needs to be explored. Recently, since the generative pre-trained language models (PLMs) typically trained in
more » ... language (NL)-to-NL paradigm have been proven effective for low-resource generation, e.g., T5 and BART, how to effectively utilize them to generate NL-question from non-NL SPARQL is challenging. To address these challenges, AutoQGS, an auto-prompt approach for low-resource KBQG from SPARQL, is proposed. Firstly, we put forward to generate questions directly from SPARQL for the KBQG task to handle complex operations. Secondly, we propose an auto-prompter trained on large-scale unsupervised data to rephrase SPARQL into NL description, smoothing the low-resource transformation from non-NL SPARQL to NL question with PLMs. Experimental results on the WebQuestionsSP, ComlexWebQuestions 1.1, and PathQuestions show that our model achieves state-of-the-art performance, especially in low-resource settings. Furthermore, a corpus of 330k factoid complex question-SPARQL pairs is generated for further KBQG research.
arXiv:2208.12461v1 fatcat:rta32rv5zvdx3cr4ww4iwehjsm

The brand analysis of Nike based on its emotional branding and marketing strategies

Guanming Wu
2022 BCP Business & Management  
Nowadays, Nike has become one of the most socially-conscious brands around the world because of its effective branding and marketing strategies. Therefore, it is worthwhile to understand the brand development of Nike and explore how Nike's branding and marketing strategies put it into a favorable position in the competitive market. This paper was committed to a brand analysis of Nike taking its main product—shoes as the example. The brand value proposition of Nike is to provide accessible,
more » ... onable, innovative, and high-performance shoes for its customers in every sport. Customer-focused emotional branding and marketing have made Nike establish a strong emotional resonance for its audience and thereby developed a prominent brand cognitive. Additionally, although traditional marketing channels have still played an important role in brand publicity, digital marketing has functioned as a booster to help Nike develop new markets and enhance customer loyalty to the brand. Nevertheless, in order to obtain greater success in the high-performance athletic-product market, Nike needs to overcome huge internal and external challenges, such as inadequate product competitiveness, the impact of Covid-19 pandemic, and global economic uncertainty. In this paper, some practical suggestions were provided for the management to improve product competitiveness and strengthen the two-way interaction between the brand and its customers.
doi:10.54691/bcpbm.v19i.816 fatcat:7uu5fov4qveglknw4rawgk5nha

A human functional protein interaction network and its application to cancer data analysis

Guanming Wu, Xin Feng, Lincoln Stein
2010 Genome Biology  
63] TRED [64] NCI-BioCarta [62] NCI-Nature [62] CellMap [61] Na Data sources for annotated FIs Naïve Bayes Classifier r trained by validated by Predicted FIs Annotated FIs t t d FI d F FI Network N t Wu  ... 
doi:10.1186/gb-2010-11-5-r53 pmid:20482850 pmcid:PMC2898064 fatcat:vntehsevq5gcrfppuzcikesvde

ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis

Guanming Wu, Eric Dawson, Adrian Duong, Robin Haw, Lincoln Stein
2014 F1000Research  
The details about the type of analyses and the statistical tests the App enables are provided in an earlier paper by the same group (Wu, Feng and Stein, 2010), but not in this paper.  ...  The details about the type of analyses and the statistical tests the App enables are provided in an earlier paper by the same group (Wu, Feng and Stein, 2010), but not in this paper.  ...  Competing Interests: 1 Comment Author Response , Guanming Wu Posted: 06 Sep 2014 Thanks a lot for your comments. We have made changes according to your comments.  ... 
doi:10.12688/f1000research.4431.2 pmid:25309732 pmcid:PMC4184317 fatcat:xk7tmedvkvefnivh3vrciysqvi

Annotating Cancer Variants and Anti-Cancer Therapeutics in Reactome

Marija Milacic, Robin Haw, Karen Rothfels, Guanming Wu, David Croft, Henning Hermjakob, Peter D'Eustachio, Lincoln Stein
2012 Cancers  
Wu), the European Bioinformatics Institute (Henning Hermjakob, David Croft, Antonio Fabregat-Mundo, Phani Garapati, Bijay Jassal, Steven Jupe) and the NYU School of Medicine (Peter D'Eustachio, Lisa Matthews  ...  curators and software developers at the Ontario Institute for Cancer Research (Lincoln Stein, Michael Caudy, Marc Gillespie, Robin Haw, Marija Milacic, Bruce May, Karen Rothfels, Heeyeon Song, Joel Weiser, Guanming  ... 
doi:10.3390/cancers4041180 pmid:24213504 pmcid:PMC3712731 fatcat:yuq7zjs3z5edxngpwzncfa7jaq

ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis

Guanming Wu, Eric Dawson, Adrian Duong, Robin Haw, Lincoln Stein
2014 F1000Research  
Since then, both Cytoscape (Wu, Feng and Stein, 2010 extensions, the plug-in and the app, have actively been used by users.  ...  The details about the type of analyses and the statistical tests the App enables are provided in an earlier paper by the same group (Wu, Feng and Stein, 2010), but not in this paper.  ...  Author Response 06 Sep 2014 , Oregon Health & Science University, USA Guanming Wu Thanks a lot for your comments. We have made changes according to your comments.  ... 
doi:10.12688/f1000research.4431.1 pmid:25309732 pmcid:PMC4184317 fatcat:ge5zyllirjdqjlnxr7sddqo5lm

Visualization of drug target interactions in the contexts of pathways and networks with ReactomeFIViz

Aurora S. Blucher, Shannon K. McWeeney, Lincoln Stein, Guanming Wu
2019 F1000Research  
The precision medicine paradigm is centered on therapies targeted to particular molecular entities that will elicit an anticipated and controlled therapeutic response. However, genetic alterations in the drug targets themselves or in genes whose products interact with the targets can affect how well a drug actually works for an individual patient. To better understand the effects of targeted therapies in patients, we need software tools capable of simultaneously visualizing patient-specific
more » ... ations and drug targets in their biological context. This context can be provided using pathways, which are process-oriented representations of biological reactions, or biological networks, which represent pathway-spanning interactions among genes, proteins, and other biological entities. To address this need, we have recently enhanced the Reactome Cytoscape app, ReactomeFIViz, to assist researchers in visualizing and modeling drug and target interactions. ReactomeFIViz integrates drug-target interaction information with high quality manually curated pathways and a genome-wide human functional interaction network. Both the pathways and the functional interaction network are provided by Reactome, the most comprehensive open source biological pathway knowledgebase. We describe several examples demonstrating the application of these new features to the visualization of drugs in the contexts of pathways and networks. Complementing previous features in ReactomeFIViz, these new features enable researchers to ask focused questions about targeted therapies, such as drug sensitivity for patients with different mutation profiles, using a pathway or network perspective.
doi:10.12688/f1000research.19592.1 pmid:31372215 pmcid:PMC6644836 fatcat:ghlhbtvc3jcu5iqn5owdwsaum4

Evidence-Based Precision Oncology with the Cancer Targetome

Aurora S. Blucher, Gabrielle Choonoo, Molly Kulesz-Martin, Guanming Wu, Shannon K. McWeeney
2017 TIPS - Trends in Pharmacological Sciences  
A core tenet of precision oncology is the rational choice of drugs to interact with patient-specific biological targets of interest, but it is currently difficult for researchers to obtain consistent and well-supported target information for pharmaceutical drugs. We review current drug target interaction resources and critically assess how supporting evidence is handled. We introduce the concept of a unified Cancer Targetome to aggregate drug target interactions within an evidencebased
more » ... . We discuss current unmet needs and the implications for evidence based-clinical omics. The focus of this review is precision oncology but the discussion is highly relevant to targeted therapies of any area. The advent of precision oncology (see Glossary) is often hallmarked with the development of the targeted therapy imatinib to treat BCR/ABL1 positive chronic myeloid leukemia (CML) [1] . Over time, the term precision oncology has evolved to include the use of genetic biomarkers to guide treatment selection as well as refer to the emerging paradigm of treating cancer in a mutation-centric manner over a histology-centric manner [2] [3] [4] . This work is open for academic research use, but additional licensing permission may be required by a third party. Our work is made available under the Creative Commons Attribution Non-Commercial Share Alike 4.0 License. Please see http://github.com/ablucher/ The-Cancer-Targetome for more information.
doi:10.1016/j.tips.2017.08.006 pmid:28964549 pmcid:PMC5759325 fatcat:55goefufurgtjcqmmnioogj4ei

REACTOME: A KNOWLEDGEBASE OF BIOLOGICAL PATHWAYS

Lincoln Stein, Peter D'Eustachio, Gopal Gopinathrao, Marc Gillespie, Lisa Matthews, Guanming Wu, Imre Vastrik, Esther Schmidt, Bernard de Bono, Bijay Jassal, David Croft, Ewan Birney (+1 others)
2006 Computational Systems Bioinformatics  
Reactome, located at http://www.reactome.org is a curated, peer-reviewed resource of human biological processes. Given the genetic makeup of an organism, the complete set of possible reactions constitutes its reactome. The basic unit of the Reactome database is a reaction; reactions are then grouped into causal chains to form pathways. The Reactome data model allows us to represent many diverse processes in the human system, including the pathways of intermediary metabolism, regulatory
more » ... and signal transduction, and high-level processes, such as the cell cycle. Reactome provides a qualitative framework, on which quantitative data can be superimposed. Tools have been developed to facilitate custom data entry and annotation by expert biologists, and to allow visualization and exploration of the finished dataset as an interactive process map. Although our primary curational domain is pathways from Homo sapiens, we regularly create electronic projections of human pathways onto other organisms via putative orthologs, thus making Reactome relevant to model organism research communities. The database is publicly available under open source terms, which allows both its content and its software infrastructure to be freely used and redistributed.
doi:10.1142/9781860947575_0009 fatcat:yk445f4ienairev4uebdmrgaca

Reactome – a knowledgebase of human biological pathways

Peter D'Eustachio, Lisa Matthews, Ewan Birney, Lincoln Stein, Esther Schmidt, Imre Vastrik, Guanming Wu, David Croft, Bernard de Bono, Gopal Gopinath, Suzanna Lewis, Marc Gillespie (+1 others)
2007 Nature Precedings  
doi:10.1038/npre.2007.1281.1 fatcat:ux3n3qxu3zalho3t65cp4jh3mm

Natural Product Target Network Reveals Potential for Cancer Combination Therapies

Steven R. Chamberlin, Aurora Blucher, Guanming Wu, Lynne Shinto, Gabrielle Choonoo, Molly Kulesz-Martin, Shannon McWeeney
2019 Frontiers in Pharmacology  
This network integrates uncurated relationships from sources such as PPI databases and others with curated interaction information derived from pathway data in Reactome and other databases (Wu et al.,  ... 
doi:10.3389/fphar.2019.00557 pmid:31214023 pmcid:PMC6555193 fatcat:57bcirnbtfbxtltqwhosin73ae

Reactome – A Knowledgebase of Biological Pathways [chapter]

Esther Schmidt, Ewan Birney, David Croft, Bernard de Bono, Peter D'Eustachio, Marc Gillespie, Gopal Gopinath, Bijay Jassal, Suzanna Lewis, Lisa Matthews, Lincoln Stein, Imre Vastrik (+1 others)
2006 Lecture Notes in Computer Science  
Reactome, located at http://www.reactome.org is a curated, peer-reviewed resource of human biological processes. Given the genetic makeup of an organism, the complete set of possible reactions constitutes its reactome. The basic unit of the Reactome database is a reaction; reactions are then grouped into causal chains to form pathways. The Reactome data model allows us to represent many diverse processes in the human system, including the pathways of intermediary metabolism, regulatory
more » ... and signal transduction, and high-level processes, such as the cell cycle. Reactome provides a qualitative framework, on which quantitative data can be superimposed. Tools have been developed to facilitate custom data entry and annotation by expert biologists, and to allow visualization and exploration of the finished dataset as an interactive process map. Although our primary curational domain is pathways from Homo sapiens, we regularly create electronic projections of human pathways onto other organisms via putative orthologs, thus making Reactome relevant to model organism research communities. The database is publicly available under open source terms, which allows both its content and its software infrastructure to be freely used and redistributed.
doi:10.1007/11915034_95 fatcat:mhi75mdnrzhddiaccuq6viyebq
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