@misc{Huang2014,
author = {Huang, Lei and Feng, Gang and Du, Pan and Xia, Tian and Wang, Xishu and Wen, Jing and Kibbe, Warren and Lin, Simon},
publisher = {Bioconductor},
title = {{GeneAnswers: Integrated Interpretation of Genes}},
url = {https://www.bioconductor.org/packages/release/bioc/html/GeneAnswers.html},
year = {2014}
}
@incollection{Feng2012,
abstract = {Use of microarray data to generate expression profiles of genes associated with disease can aid in identification of markers of disease and potential therapeutic targets. Pathway analysis methods further extend expression profiling by creating inferred networks that provide an interpretable structure of the gene list and visualize gene interactions. This chapter describes GeneAnswers, a novel gene-concept network analysis tool available as an open source Bioconductor package. GeneAnswers creates a gene-concept network and also can be used to build protein-protein interaction networks. The package includes an example multiple myeloma cell line dataset and tutorial. Several network analysis methods are included in GeneAnswers, and the tutorial highlights the conditions under which each type of analysis is most beneficial and provides sample code.},
author = {Feng, Gang and Shaw, Pamela and Rosen, Steven T. and Lin, Simon M. and Kibbe, Warren A.},
booktitle = {Methods in molecular biology (Clifton, N.J.)},
doi = {10.1007/978-1-61779-400-1_7},
issn = {1940-6029},
pages = {101--112},
pmid = {22130876},
title = {{Using the Bioconductor GeneAnswers Package to Interpret Gene Lists}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/22130876 http://link.springer.com/10.1007/978-1-61779-400-1{\_}7},
volume = {802},
year = {2012}
}
@article{Feng2010,
abstract = {BACKGROUND Gene-list annotations are critical for researchers to explore the complex relationships between genes and functionalities. Currently, the annotations of a gene list are usually summarized by a table or a barplot. As such, potentially biologically important complexities such as one gene belonging to multiple annotation categories are difficult to extract. We have devised explicit and efficient visualization methods that provide intuitive methods for interrogating the intrinsic connections between biological categories and genes. FINDINGS We have constructed a data model and now present two novel methods in a Bioconductor package, "GeneAnswers", to simultaneously visualize genes, concepts (a.k.a. annotation categories), and concept-gene connections (a.k.a. annotations): the "Concept-and-Gene Network" and the "Concept-and-Gene Cross Tabulation". These methods have been tested and validated with microarray-derived gene lists. CONCLUSIONS These new visualization methods can effectively present annotations using Gene Ontology, Disease Ontology, or any other user-defined gene annotations that have been pre-associated with an organism's genome by human curation, automated pipelines, or a combination of the two. The gene-annotation data model and associated methods are available in the Bioconductor package called "GeneAnswers " described in this publication.},
author = {Feng, Gang and Du, Pan and Krett, Nancy L and Tessel, Michael and Rosen, Steven and Kibbe, Warren A and Lin, Simon M},
doi = {10.1186/1756-0500-3-10},
issn = {1756-0500},
journal = {BMC Research Notes},
month = {jan},
number = {1},
pages = {10},
pmid = {20180973},
title = {{A collection of bioconductor methods to visualize gene-list annotations}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/20180973 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2829581 http://bmcresnotes.biomedcentral.com/articles/10.1186/1756-0500-3-10},
volume = {3},
year = {2010}
}
@article{Kalderimis2014,
abstract = {InterMine (www.intermine.org) is a biological data warehousing system providing extensive automatically generated and configurable RESTful web services that underpin the web interface and can be re-used in many other applications: to find and filter data; export it in a flexible and structured way; to upload, use, manipulate and analyze lists; to provide services for flexible retrieval of sequence segments, and for other statistical and analysis tools. Here we describe these features and discuss how they can be used separately or in combinations to support integrative and comparative analysis.},
author = {Kalderimis, Alex and Lyne, Rachel and Butano, Daniela and Contrino, Sergio and Lyne, Mike and Heimbach, Joshua and Hu, Fengyuan and Smith, Richard and St{\v{e}}p{\'{a}}n, Radek and Sullivan, Julie and Micklem, Gos},
doi = {10.1093/nar/gku301},
issn = {1362-4962},
journal = {Nucleic acids research},
month = {jul},
number = {Web Server issue},
pages = {W468--72},
pmid = {24753429},
publisher = {Oxford University Press},
title = {{InterMine: extensive web services for modern biology.}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/24753429 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4086141},
volume = {42},
year = {2014}
}
@article{Smith2012,
abstract = {SUMMARY InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. Using InterMine, large biological databases can be created from a range of heterogeneous data sources, and the extensible data model allows for easy integration of new data types. The analysis tools include a flexible query builder, genomic region search and a library of 'widgets' performing various statistical analyses. The results can be exported in many commonly used formats. InterMine is a fully extensible framework where developers can add new tools and functionality. Additionally, there is a comprehensive set of web services, for which client libraries are provided in five commonly used programming languages. AVAILABILITY Freely available from http://www.intermine.org under the LGPL license. CONTACT g.micklem@gen.cam.ac.uk SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.},
author = {Smith, R. N. and Aleksic, J. and Butano, D. and Carr, A. and Contrino, S. and Hu, F. and Lyne, M. and Lyne, R. and Kalderimis, A. and Rutherford, K. and Stepan, R. and Sullivan, J. and Wakeling, M. and Watkins, X. and Micklem, G.},
doi = {10.1093/bioinformatics/bts577},
issn = {1367-4803},
journal = {Bioinformatics},
month = {dec},
number = {23},
pages = {3163--3165},
pmid = {23023984},
title = {{InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/23023984 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3516146 https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/bts577},
volume = {28},
year = {2012}
}
