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Bruce R. Conklin

dblp:02/254 · DBLP profile ↗
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5ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0003-1463-6061ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 5

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › functional genomics › functional enrichment analysis
gene ontology analysis
0.112012
GO-Elite: a flexible solution for pathway and ontology over-representation · Bioinform. 2012
Bioinformatics and computational biology › knowledge representation in biology › biomedical ontology
ontology analysis
0.112012
GO-Elite: a flexible solution for pathway and ontology over-representation · Bioinform. 2012
Bioinformatics and computational biology › functional genomics › functional enrichment analysis
over-representation analysis
0.112012
GO-Elite: a flexible solution for pathway and ontology over-representation · Bioinform. 2012
Bioinformatics and computational biology › systems bioinformatics
pathway analysis
0.112012
GO-Elite: a flexible solution for pathway and ontology over-representation · Bioinform. 2012
YearPublicationVenuePosition
2012 GO-Elite: a flexible solution for pathway and ontology over-representation
abstract
UNLABELLED: We introduce GO-Elite, a flexible and powerful pathway analysis tool for a wide array of species, identifiers (IDs), pathways, ontologies and gene sets. In addition to the Gene Ontology (GO), GO-Elite allows the user to perform over-representation analysis on any structured ontology annotations, pathway database or biological IDs (e.g. gene, protein or metabolite). GO-Elite exploits the structured nature of biological ontologies to report a minimal set of non-overlapping terms. The results can be visualized on WikiPathways or as networks. Built-in support is provided for over 60 species and 50 ID systems, covering gene, disease and phenotype ontologies, multiple pathway databases, biomarkers, and transcription factor and microRNA targets. GO-Elite is available as a web interface, GenMAPP-CS plugin and as a cross-platform application. AVAILABILITY: http://www.genmapp.org/go_elite
Alexander C. Zambon, Stan Gaj, Isaac Ho, Kristina Hanspers, Karen Vranizan, Chris T. A. Evelo, Bruce R. Conklin, Alexander R. Pico, Nathan Salomonis
Bioinform.7
2010 The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services
abstract
BACKGROUND: Many complementary solutions are available for the identifier mapping problem. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. RESULTS: Here we present BridgeDb, a software framework for gene, protein and metabolite identifier mapping. This framework provides a standardized interface layer through which bioinformatics tools can be connected to different identifier mapping services. This approach makes it easier for tool developers to support identifier mapping. Mapping services can be combined or merged to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb provides its own ready-to-go mapping services, both in webservice and local database forms. However, the framework is intended for customization and adaptation to any identifier mapping service. BridgeDb has already been integrated into several bioinformatics applications. CONCLUSION: By uncoupling bioinformatics tools from mapping services, BridgeDb improves capability and flexibility of those tools. All described software is open source and available at http://www.bridgedb.org.
Martijn P. van Iersel, Alexander R. Pico, Thomas Kelder, Jianjiong Gao, Isaac Ho, Kristina Hanspers, Bruce R. Conklin, Chris T. A. Evelo
BMC Bioinform.7
2009 Alternative Splicing in the Differentiation of Human Embryonic Stem Cells into Cardiac Precursors
abstract
The role of alternative splicing in self-renewal, pluripotency and tissue lineage specification of human embryonic stem cells (hESCs) is largely unknown. To better define these regulatory cues, we modified the H9 hESC line to allow selection of pluripotent hESCs by neomycin resistance and cardiac progenitors by puromycin resistance. Exon-level microarray expression data from undifferentiated hESCs and cardiac and neural precursors were used to identify splice isoforms with cardiac-restricted or common cardiac/neural differentiation expression patterns. Splice events for these groups corresponded to the pathways of cytoskeletal remodeling, RNA splicing, muscle specification, and cell cycle checkpoint control as well as genes with serine/threonine kinase and helicase activity. Using a new program named AltAnalyze (http://www.AltAnalyze.org), we identified novel changes in protein domain and microRNA binding site architecture that were predicted to affect protein function and expression. These included an enrichment of splice isoforms that oppose cell-cycle arrest in hESCs and that promote calcium signaling and cardiac development in cardiac precursors. By combining genome-wide predictions of alternative splicing with new functional annotations, our data suggest potential mechanisms that may influence lineage commitment and hESC maintenance at the level of specific splice isoforms and microRNA regulation.
Nathan Salomonis, Brandon Nelson, Karen Vranizan, Alexander R. Pico, Kristina Hanspers, Allan Kuchinsky, Linda Ta, Mark Mercola, Bruce R. Conklin
PLoS Comput. Biol.9
2008 Presenting and exploring biological pathways with PathVisio
abstract
BACKGROUND: Biological pathways are a useful abstraction of biological concepts, and software tools to deal with pathway diagrams can help biological research. PathVisio is a new visualization tool for biological pathways that mimics the popular GenMAPP tool with a completely new Java implementation that allows better integration with other open source projects. The GenMAPP MAPP file format is replaced by GPML, a new XML file format that provides seamless exchange of graphical pathway information among multiple programs. RESULTS: PathVisio can be combined with other bioinformatics tools to open up three possible uses: visual compilation of biological knowledge, interpretation of high-throughput expression datasets, and computational augmentation of pathways with interaction information. PathVisio is open source software and available at http://www.pathvisio.org. CONCLUSION: PathVisio is a graphical editor for biological pathways, with flexibility and ease of use as primary goals.
Martijn P. van Iersel, Thomas Kelder, Alexander R. Pico, Kristina Hanspers, Susan L. Coort, Bruce R. Conklin, Chris T. A. Evelo
BMC Bioinform.6
2007 GenMAPP 2: new features and resources for pathway analysis
abstract
BACKGROUND: Microarray technologies have evolved rapidly, enabling biologists to quantify genome-wide levels of gene expression, alternative splicing, and sequence variations for a variety of species. Analyzing and displaying these data present a significant challenge. Pathway-based approaches for analyzing microarray data have proven useful for presenting data and for generating testable hypotheses. RESULTS: To address the growing needs of the microarray community we have released version 2 of Gene Map Annotator and Pathway Profiler (GenMAPP), a new GenMAPP database schema, and integrated resources for pathway analysis. We have redesigned the GenMAPP database to support multiple gene annotations and species as well as custom species database creation for a potentially unlimited number of species. We have expanded our pathway resources by utilizing homology information to translate pathway content between species and extending existing pathways with data derived from conserved protein interactions and coexpression. We have implemented a new mode of data visualization to support analysis of complex data, including time-course, single nucleotide polymorphism (SNP), and splicing. GenMAPP version 2 also offers innovative ways to display and share data by incorporating HTML export of analyses for entire sets of pathways as organized web pages. CONCLUSION: GenMAPP version 2 provides a means to rapidly interrogate complex experimental data for pathway-level changes in a diverse range of organisms.
Nathan Salomonis, Kristina Hanspers, Alexander C. Zambon, Karen Vranizan, Steven C. Lawlor, Kam D. Dahlquist, Scott Doniger, Joshua M. Stuart, Bruce R. Conklin, Alexander R. Pico
BMC Bioinform.9