Demo Data from SIGIR 2026 / reviewers in the wild / expert
William C. Reinhold
dblp:39/1282
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0001-5513-9323ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 4
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
2 papers |
Bioinformatics and computational biology · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › computational oncology
cancer cell line analysis |
0.2 | 1 | 2016 | rcellminer: exploring molecular profiles and drug response of the NCI-60 cell lines in R · Bioinform. 2016 |
Bioinformatics and computational biology › gene expression analysis
microarray data analysis |
0.1 | 1 | 2007 | AffyProbeMiner: a web resource for computing or retrieving accurately redefined Affymetrix probe sets · Bioinform. 2007 |
Bioinformatics and computational biology
transcriptomics |
0.0 | 1 | 2007 | AffyProbeMiner: a web resource for computing or retrieving accurately redefined Affymetrix probe sets · Bioinform. 2007 |
Methods — techniques the papers use, named apart from their topics
refseq · 0.1genbank · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | rcellminer: exploring molecular profiles and drug response of the NCI-60 cell lines in RabstractPURPOSE: The rcellminer R package provides a wide range of functionality to help R users access and explore molecular profiling and drug response data for the NCI-60. The package enables flexible programmatic access to CellMiner's unparalleled breadth of NCI-60 data, including gene and protein expression, copy number, whole exome mutations, as well as activity data for ∼21K compounds, with information on their structure, mechanism of action and repeat screens. Functions are available to easily visualize compound structures, activity patterns and molecular feature profiles. Additionally, embedded R Shiny applications allow interactive data exploration. AVAILABILITY AND IMPLEMENTATION: rcellminer is compatible with R 3.2 and above on Windows, Mac OS X and Linux. The package, documentation, tutorials and Shiny-based applications are available through Bioconductor (http://www.bioconductor.org/packages/rcellminer); ongoing updates will occur according to the Bioconductor release schedule with new CellMiner data. The package is free and open-source (LGPL 3). CONTACT: [email protected] or [email protected]. Augustin Luna, Vinodh N. Rajapakse, Fabricio G. Sousa, Jianjiong Gao, Nikolaus Schultz, Sudhir Varma, William C. Reinhold, Chris Sander, Yves Pommier |
Bioinform. | 7 |
| 2011 | RedundancyMiner: De-replication of redundant GO categories in microarray and proteomics analysisabstractBACKGROUND: The Gene Ontology (GO) Consortium organizes genes into hierarchical categories based on biological process, molecular function and subcellular localization. Tools such as GoMiner can leverage GO to perform ontological analysis of microarray and proteomics studies, typically generating a list of significant functional categories. Two or more of the categories are often redundant, in the sense that identical or nearly-identical sets of genes map to the categories. The redundancy might typically inflate the report of significant categories by a factor of three-fold, create an illusion of an overly long list of significant categories, and obscure the relevant biological interpretation. RESULTS: We now introduce a new resource, RedundancyMiner, that de-replicates the redundant and nearly-redundant GO categories that had been determined by first running GoMiner. The main algorithm of RedundancyMiner, MultiClust, performs a novel form of cluster analysis in which a GO category might belong to several category clusters. Each category cluster follows a "complete linkage" paradigm. The metric is a similarity measure that captures the overlap in gene mapping between pairs of categories. CONCLUSIONS: RedundancyMiner effectively eliminated redundancies from a set of GO categories. For illustration, we have applied it to the clarification of the results arising from two current studies: (1) assessment of the gene expression profiles obtained by laser capture microdissection (LCM) of serial cryosections of the retina at the site of final optic fissure closure in the mouse embryos at specific embryonic stages, and (2) analysis of a conceptual data set obtained by examining a list of genes deemed to be "kinetochore" genes. Barry Zeeberg, Ari B. Kahn, Martin Ehler, Vinodh N. Rajapakse, Robert F. Bonner, Jacob D. Brown, Brian P. Brooks, Vladimir L. Larionov, William C. Reinhold, John N. Weinstein, Yves Pommier |
BMC Bioinform. | 10 |
| 2007 | AffyProbeMiner: a web resource for computing or retrieving accurately redefined Affymetrix probe setsabstractMOTIVATION: Affymetrix microarrays are widely used to measure global expression of mRNA transcripts. That technology is based on the concept of a probe set. Individual probes within a probe set were originally designated by Affymetrix to hybridize with the same unique mRNA transcript. Because of increasing accuracy in knowledge of genomic sequences, however, a substantial number of the manufacturer's original probe groupings and mappings are now known to be inaccurate and must be corrected. Otherwise, analysis and interpretation of an Affymetrix microarray experiment will be in error. RESULTS: AffyProbeMiner is a computationally efficient platform-independent tool that uses all RefSeq mature RNA protein coding transcripts and validated complete coding sequences in GenBank to (1) regroup the individual probes into consistent probe sets and (2) remap the probe sets to the correct sets of mRNA transcripts. The individual probes are grouped into probe sets that are 'transcript-consistent' in that they hybridize to the same mRNA transcript (or transcripts) and, therefore, measure the same entity (or entities). About 65.6% of the probe sets on the HG-U133A chip were affected by the remapping. Pre-computed regrouped and remapped probe sets for many Affymetrix microarrays are made freely available at the AffyProbeMiner web site. Alternatively, we provide a web service that enables the user to perform the remapping for any type of short-oligo commercial or custom array that has an Affymetrix-format Chip Definition File (CDF). Important features that differentiate AffyProbeMiner from other approaches are flexibility in the handling of splice variants, computational efficiency, extensibility, customizability and user-friendliness of the interface. AVAILABILITY: The web interface and software (GPL open source license), are publicly-accessible at http://discover.nci.nih.gov/affyprobeminer. Barry Zeeberg, Gang Qu 0001, Akif Günes Koru, Alessandro Ferrucci, Ari B. Kahn, Michael C. Ryan, Antej Nuhanovic, Peter J. Munson, William C. Reinhold, David W. Kane, John N. Weinstein |
Bioinform. | 10 |
| 2003 | Development of Gene Ontology Tool for Biological Interpretation of Genomic and Proteomic Data
Weimin Feng, Geoffrey Wang, Barry Zeeberg, Kejiao Guo, Anthony T. Fojo, David W. Kane, William C. Reinhold, Samir Lababidi, John N. Weinstein, May D. Wang |
AMIA | 7 |