Demo Data from EDBT 2026 / reviewers in the wild / expert
Ben S. Wittner
dblp:23/6832
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2006
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1
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 · 99% Computing education · 1% | |
| Artificial intelligence
2 papers |
Deep learning architectures and training · 67% Efficient and distributed learning · 33% |
Topics — the 4 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › gene expression analysis › gene expression meta-analysis
differential expression meta-analysis |
0.1 | 1 | 2006 | RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis · Bioinform. 2006 |
Bioinformatics and computational biology
gene expression analysis |
0.1 | 1 | 2006 | RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis · Bioinform. 2006 |
Machine learning › Efficient and distributed learning
model compression |
0.0 | 1 | 1987 | Network Generality, Training Required, and Precision Required · NIPS 1987 |
Machine learning › Deep learning architectures and training › feedforward neural network
multilayer neural network |
0.0 | 1 | 1987 | Strategies for Teaching Layered Networks Classification Tasks · NIPS 1987 |
Methods — techniques the papers use, named apart from their topics
rank product · 0.1permutation test · 0.1false discovery rate · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysisabstractUNLABELLED: While meta-analysis provides a powerful tool for analyzing microarray experiments by combining data from multiple studies, it presents unique computational challenges. The Bioconductor package RankProd provides a new and intuitive tool for this purpose in detecting differentially expressed genes under two experimental conditions. The package modifies and extends the rank product method proposed by Breitling et al., [(2004) FEBS Lett., 573, 83-92] to integrate multiple microarray studies from different laboratories and/or platforms. It offers several advantages over t-test based methods and accepts pre-processed expression datasets produced from a wide variety of platforms. The significance of the detection is assessed by a non-parametric permutation test, and the associated P-value and false discovery rate (FDR) are included in the output alongside the genes that are detected by user-defined criteria. A visualization plot is provided to view actual expression levels for each gene with estimated significance measurements. AVAILABILITY: RankProd is available at Bioconductor http://www.bioconductor.org. A web-based interface will soon be available at http://cactus.salk.edu/RankProd Fangxin Hong, Rainer Breitling, Connor W. McEntee, Ben S. Wittner, Jennifer L. Nemhauser, Joanne Chory |
Bioinform. | 4 |
| 1987 | Network Generality, Training Required, and Precision Required
John S. Denker, Ben S. Wittner |
NIPS | 2 |
| 1987 | Strategies for Teaching Layered Networks Classification Tasks
Ben S. Wittner, John S. Denker |
NIPS | 1 |