Demo Data from EDBT 2026 / reviewers in the wild / expert
Tanzeem Haque
dblp:132/3537
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, 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
1 paper |
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 › molecular informatics
cheminformatics |
0.2 | 1 | 2013 | HitPick: a web server for hit identification and target prediction of chemical screenings · Bioinform. 2013 |
Bioinformatics and computational biology › drug discovery › drug screening
hit identification |
0.2 | 1 | 2013 | HitPick: a web server for hit identification and target prediction of chemical screenings · Bioinform. 2013 |
Bioinformatics and computational biology › drug discovery
virtual screening |
0.2 | 1 | 2013 | HitPick: a web server for hit identification and target prediction of chemical screenings · Bioinform. 2013 |
Methods — techniques the papers use, named apart from their topics
naive bayes · 0.2b-score · 0.21-nearest-neighbor · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | HitPick: a web server for hit identification and target prediction of chemical screeningsabstractMOTIVATION: High-throughput phenotypic assays reveal information about the molecules that modulate biological processes, such as a disease phenotype and a signaling pathway. In these assays, the identification of hits along with their molecular targets is critical to understand the chemical activities modulating the biological system. Here, we present HitPick, a web server for identification of hits in high-throughput chemical screenings and prediction of their molecular targets. HitPick applies the B-score method for hit identification and a newly developed approach combining 1-nearest-neighbor (1NN) similarity searching and Laplacian-modified naïve Bayesian target models to predict targets of identified hits. The performance of the HitPick web server is presented and discussed. AVAILABILITY: The server can be accessed at http://mips.helmholtz-muenchen.de/proj/hitpick. CONTACT: [email protected]. Ingo Vogt, Tanzeem Haque, Monica Campillos |
Bioinform. | 3 |