Demo Data from EDBT 2026 / reviewers in the wild / expert
Benjamin D. Lee
dblp:143/9774
· DBLP profile ↗
3ranked-venue papers
3as first author
1since 2021 · last 2022
0000-0002-7133-8397ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 3 first-author · 1 since 2021
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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence analysis › sequence visualization
DNA sequence visualization |
0.4 | 1 | 2019 | Squiggle: a user-friendly two-dimensional DNA sequence visualization tool · Bioinform. 2019 |
Bioinformatics and computational biology
sequence analysis |
0.4 | 1 | 2019 | Squiggle: a user-friendly two-dimensional DNA sequence visualization tool · Bioinform. 2019 |
Methods — techniques the papers use, named apart from their topics
web-based visualization · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Ten quick tips for deep learning in biologyabstractMachine learning is a modern approach to problem-solving and task automation.In particular, machine learning is concerned with the development and applications of algorithms that Benjamin D. Lee, Anthony Gitter, Casey S. Greene, Sebastian Raschka, Finlay Maguire, Alexander J. Titus, Michael D. Kessler, Alexandra Lee, Marc G. Chevrette, Paul Allen Stewart, Thiago Britto-Borges, Evan M. Cofer, Kun-Hsing Yu, Juan Jose Carmona, Elana J. Fertig, Alexandr A. Kalinin, Brandon Signal, Benjamin J. Lengerich, Timothy J. Triche Jr., Simina M. Boca |
PLoS Comput. Biol. | 1 |
| 2019 | Squiggle: a user-friendly two-dimensional DNA sequence visualization toolabstractSUMMARY: Squiggle is a software tool that automatically generates interactive web-based two-dimensional graphical representations of raw DNA sequences. Built with ease of use in mind, Squiggle implements several prior sequence visualization algorithms and introduces novel visualization methods designed to maximize human usability. AVAILABILITY AND IMPLEMENTATION: Squiggle is written in Python 3 and freely available under the permissive MIT license. The open-source code can be downloaded from github.com/Lab41/squiggle as well as the Python Package Index. The installation instructions and user guide are available at squiggle.readthedocs.org. Benjamin D. Lee |
Bioinform. | 1 |
| 2018 | Ten simple rules for documenting scientific software
Benjamin D. Lee |
PLoS Comput. Biol. | 1 |