Demo Data from EDBT 2026 / reviewers in the wild / expert
Jan P. Buchmann
dblp:254/3366
· DBLP profile ↗
2ranked-venue papers
2as first author
1since 2021 · last 2021
0000-0002-6842-1229ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 2 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
2 papers |
Bioinformatics and computational biology · 56% Environmental and earth informatics · 44% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Environmental and earth informatics › biodiversity informatics
taxonomic data management |
0.5 | 1 | 2021 | Collecting and managing taxonomic data with NCBI-taxonomist · Bioinform. 2021 |
Bioinformatics and computational biology › biological database
biological database querying |
0.4 | 1 | 2019 | Entrezpy: a Python library to dynamically interact with the NCBI Entrez databases · Bioinform. 2019 |
Bioinformatics and computational biology › data integration
database integration |
0.1 | 1 | 2021 | Collecting and managing taxonomic data with NCBI-taxonomist · Bioinform. 2021 |
Methods — techniques the papers use, named apart from their topics
command-line tool · 0.5e-utilities · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Collecting and managing taxonomic data with NCBI-taxonomistabstractSUMMARY: We present NCBI-taxonomist-a command-line tool written in Python that collects and manages taxonomic data from the National Center for Biotechnology Information (NCBI). NCBI-taxonomist does not depend on a pre-downloaded taxonomic database but can store data locally. NCBI-taxonomist has six commands to map, collect, extract, resolve, import and group taxonomic data that can be linked together to create powerful analytical pipelines. Because many lifescience databases use the same taxonomic information, the data managed by NCBI-taxonomist is not limited to NCBI and can be used to find data linked to taxonomic information present in other scientific databases. AVAILABILITY AND IMPLEMENTATION: NCBI-taxonomist is implemented in Python 3 (≥3.8) and available at https://gitlab.com/janpb/ncbi-taxonomist and via PyPi (https://pypi.org/project/ncbi-taxonomist/), as a Docker container (https://gitlab.com/janpb/ncbi-taxonomist/container_registry/) and Singularity (v3.5.3) image (https://cloud.sylabs.io/library/jpb/ncbi-taxonomist). NCBI-taxonomist is licensed under the GPLv3. Jan P. Buchmann, Edward C. Holmes |
Bioinform. | 1 |
| 2019 | Entrezpy: a Python library to dynamically interact with the NCBI Entrez databasesabstractSUMMARY: Entrezpy is a Python library that automates the querying and downloading of data from the Entrez databases at National Center for Biotechnology Information by interacting with E-Utilities. Entrezpy implements complex queries by automatically creating E-Utility parameters from the results obtained that can then be used directly in subsequent queries. Entrezpy also allows the user to cache and retrieve results locally, implements interactions with all Entrez databases as part of an analysis pipeline and adjusts parameters within an ongoing query or using prior results. Entrezpy's modular design enables it to easily extend and adjust existing E-Utility functions. AVAILABILITY AND IMPLEMENTATION: Entrezpy is implemented in Python 3 (≥3.6) and depends only on the Python Standard Library. It is available via PyPi (https://pypi.org/project/entrezpy/) and at https://gitlab.com/ncbipy/entrezpy.git. Entrezpy is licensed under the LGPLv3 and also at http://entrezpy.readthedocs.io/. Jan P. Buchmann, Edward C. Holmes |
Bioinform. | 1 |