Demo Data from EDBT 2026 / reviewers in the wild / expert
Rudolph Rico
dblp:157/1639
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—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 · 81% Medical and health informatics · 19% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics
clinical diagnosis |
0.1 | 1 | 2015 | A Python package for parsing, validating, mapping and formatting sequence variants using HGVS nomenclature · Bioinform. 2015 |
Bioinformatics and computational biology › genomics
high-throughput sequencing |
0.1 | 1 | 2015 | A Python package for parsing, validating, mapping and formatting sequence variants using HGVS nomenclature · Bioinform. 2015 |
Methods — techniques the papers use, named apart from their topics
validation · 0.2parsing · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | A Python package for parsing, validating, mapping and formatting sequence variants using HGVS nomenclatureabstractUNLABELLED: Biological sequence variants are commonly represented in scientific literature, clinical reports and databases of variation using the mutation nomenclature guidelines endorsed by the Human Genome Variation Society (HGVS). Despite the widespread use of the standard, no freely available and comprehensive programming libraries are available. Here we report an open-source and easy-to-use Python library that facilitates the parsing, manipulation, formatting and validation of variants according to the HGVS specification. The current implementation focuses on the subset of the HGVS recommendations that precisely describe sequence-level variation relevant to the application of high-throughput sequencing to clinical diagnostics. AVAILABILITY AND IMPLEMENTATION: The package is released under the Apache 2.0 open-source license. Source code, documentation and issue tracking are available at http://bitbucket.org/hgvs/hgvs/. Python packages are available at PyPI (https://pypi.python.org/pypi/hgvs). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Reece K. Hart, Rudolph Rico, Emily Hare, John Garcia, Jody Westbrook, Vincent A. Fusaro |
Bioinform. | 2 |