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Lina Kim

dblp:340/3389 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0002-2852-2869ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › biological database
sequence database management
0.612022
Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta)data using q2-fondue · Bioinform. 2022
Bioinformatics and computational biology
metagenomics
0.212022
Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta)data using q2-fondue · Bioinform. 2022

Methods — techniques the papers use, named apart from their topics

provenance tracking · 0.6
YearPublicationVenuePosition
2022 Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta)data using q2-fondue
abstract
MOTIVATION: The volume of public nucleotide sequence data has blossomed over the past two decades and is ripe for re- and meta-analyses to enable novel discoveries. However, reproducible re-use and management of sequence datasets and associated metadata remain critical challenges. We created the open source Python package q2-fondue to enable user-friendly acquisition, re-use and management of public sequence (meta)data while adhering to open data principles. RESULTS: q2-fondue allows fully provenance-tracked programmatic access to and management of data from the NCBI Sequence Read Archive (SRA). Unlike other packages allowing download of sequence data from the SRA, q2-fondue enables full data provenance tracking from data download to final visualization, integrates with the QIIME 2 ecosystem, prevents data loss upon space exhaustion and allows download of (meta)data given a publication library. To highlight its manifold capabilities, we present executable demonstrations using publicly available amplicon, whole genome and metagenome datasets. AVAILABILITY AND IMPLEMENTATION: q2-fondue is available as an open-source BSD-3-licensed Python package at https://github.com/bokulich-lab/q2-fondue. Usage tutorials are available in the same repository. All Jupyter notebooks used in this article are available under https://github.com/bokulich-lab/q2-fondue-examples. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Michal Ziemski, Anja Adamov, Lina Kim, Lena Flörl, Nicholas A. Bokulich
Bioinform.3