Demo Data from VLDB 2026 / reviewers in the wild / expert
Jared G. Galloway
dblp:370/5376
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0001-5838-7840ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 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 · 81% Computational science and engineering · 19% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
immunoinformatics |
0.7 | 1 | 2023 | phippery: a software suite for PhIP-Seq data analysis · Bioinform. 2023 |
Computational science and engineering › computational reproducibility
reproducible workflow |
0.2 | 1 | 2023 | phippery: a software suite for PhIP-Seq data analysis · Bioinform. 2023 |
Bioinformatics and computational biology › sequence analysis
sequencing data processing |
0.2 | 1 | 2023 | phippery: a software suite for PhIP-Seq data analysis · Bioinform. 2023 |
Methods — techniques the papers use, named apart from their topics
streamlit · 0.7nextflow · 0.7Python API · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | phippery: a software suite for PhIP-Seq data analysisabstractSUMMARY: We present the phippery software suite for analyzing data from phage display methods that use immunoprecipitation and deep sequencing to capture antibody binding to peptides, often referred to as PhIP-Seq. It has three main components that can be used separately or in conjunction: (i) a Nextflow pipeline, phip-flow, to process raw sequencing data into a compact, multidimensional dataset format and allows for end-to-end automation of reproducible workflows. (ii) a Python API, phippery, which provides interfaces for tasks such as count normalization, enrichment calculation, multidimensional scaling, and more, and (iii) a Streamlit application, phip-viz, as an interactive interface for visualizing the data as a heatmap in a flexible manner. AVAILABILITY AND IMPLEMENTATION: All software packages are publicly available under the MIT License. The phip-flow pipeline: https://github.com/matsengrp/phip-flow. The phippery library: https://github.com/matsengrp/phippery. The phip-viz Streamlit application: https://github.com/matsengrp/phip-viz. Jared G. Galloway, Kevin Sung, Samuel Schwartz Minot, Meghan E. Garrett, Caitlin I Stoddard, Alexandra C. Willcox, Zak A. Yaffe, Ryan Yucha, Julie Overbaugh, Frederick A. Matsen IV |
Bioinform. | 1 |