VLDB 2026 Research / reviewers in the wild / expert
Lily Zhou
dblp:267/6686
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0002-3064-0864ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1Applied, 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 · 88% Medical and health informatics · 12% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › genomics
mitochondrial genomics |
0.6 | 1 | 2022 | MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA · Bioinform. 2022 |
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA structure analysis |
0.6 | 1 | 2022 | MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA · Bioinform. 2022 |
Medical and health informatics
clinical genomics |
0.2 | 1 | 2022 | MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA · Bioinform. 2022 |
Bioinformatics and computational biology › clinical bioinformatics
variant interpretation |
0.2 | 1 | 2022 | MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
RNA secondary structure visualization · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNAabstractSUMMARY: We present MitoVisualize, a new tool for analysis of the human mitochondrial DNA (mtDNA). MitoVisualize enables visualization of: (i) the position and effect of variants in mitochondrial transfer RNA and ribosomal RNA secondary structures alongside curated variant annotations, (ii) data across RNA structures, such as to show all positions with disease-associated variants or with post-transcriptional modifications and (iii) the position of a base, gene or region in the circular mtDNA map, such as to show the location of a large deletion. All visualizations can be easily downloaded as figures for reuse. MitoVisualize can be useful for anyone interested in exploring mtDNA variation, though is designed to facilitate mtDNA variant interpretation in particular. AVAILABILITY AND IMPLEMENTATION: MitoVisualize can be accessed via https://www.mitovisualize.org/. The source code is available at https://github.com/leklab/mito_visualize/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Nicole J. Lake, Lily Zhou, Jenny Xu, Monkol Lek |
Bioinform. | 2 |
| 2020 | Supporting children's math learning with feedback-augmented narrative technologyabstractA key challenge in education is effectively engaging children in learning activities. We investigated how a narrative story impacts engagement and learning, as well as how feedback can provide further benefits. To do so, we created an interactive, tablet-based learning platform with a multi-step math task designed using Common Core State Standards. Subjects completed a pretest and then were assigned to a condition, either one of three variations of the system (narratives, narratives with hints, and narratives with a tutoring chatbot using wizard-of-oz techniques) or a control system that has children complete the same learning task without narratives nor feedback, before the subjects completed a post test. 72 children in U.S. grades 3--5 participated. Our results showed that embedding learning activities into narratives boosted children's engagement as evaluated by coding video responses and surveys, and the integration of a tutoring chatbot improved learning outcomes on the assessment. These results provide evidence that a narrative-based tutoring system with chatbot-mediated help may support effective learning experiences for children. Sherry Ruan, Jiayu He, Rui Ying, Jonathan Burkle, Dunia Hakim, Yufeng Yin 0002, Lily Zhou, Qianyao Xu, Abdallah A. AbuHashem, Griffin Dietz, Elizabeth L. Murnane, Emma Brunskill, James A. Landay |
IDC | 8 |