VLDB 2026 Research / reviewers in the wild / expert
Harrison B. Caudill
dblp:70/8887
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2010
—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 · 100% |
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 › sequence analysis › high-throughput sequencing data analysis
deep sequencing data analysis |
0.1 | 1 | 2010 | A classification model for G-to-A hypermutation in hepatitis B virus ultra-deep pyrosequencing reads · Bioinform. 2010 |
Bioinformatics and computational biology
sequence analysis |
0.1 | 1 | 2010 | A classification model for G-to-A hypermutation in hepatitis B virus ultra-deep pyrosequencing reads · Bioinform. 2010 |
Bioinformatics and computational biology › genomics
viral genomics |
0.1 | 1 | 2010 | A classification model for G-to-A hypermutation in hepatitis B virus ultra-deep pyrosequencing reads · Bioinform. 2010 |
Methods — techniques the papers use, named apart from their topics
lethal mutation prediction · 0.1classification models · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | A classification model for G-to-A hypermutation in hepatitis B virus ultra-deep pyrosequencing readsabstractMOTIVATION: G → A hypermutation is an innate antiviral defense mechanism, mediated by host enzymes, which leads to the mutational impairment of viruses. Sensitive and specific identification of host-mediated G → A hypermutation is a novel sequence analysis challenge, particularly for viral deep sequencing studies. For example, two of the most common hepatitis B virus (HBV) reverse transcriptase (RT) drug-resistance mutations, A181T and M204I, arise from G → A changes and are routinely detected as low-abundance variants in nearly all HBV deep sequencing samples. RESULTS: We developed a classification model using measures of G → A excess and predicted indicators of lethal mutation and applied this model to 325 920 unique deep sequencing reads from plasma virus samples from 45 drug treatment-naïve HBV-infected individuals. The 2.9% of sequence reads that were classified as hypermutated by our model included most of the reads with A181T and/or M204I, indicating the usefulness of this model for distinguishing viral adaptive changes from host-mediated viral editing. AVAILABILITY: Source code and sequence data are available at http://hivdb.stanford.edu/pages/resources.html. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Elizabeth C. Reuman, Severine Margeridon-Thermet, Harrison B. Caudill, Tommy F. Liu, Katyna Borroto-Esoda, Evguenia S. Svarovskaia, Susan P. Holmes, Robert W. Shafer |
Bioinform. | 3 |