Demo Data from SIGIR 2026 / reviewers in the wild / expert
Daoyi Huang
dblp:370/5771
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
0009-0004-5545-4381ORCID · 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 · 62% Medical and health informatics · 38% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics
clinical decision support |
0.7 | 1 | 2023 | diseaseGPS: auxiliary diagnostic system for genetic disorders based on genotype and phenotype · Bioinform. 2023 |
Bioinformatics and computational biology › statistical genetics
phenotype-genotype integration |
0.7 | 1 | 2023 | diseaseGPS: auxiliary diagnostic system for genetic disorders based on genotype and phenotype · Bioinform. 2023 |
Bioinformatics and computational biology
genomics |
0.2 | 1 | 2023 | diseaseGPS: auxiliary diagnostic system for genetic disorders based on genotype and phenotype · Bioinform. 2023 |
Bioinformatics and computational biology › statistical genetics
variant prioritization |
0.2 | 1 | 2023 | diseaseGPS: auxiliary diagnostic system for genetic disorders based on genotype and phenotype · Bioinform. 2023 |
Methods — techniques the papers use, named apart from their topics
phenotypic similarity · 0.7ACMG-Bayes · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | diseaseGPS: auxiliary diagnostic system for genetic disorders based on genotype and phenotypeabstractSUMMARY: The next-generation sequencing brought opportunities for the diagnosis of genetic disorders due to its high-throughput capabilities. However, the majority of existing methods were limited to only sequencing candidate variants, and the process of linking these variants to a diagnosis of genetic disorders still required medical professionals to consult databases. Therefore, we introduce diseaseGPS, an integrated platform for the diagnosis of genetic disorders that combines both phenotype and genotype data for analysis. It offers not only a user-friendly GUI web application for those without a programming background but also scripts that can be executed in batch mode for bioinformatics professionals. The genetic and phenotypic data are integrated using the ACMG-Bayes method and a novel phenotypic similarity method, to prioritize the results of genetic disorders. diseaseGPS was evaluated on 6085 cases from Deciphering Developmental Disorders project and 187 cases from Shanghai Children's hospital. The results demonstrated that diseaseGPS performed better than other commonly used methods. AVAILABILITY AND IMPLEMENTATION: diseaseGPS is available to freely accessed at https://diseasegps.sjtu.edu.cn with source code at https://github.com/BioHuangDY/diseaseGPS. Daoyi Huang, Pin Li, Yongfen Lyu, Jincai Feng, Mingyue Wei, Zhixing Zhu, Jianlei Gu, Yongyong Ren, Guangjun Yu, Hui Lu 0004 |
Bioinform. | 1 |