Demo Data from EDBT 2026 / reviewers in the wild / expert
Andrew Whalen
dblp:176/0279
· DBLP profile ↗
8ranked-venue papers
4as first author
0since 2021 · last 2020
0000-0002-6922-0947ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 8 · 4 first-authorArtificial intelligence and machine learning · 7 · 3 first-author
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 › genomics › genotyping
genotype imputation |
0.4 | 1 | 2020 | AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing data · Bioinform. 2020 |
Bioinformatics and computational biology › statistical genetics › haplotype analysis
genotype phasing |
0.4 | 1 | 2020 | AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing data · Bioinform. 2020 |
Bioinformatics and computational biology › statistical genetics › haplotype analysis
haplotype phasing |
0.4 | 1 | 2020 | AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing data · Bioinform. 2020 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.4hidden markov model · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing dataabstractSUMMARY: AlphaFamImpute is an imputation package for calling, phasing and imputing genome-wide genotypes in outbred full-sib families from single nucleotide polymorphism (SNP) array and genotype-by-sequencing (GBS) data. GBS data are increasingly being used to genotype individuals, especially when SNP arrays do not exist for a population of interest. Low-coverage GBS produces data with a large number of missing or incorrect naïve genotype calls, which can be improved by identifying shared haplotype segments between full-sib individuals. Here, we present AlphaFamImpute, an algorithm specifically designed to exploit the genetic structure of full-sib families. It performs imputation using a two-step approach. In the first step, it phases and imputes parental genotypes based on the segregation states of their offspring (i.e. which pair of parental haplotypes the offspring inherited). In the second step, it phases and imputes the offspring genotypes by detecting which haplotype segments the offspring inherited from their parents. With a series of simulations, we find that AlphaFamImpute obtains high-accuracy genotypes, even when the parents are not genotyped and individuals are sequenced at <1x coverage. AVAILABILITY AND IMPLEMENTATION: AlphaFamImpute is available as a Python package from the AlphaGenes website http://www.AlphaGenes.roslin.ed.ac.uk/AlphaFamImpute. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Andrew Whalen, Gregor Gorjanc, John M. Hickey |
Bioinform. | 1 |
| 2017 | Investigating Sensitivity to Shared Information and Personal Experience in Children's Use of Majority Information
Kay Otsubo, Andrew Whalen, Daphna Buchsbaum |
CogSci | 2 |
| 2015 | Can children balance the size of a majority with the quality of their information?
Jane C. Hu, Andrew Whalen, Daphna Buchsbaum, Thomas L. Griffiths 0001 |
CogSci | 2 |
| 2015 | Using Ground Truths to Improve Wisdom of the Crowd Estimates
Andrew Whalen, Saiwing Yeung |
CogSci | 1 |
| 2015 | Learning of bimodally distributed quantities
Saiwing Yeung, Andrew Whalen |
CogSci | 2 |
| 2014 | Cultural evolution with sparse testimony: when does the cultural ratchet slip?
Andrew Whalen, Luke Maurits, Michael Pacer, Thomas L. Griffiths 0001 |
CogSci | 1 |
| 2013 | How do you know that? Sensitivity to statistical dependency in social learning
Andrew Whalen, Daphna Buchsbaum, Thomas L. Griffiths 0001 |
CogSci | 1 |
| 2012 | Do I know that you know what you know? Modeling testimony in causal inference
Daphna Buchsbaum, Sophie Bridgers, Andrew Whalen, Elizabeth Seiver, Thomas L. Griffiths 0001, Alison Gopnik |
CogSci | 3 |