Christopher Yau

19.4k citations
70 papers · 3.2k · 2 hit papers · h-index 23

Impact in

Papers in

    • Single-cell and spatial transcriptomics 12
    • Gene expression and cancer classification 9
    • Gene Regulatory Network Analysis 8
    • Bayesian Methods and Mixture Models 10

Christopher Yau

68 papers receiving 3.1k citations

Christopher Yau's Hit Papers

Bayesian statistics and modelling 2021 · 616 citations
6160+3+7Years since publication200400600

Peers

Christopher Yau
Comparison fields: 5 of 200
  • Cancer Research 521
  • Biophysics 178
  • Genetics 746
  • Molecular Biology 1.6k
  • Statistics and Probability 188
Replace Guido Sanguinetti with:
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Christopher Yau relative to Guido Sanguinetti United Kingdom Guido Sanguinetti's profile →
Citations per field
00.5×2.5×
Guido Sanguinetti · 1×
Citations per year

Countries citing papers authored by Christopher Yau

Since Specialization
Citations

This map shows the geographic impact of Christopher Yau's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Christopher Yau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Yau more than expected).

Fields of papers citing papers by Christopher Yau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher Yau. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Christopher Yau. The network helps show where Christopher Yau may publish in the future.

Co-authors

The 25 scholars most cited alongside Christopher Yau, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Christopher Yau Line = papers co-authored together Christopher Yau links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Bayesian statistics and modelling
Hit paper breakdown →
2021616
2 2007400
3
ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis
Hit paper breakdown →
2015392
4 2016213
5 2013192
6 2009153
7
On the utility of graphics cards to perform massively parallel\nsimulation with advanced Monte Carlo methods.
2009151
8 2010100
9 201093
10 201073
11 201871
12 202156
13 201747
14 201245
15 200845
16 201641
17 200840
18 200838
19 201930
20 201626

About Christopher Yau

Christopher Yau is a scholar working on Molecular Biology, Artificial Intelligence, Cancer Research, Genetics and Statistics and Probability, having authored 70 papers that have together received 3.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (13 papers), Single-cell and spatial transcriptomics (12 papers), Bayesian Methods and Mixture Models (10 papers), Gene expression and cancer classification (9 papers), Gene Regulatory Network Analysis (8 papers), Genomic variations and chromosomal abnormalities (6 papers), Statistical Methods and Inference (5 papers) and Markov Chains and Monte Carlo Methods (5 papers). The work is most often cited by research in Cancer Research (521 citations), Biophysics (178 citations), Genetics (746 citations), Molecular Biology (1.6k citations) and Statistics and Probability (188 citations). Christopher Yau has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Emma Pierson, Chris Holmes, Jiannis Ragoussis, Justina Žurauskienė, Kieran R. Campbell, Kaspar Märtens, Mahlet G. Tadesse, Rens van de Schoot, Bianca Kramer and Marina Vannucci. Their work appears in journals such as Nature Communications, Bioinformatics, Nature Reviews Methods Primers, Genome biology and Cancer Research.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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