Taylor Applebaum
Impact in
- Genetics top 10%
- Genomics and Rare Diseases
- Genetic Associations and Epidemiology
- Health Informatics top 10%
Papers in
-
- Coding theory and cryptography 1
-
- Finite Group Theory Research 1
- Co-authors
- Rosalia G. Schneider (3 shared papers)Demis Hassabis (3 shared papers)Pushmeet Kohli (3 shared papers)Clare Bycroft (3 shared papers)John Jumper (3 shared papers)Tobias Sargeant (3 shared papers)Alexander Pritzel (3 shared papers)Lai Hong Wong (3 shared papers)
- Journals
- Algebra & Number Theory (1 paper)Science (1 paper)Applied and Environmental Microbiology (1 paper)Zenodo (CERN European Organization for Nuclear Research) (2 papers)
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Taylor Applebaum
5 papers receiving 827 citations
Taylor Applebaum's Hit Papers
Peers
Comparison fields: 5 of 102
- Genetics 273
- Health Informatics 11
- Molecular Biology 404
- Cancer Research 67
- Aging 7
Countries citing papers authored by Taylor Applebaum
This map shows the geographic impact of Taylor Applebaum'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 Taylor Applebaum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taylor Applebaum more than expected).
Fields of papers citing papers by Taylor Applebaum
This network shows the impact of papers produced by Taylor Applebaum. 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 Taylor Applebaum. The network helps show where Taylor Applebaum may publish in the future.
Co-authors
The 23 scholars most cited alongside Taylor Applebaum, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Accurate proteome-wide missense variant effect prediction with AlphaMissense Hit paper breakdown → | 2023 | 805 |
| 2 | 2015 | 18 | |
| 3 | 2018 | 13 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 0 |
About Taylor Applebaum
Taylor Applebaum is a scholar working on Artificial Intelligence, Discrete Mathematics and Combinatorics, Signal Processing, Public Health, Environmental and Occupational Health and Genetics, having authored 6 papers that have together received 840 indexed citations. Recurring topics across this work include graph theory and CDMA systems (1 paper), Genomics and Rare Diseases (1 paper), Coding theory and cryptography (1 paper), Finite Group Theory Research (1 paper), Insect symbiosis and bacterial influences (1 paper), Mosquito-borne diseases and control (1 paper), Insect and Pesticide Research (1 paper) and Genomic variations and chromosomal abnormalities (1 paper). The work is most often cited by research in Genetics (273 citations), Health Informatics (11 citations), Molecular Biology (404 citations), Cancer Research (67 citations) and Aging (7 citations). Taylor Applebaum has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Rosalia G. Schneider, Demis Hassabis, Pushmeet Kohli, Clare Bycroft, John Jumper, Tobias Sargeant, Alexander Pritzel, Lai Hong Wong, Žiga Avsec and Jun Cheng. Their work appears in journals such as Algebra & Number Theory, Science, Applied and Environmental Microbiology and Zenodo (CERN European Organization for Nuclear 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.