Guy Amster

648 total citations
9 papers, 269 citations indexed

About

Guy Amster is a scholar working on Genetics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Guy Amster has authored 9 papers receiving a total of 269 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Genetics, 3 papers in Molecular Biology and 3 papers in Artificial Intelligence. Recurrent topics in Guy Amster's work include Genetic diversity and population structure (5 papers), Evolution and Genetic Dynamics (5 papers) and Machine Learning in Healthcare (3 papers). Guy Amster is often cited by papers focused on Genetic diversity and population structure (5 papers), Evolution and Genetic Dynamics (5 papers) and Machine Learning in Healthcare (3 papers). Guy Amster collaborates with scholars based in United States and United Kingdom. Guy Amster's co-authors include Guy Sella, Lynn B. Jorde, Thomas A. Sasani, Aaron R. Quinlan, Brent S. Pedersen, Ziyue Gao, Molly Przeworski, Priya Moorjani, Eyal Elyashiv and Jonathan Kelly and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Genetics and eLife.

In The Last Decade

Guy Amster

7 papers receiving 264 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Guy Amster United States	5	151	108	43	33	23	9	269
Juan Antonio Rodríguez Spain	10	194 1.3×	183 1.7×	19 0.4×	37 1.1×	18 0.8×	19	425
Cameron D. Palmer United States	8	311 2.1×	175 1.6×	47 1.1×	28 0.8×	2 0.1×	11	477
Mashaal Sohail United States	7	346 2.3×	132 1.2×	24 0.6×	13 0.4×	7 0.3×	14	453
Joanna Kaplanis United Kingdom	4	167 1.1×	129 1.2×	53 1.2×	22 0.7×	3 0.1×	7	313
Boris Rebolledo‐Jaramillo Chile	9	67 0.4×	257 2.4×	23 0.5×	15 0.5×	4 0.2×	14	375
Jianghan Qu United States	6	120 0.8×	311 2.9×	52 1.2×	39 1.2×	8 0.3×	10	385
Simone Rubinacci Switzerland	10	369 2.4×	180 1.7×	67 1.6×	16 0.5×	30 1.3×	22	512
Michael Sachs Austria	6	43 0.3×	196 1.8×	11 0.3×	23 0.7×	6 0.3×	10	242
Xavier Farré Spain	7	76 0.5×	98 0.9×	11 0.3×	22 0.7×	4 0.2×	19	206
Jorge Azofeifa Costa Rica	11	200 1.3×	172 1.6×	13 0.3×	49 1.5×	3 0.1×	29	409

Countries citing papers authored by Guy Amster

Since Specialization

Citations

This map shows the geographic impact of Guy Amster'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 Guy Amster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guy Amster more than expected).

Fields of papers citing papers by Guy Amster

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guy Amster. 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 Guy Amster. The network helps show where Guy Amster may publish in the future.

Co-authorship network of co-authors of Guy Amster

This figure shows the co-authorship network connecting the top 25 collaborators of Guy Amster. A scholar is included among the top collaborators of Guy Amster based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Guy Amster. Guy Amster is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Cohen, Aaron B., et al.. (2025). Large Language Model Extraction of PD-L1 Biomarker Testing Details From Electronic Health Records. 2(2). 57–64.

2.

Cohen, Aaron B., et al.. (2024). MSR64 Using Large Language Models To Extract PD-L1 Testing Details From Electronic Health Records. Value in Health. 27(6). S271–S271.

3.

Adamson, Blythe, Jonathan Kelly, Konstantin Krismer, et al.. (2023). Approach to machine learning for extraction of real-world data variables from electronic health records. Frontiers in Pharmacology. 14. 1180962–1180962. 43 indexed citations

4.

Milligan, William, Guy Amster, & Guy Sella. (2022). The impact of genetic modifiers on variation in germline mutation rates within and among human populations. Genetics. 221(4). 4 indexed citations

5.

Elyashiv, Eyal, et al.. (2022). Broad-scale variation in human genetic diversity levels is predicted by purifying selection on coding and non-coding elements. eLife. 12. 27 indexed citations

6.

Amster, Guy & Guy Sella. (2020). Life History Effects on Neutral Diversity Levels of Autosomes and Sex Chromosomes. Genetics. 215(4). 1133–1142. 4 indexed citations

7.

Amster, Guy, et al.. (2020). Changes in life history and population size can explain the relative neutral diversity levels on X and autosomes in extant human populations. Proceedings of the National Academy of Sciences. 117(33). 20063–20069. 4 indexed citations

8.

Gao, Ziyue, Priya Moorjani, Thomas A. Sasani, et al.. (2019). Overlooked roles of DNA damage and maternal age in generating human germline mutations. Proceedings of the National Academy of Sciences. 116(19). 9491–9500. 122 indexed citations

9.

Amster, Guy & Guy Sella. (2016). Life history effects on the molecular clock of autosomes and sex chromosomes. Proceedings of the National Academy of Sciences. 113(6). 1588–1593. 65 indexed citations

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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