Peter S. Chines

42.3k total citations · 1 hit paper
8 papers, 1.9k citations indexed

About

Peter S. Chines is a scholar working on Molecular Biology, Genetics and Surgery. According to data from OpenAlex, Peter S. Chines has authored 8 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Genetics and 2 papers in Surgery. Recurrent topics in Peter S. Chines's work include Genetic Associations and Epidemiology (3 papers), Epigenetics and DNA Methylation (3 papers) and Liver Disease Diagnosis and Treatment (2 papers). Peter S. Chines is often cited by papers focused on Genetic Associations and Epidemiology (3 papers), Epigenetics and DNA Methylation (3 papers) and Liver Disease Diagnosis and Treatment (2 papers). Peter S. Chines collaborates with scholars based in United States and Finland. Peter S. Chines's co-authors include Michael Boehnke, Cristen J. Willer, Ryan Welch, Randall Pruim, Gonçalo R. Abecasis, Tanya M. Teslovich, Serena Sanna, Francis S. Collins, Lori L. Bonnycastle and Karen L. Mohlke and has published in prestigious journals such as Bioinformatics, Cell Metabolism and Diabetes.

In The Last Decade

Peter S. Chines

8 papers receiving 1.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

LocusZoom: regional visualization of genome-wide association scan results

2010 1.4k citations Randall Pruim, Ryan Welch et al. Bioinformatics profile →

Peers

Peter S. Chines

GENET

MB

SURGE

PHYSI

EPIDE

Ryan Welch United States

Teresa Ferreira Portugal

Jean Morrison United States

Sara L. Pulit Netherlands

Erdogan Taskesen Netherlands

Futao Zhang China

Marc A. Schaub United States

Matthew P. Johnson United States

Jimmy Z. Liu United States

Sabrina Giglio Italy

Ryan Welch United States

Peter S. Chines

871 ×0.9

GENET

794 ×1.0

MB

231 ×1.1

SURGE

168 ×1.0

PHYSI

184 ×1.1

EPIDE

Citations per year, relative to Peter S. Chines Peter S. Chines (= 1×) peers Ryan Welch

Countries citing papers authored by Peter S. Chines

Since Specialization

Citations

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

Fields of papers citing papers by Peter S. Chines

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter S. Chines. 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 Peter S. Chines. The network helps show where Peter S. Chines may publish in the future.

Co-authorship network of co-authors of Peter S. Chines

This figure shows the co-authorship network connecting the top 25 collaborators of Peter S. Chines. A scholar is included among the top collaborators of Peter S. Chines 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 Peter S. Chines. Peter S. Chines is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Lach, Francis P., Moonjung Jung, Frank X. Donovan, et al.. (2017). Somatic mosaicism of an intragenic FANCB duplication in both fibroblast and peripheral blood cells observed in a Fanconi anemia patient leads to milder phenotype. Molecular Genetics & Genomic Medicine. 6(1). 77–91. 24 indexed citations

2.

Teer, Jamie K., Lori L. Bonnycastle, Peter S. Chines, et al.. (2010). Systematic comparison of three genomic enrichment methods for massively parallel DNA sequencing. Genome Research. 20(10). 1420–1431. 155 indexed citations

3.

Pruim, Randall, Ryan Welch, Serena Sanna, et al.. (2010). LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 26(18). 2336–2337. 1426 indexed citations breakdown →

4.

Stitzel, Michael L., Praveen Sethupathy, Daniel S. Pearson, et al.. (2010). Global Epigenomic Analysis of Primary Human Pancreatic Islets Provides Insights into Type 2 Diabetes Susceptibility Loci. Cell Metabolism. 12(6). 683–683. 3 indexed citations

5.

Scott, Laura J., Lori L. Bonnycastle, Cristen J. Willer, et al.. (2006). Association of Transcription Factor 7-Like 2 (TCF7L2) Variants With Type 2 Diabetes in a Finnish Sample. Diabetes. 55(9). 2649–2653. 186 indexed citations

6.

Mohlke, Karen L., Anne Jackson, Laura J. Scott, et al.. (2005). Mitochondrial polymorphisms and susceptibility to type 2 diabetes-related traits in Finns. Human Genetics. 118(2). 245–254. 63 indexed citations

7.

Mohlke, Karen L., Kaisa Silander, Laura J. Scott, et al.. (2003). Common non-coding SNPs near the Hepatocyte Nuclear Factor-4 Alpha gene are associated with type 2 diabetes. The American Journal of Human Genetics. 73(5). 210. 2 indexed citations

8.

Mohlke, Karen L., Ethan M. Lange, Timo T. Valle, et al.. (2001). Linkage Disequilibrium Between Microsatellite Markers Extends Beyond 1 cM on Chromosome 20 in Finns. Genome Research. 11(7). 1221–1226. 63 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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