Kimberly D. Chambert

12.6k total citations
8 papers, 1.0k citations indexed

About

Kimberly D. Chambert is a scholar working on Genetics, Pediatrics, Perinatology and Child Health and Molecular Biology. According to data from OpenAlex, Kimberly D. Chambert has authored 8 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Genetics, 2 papers in Pediatrics, Perinatology and Child Health and 1 paper in Molecular Biology. Recurrent topics in Kimberly D. Chambert's work include Genomic variations and chromosomal abnormalities (7 papers), Genomics and Rare Diseases (5 papers) and Genetic Associations and Epidemiology (5 papers). Kimberly D. Chambert is often cited by papers focused on Genomic variations and chromosomal abnormalities (7 papers), Genomics and Rare Diseases (5 papers) and Genetic Associations and Epidemiology (5 papers). Kimberly D. Chambert collaborates with scholars based in United States, United Kingdom and Sweden. Kimberly D. Chambert's co-authors include Steven A. McCarroll, Jennifer L. Moran, Michael O’Donovan, Michael J. Owen, James Walters, Elliott Rees, George Kirov, Lyudmila Georgieva, Alexander Richards and Sophie E. Legge and has published in prestigious journals such as Biological Psychiatry, Human Molecular Genetics and The British Journal of Psychiatry.

In The Last Decade

Kimberly D. Chambert

8 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kimberly D. Chambert United States 8 812 456 184 158 59 8 1.0k
Jacobine E. Buizer‐Voskamp Netherlands 14 507 0.6× 340 0.7× 100 0.5× 149 0.9× 85 1.4× 16 781
Rebecca Birnbaum United States 8 191 0.2× 243 0.5× 132 0.7× 126 0.8× 41 0.7× 16 607
Cyril Peter United States 12 256 0.3× 470 1.0× 57 0.3× 82 0.5× 77 1.3× 16 713
Barbara Manzi Italy 13 516 0.6× 284 0.6× 197 1.1× 633 4.0× 32 0.5× 17 979
Radhika Kandaswamy United Kingdom 13 289 0.4× 407 0.9× 96 0.5× 30 0.2× 46 0.8× 21 679
Regina Waltes Germany 13 345 0.4× 481 1.1× 71 0.4× 241 1.5× 20 0.3× 19 870
Catarina Correia Portugal 12 331 0.4× 173 0.4× 116 0.6× 352 2.2× 38 0.6× 18 639
Kamran Razi United States 12 246 0.3× 167 0.4× 239 1.3× 205 1.3× 17 0.3× 15 639
Michael J. Owen United Kingdom 5 325 0.4× 283 0.6× 132 0.7× 99 0.6× 15 0.3× 5 648
Claudia Hanses Germany 5 287 0.4× 195 0.4× 90 0.5× 48 0.3× 15 0.3× 6 508

Countries citing papers authored by Kimberly D. Chambert

Since Specialization
Citations

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

Fields of papers citing papers by Kimberly D. Chambert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kimberly D. Chambert. 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 Kimberly D. Chambert. The network helps show where Kimberly D. Chambert may publish in the future.

Co-authorship network of co-authors of Kimberly D. Chambert

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

All Works

8 of 8 papers shown
1.
Richards, Alexander, Ganna Leonenko, James Walters, et al.. (2016). Exome arrays capture polygenic rare variant contributions to schizophrenia. Human Molecular Genetics. 25(5). 1001–1007. 35 indexed citations
2.
Hubbard, Leon, Katherine E. Tansey, Dheeraj Rai, et al.. (2015). Evidence of Common Genetic Overlap Between Schizophrenia and Cognition. Schizophrenia Bulletin. 42(3). 832–842. 83 indexed citations
3.
Tansey, Katherine E., Elliott Rees, David E.J. Linden, et al.. (2015). Common alleles contribute to schizophrenia in CNV carriers. Molecular Psychiatry. 21(8). 1085–1089. 89 indexed citations
4.
Rees, Elliott, James Walters, Liz Forty, et al.. (2015). Copy number variation in bipolar disorder. Molecular Psychiatry. 21(1). 89–93. 110 indexed citations
5.
Georgieva, Lyudmila, Elliott Rees, Jennifer L. Moran, et al.. (2014). De novo CNVs in bipolar affective disorder and schizophrenia. Human Molecular Genetics. 23(24). 6677–6683. 56 indexed citations
6.
Kirov, George, Elliott Rees, James Walters, et al.. (2013). The Penetrance of Copy Number Variations for Schizophrenia and Developmental Delay. Biological Psychiatry. 75(5). 378–385. 235 indexed citations
7.
Rees, Elliott, James Walters, Lyudmila Georgieva, et al.. (2013). Analysis of copy number variations at 15 schizophrenia-associated loci. The British Journal of Psychiatry. 204(2). 108–114. 266 indexed citations
8.
Bergen, Sarah E., Colm Ó'Dúshláine, Stephan Ripke, et al.. (2012). Genome-wide association study in a Swedish population yields support for greater CNV and MHC involvement in schizophrenia compared with bipolar disorder. Molecular Psychiatry. 17(9). 880–886. 171 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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