Kevin R. Conard

1.7k total citations · 1 hit paper
7 papers, 1.3k citations indexed

About

Kevin R. Conard is a scholar working on Molecular Biology, Biomedical Engineering and Surgery. According to data from OpenAlex, Kevin R. Conard has authored 7 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Biomedical Engineering and 2 papers in Surgery. Recurrent topics in Kevin R. Conard's work include 3D Printing in Biomedical Research (3 papers), Pluripotent Stem Cells Research (2 papers) and Metabolomics and Mass Spectrometry Studies (1 paper). Kevin R. Conard is often cited by papers focused on 3D Printing in Biomedical Research (3 papers), Pluripotent Stem Cells Research (2 papers) and Metabolomics and Mass Spectrometry Studies (1 paper). Kevin R. Conard collaborates with scholars based in United States. Kevin R. Conard's co-authors include W. Travis Berggren, James A. Thomson, Mark E. Levenstein, Tenneille E. Ludwig, Jeffrey M. Jones, Christine A. Daigh, Leann Crandall, Marian S. Piekarczyk, Paul R. West and Jessica Palmer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Biotechnology and PLoS ONE.

In The Last Decade

Kevin R. Conard

7 papers receiving 1.2k citations

Hit Papers

Derivation of human embryonic stem cells in defined condi... 2006 2026 2012 2019 2006 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kevin R. Conard United States 7 1.1k 450 250 104 96 7 1.3k
Makio Saeki Japan 20 657 0.6× 98 0.2× 123 0.5× 174 1.7× 63 0.7× 52 1.1k
Deivid C. Rodrigues Brazil 18 590 0.6× 46 0.1× 105 0.4× 53 0.5× 217 2.3× 37 929
Ludi Zhang China 15 688 0.7× 172 0.4× 383 1.5× 77 0.7× 80 0.8× 45 1.2k
Nina D. Ullrich Germany 19 746 0.7× 141 0.3× 176 0.7× 123 1.2× 77 0.8× 47 1.3k
Takashi Saito Japan 18 825 0.8× 99 0.2× 102 0.4× 73 0.7× 228 2.4× 45 1.0k
Alireza Haghighi United States 15 491 0.5× 143 0.3× 200 0.8× 53 0.5× 113 1.2× 33 945
Akiko Tani Japan 13 525 0.5× 54 0.1× 81 0.3× 60 0.6× 34 0.4× 38 794
Lukas Cyganek Germany 18 685 0.7× 156 0.3× 194 0.8× 44 0.4× 24 0.3× 54 1.1k
Jessica Chadwick United States 13 482 0.5× 77 0.2× 39 0.2× 146 1.4× 37 0.4× 19 770
Liangxue Zhou China 14 271 0.3× 133 0.3× 46 0.2× 54 0.5× 73 0.8× 32 793

Countries citing papers authored by Kevin R. Conard

Since Specialization
Citations

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

Fields of papers citing papers by Kevin R. Conard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin R. Conard. 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 Kevin R. Conard. The network helps show where Kevin R. Conard may publish in the future.

Co-authorship network of co-authors of Kevin R. Conard

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

All Works

7 of 7 papers shown
1.
West, Paul R., David G. Amaral, Preeti Bais, et al.. (2014). Metabolomics as a Tool for Discovery of Biomarkers of Autism Spectrum Disorder in the Blood Plasma of Children. PLoS ONE. 9(11). e112445–e112445. 115 indexed citations
2.
Palmer, Jessica, Alan M. Smith, Laura A. Egnash, et al.. (2013). Establishment and Assessment of a New Human Embryonic Stem Cell‐Based Biomarker Assay for Developmental Toxicity Screening. Birth Defects Research Part B Developmental and Reproductive Toxicology. 98(4). 343–363. 64 indexed citations
3.
Palmer, Jessica, et al.. (2012). Metabolic Biomarkers of Prenatal Alcohol Exposure in Human Embryonic Stem Cell–Derived Neural Lineages. Alcoholism Clinical and Experimental Research. 36(8). 1314–1324. 21 indexed citations
4.
Kleinstreuer, Nicole, Alan M. Smith, Paul R. West, et al.. (2011). Identifying developmental toxicity pathways for a subset of ToxCast chemicals using human embryonic stem cells and metabolomics. Toxicology and Applied Pharmacology. 257(1). 111–121. 75 indexed citations
5.
Levenstein, Mark E., W. Travis Berggren, Ji‐Eun Lee, et al.. (2008). Secreted Proteoglycans Directly Mediate Human Embryonic Stem Cell-Basic Fibroblast Growth Factor 2 Interactions Critical for Proliferation. Stem Cells. 26(12). 3099–3107. 39 indexed citations
6.
Phanstiel, Doug, Justin Brumbaugh, W. Travis Berggren, et al.. (2008). Mass spectrometry identifies and quantifies 74 unique histone H4 isoforms in differentiating human embryonic stem cells. Proceedings of the National Academy of Sciences. 105(11). 4093–4098. 140 indexed citations
7.
Ludwig, Tenneille E., Mark E. Levenstein, Jeffrey M. Jones, et al.. (2006). Derivation of human embryonic stem cells in defined conditions. Nature Biotechnology. 24(2). 185–187. 811 indexed citations breakdown →

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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