Jean M. Lacey

1.2k total citations
16 papers, 948 citations indexed

About

Jean M. Lacey is a scholar working on Molecular Biology, Clinical Biochemistry and Physiology. According to data from OpenAlex, Jean M. Lacey has authored 16 papers receiving a total of 948 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Clinical Biochemistry and 5 papers in Physiology. Recurrent topics in Jean M. Lacey's work include Metabolism and Genetic Disorders (5 papers), Sexual Differentiation and Disorders (4 papers) and Lysosomal Storage Disorders Research (4 papers). Jean M. Lacey is often cited by papers focused on Metabolism and Genetic Disorders (5 papers), Sexual Differentiation and Disorders (4 papers) and Lysosomal Storage Disorders Research (4 papers). Jean M. Lacey collaborates with scholars based in United States, Germany and Norway. Jean M. Lacey's co-authors include Mark J Magera, Piero Rinaldo, Dietrich Matern, H. Robert Bergen, John F. O’Brien, Bruno Casetta, Stephen Naylor, Bruno Casetta, Mark McCann and Si Houn Hahn and has published in prestigious journals such as The Journal of Clinical Endocrinology & Metabolism, Analytical Biochemistry and Clinical Chemistry.

In The Last Decade

Jean M. Lacey

16 papers receiving 921 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jean M. Lacey United States 12 499 364 224 170 150 16 948
Steven L Hillman United States 12 633 1.3× 723 2.0× 44 0.2× 209 1.2× 161 1.1× 14 1.1k
T. E. Stacey United Kingdom 18 409 0.8× 560 1.5× 67 0.3× 195 1.1× 100 0.7× 43 950
Kinya Ohta Japan 17 318 0.6× 145 0.4× 35 0.2× 64 0.4× 204 1.4× 34 955
Wolfgang Strobl Austria 16 291 0.6× 182 0.5× 220 1.0× 92 0.5× 50 0.3× 47 879
Florian B. Lagler Austria 16 280 0.6× 265 0.7× 24 0.1× 187 1.1× 168 1.1× 56 807
F. Huijing United States 19 461 0.9× 203 0.6× 55 0.2× 257 1.5× 346 2.3× 33 1.1k
Ira K. Brandt United States 15 448 0.9× 186 0.5× 49 0.2× 199 1.2× 100 0.7× 39 896
P.K. De Bree Netherlands 19 764 1.5× 382 1.0× 34 0.2× 91 0.5× 113 0.8× 44 1.1k
Silvia Funghini Italy 17 231 0.5× 219 0.6× 18 0.1× 66 0.4× 42 0.3× 36 567
T Akino Japan 24 644 1.3× 131 0.4× 32 0.1× 131 0.8× 40 0.3× 41 1.7k

Countries citing papers authored by Jean M. Lacey

Since Specialization
Citations

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

Fields of papers citing papers by Jean M. Lacey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean M. Lacey. 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 Jean M. Lacey. The network helps show where Jean M. Lacey may publish in the future.

Co-authorship network of co-authors of Jean M. Lacey

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

All Works

16 of 16 papers shown
1.
Lacey, Jean M., Lucas P. Carlstrom, Arthur E. Warrington, et al.. (2023). Cerebrospinal fluid 2-hydroxyglutarate as a monitoring biomarker for IDH-mutant gliomas. Neuro-Oncology Advances. 5(1). vdad061–vdad061. 9 indexed citations
2.
Peck, Dawn, Jean M. Lacey, Amy White, et al.. (2020). Incorporation of Second-Tier Biomarker Testing Improves the Specificity of Newborn Screening for Mucopolysaccharidosis Type I. International Journal of Neonatal Screening. 6(1). 10–10. 28 indexed citations
3.
Gavrilov, Dimitar K., Devin Oglesbee, Kimiyo Raymond, et al.. (2020). A Comparative Effectiveness Study of Newborn Screening Methods for Four Lysosomal Storage Disorders. International Journal of Neonatal Screening. 6(2). 44–44. 24 indexed citations
4.
Conboy, Erin, Silvia Tortorelli, Kim K. Nickander, et al.. (2019). Multiplex testing for the screening of lysosomal storage disease in urine: Sulfatides and glycosaminoglycan profiles in 40 cases of sulfatiduria. Molecular Genetics and Metabolism. 129(2). 106–110. 10 indexed citations
5.
Raymond, Kimiyo, Jean M. Lacey, Dietrich Matern, et al.. (2018). Mucopolysaccharides quantitation in serum by liquid chromatography-tandem mass spectrometry. Molecular Genetics and Metabolism. 123(2). S123–S123. 1 indexed citations
6.
Peck, Dawn, Jean M. Lacey, Coleman Turgeon, et al.. (2017). Precision newborn screening for lysosomal disorders. Genetics in Medicine. 20(8). 847–854. 95 indexed citations
7.
Daftary, Gaurang S., et al.. (2012). Potential of inner cell mass outgrowth and amino acid turnover as markers of quality in the in vitro fertilization laboratory. Fertility and Sterility. 98(4). 863–869.e1. 13 indexed citations
8.
Sarafoglou, Kyriakie, John H. Himes, Jean M. Lacey, et al.. (2010). Comparison of Multiple Steroid Concentrations in Serum and Dried Blood Spots throughout the Day of Patients with Congenital Adrenal Hyperplasia. Hormone Research in Paediatrics. 75(1). 19–25. 19 indexed citations
9.
Oglesbee, Devin, Jean M. Lacey, Mark J Magera, et al.. (2008). Second-Tier Test for Quantification of Alloisoleucine and Branched-Chain Amino Acids in Dried Blood Spots to Improve Newborn Screening for Maple Syrup Urine Disease (MSUD). Clinical Chemistry. 54(3). 542–549. 89 indexed citations
10.
O’Brien, John F., Jean M. Lacey, & H. Robert Bergen. (2007). Detection of Hypo‐N‐Glycosylation Using Mass Spectrometry of Transferrin. Current Protocols in Human Genetics. 54(1). Unit 17.4–Unit 17.4. 8 indexed citations
11.
Minutti, Carla, Jean M. Lacey, Mark J Magera, et al.. (2004). Steroid Profiling by Tandem Mass Spectrometry Improves the Positive Predictive Value of Newborn Screening for Congenital Adrenal Hyperplasia. The Journal of Clinical Endocrinology & Metabolism. 89(8). 3687–3693. 122 indexed citations
12.
Lacey, Jean M., Carla Minutti, Mark J Magera, et al.. (2004). Improved Specificity of Newborn Screening for Congenital Adrenal Hyperplasia by Second-Tier Steroid Profiling Using Tandem Mass Spectrometry. Clinical Chemistry. 50(3). 621–625. 168 indexed citations
13.
Bergen, H. Robert, Jean M. Lacey, John F. O’Brien, & Stephen Naylor. (2001). Online Single-Step Analysis of Blood Proteins: The Transferrin Story. Analytical Biochemistry. 296(1). 122–129. 30 indexed citations
14.
Kao, Pai C., Dwaine Machacek, Mark J Magera, Jean M. Lacey, & Piero Rinaldo. (2001). Diagnosis of adrenal cortical dysfunction by liquid chromatography-tandem mass spectrometry.. PubMed. 31(2). 199–204. 48 indexed citations
15.
Lacey, Jean M., H. Robert Bergen, Mark J Magera, Stephen Naylor, & John F. O’Brien. (2001). Rapid Determination of Transferrin Isoforms by Immunoaffinity Liquid Chromatography and Electrospray Mass Spectrometry. Clinical Chemistry. 47(3). 513–518. 140 indexed citations
16.
Magera, Mark J, Jean M. Lacey, Bruno Casetta, & Piero Rinaldo. (1999). Method for the Determination of Total Homocysteine in Plasma and Urine by Stable Isotope Dilution and Electrospray Tandem Mass Spectrometry. Clinical Chemistry. 45(9). 1517–1522. 144 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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