Latisha Love‐Gregory

3.2k total citations · 1 hit paper
32 papers, 2.2k citations indexed

About

Latisha Love‐Gregory is a scholar working on Molecular Biology, Genetics and Epidemiology. According to data from OpenAlex, Latisha Love‐Gregory has authored 32 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Genetics and 6 papers in Epidemiology. Recurrent topics in Latisha Love‐Gregory's work include Peroxisome Proliferator-Activated Receptors (6 papers), Metabolism, Diabetes, and Cancer (5 papers) and Diabetes and associated disorders (4 papers). Latisha Love‐Gregory is often cited by papers focused on Peroxisome Proliferator-Activated Receptors (6 papers), Metabolism, Diabetes, and Cancer (5 papers) and Diabetes and associated disorders (4 papers). Latisha Love‐Gregory collaborates with scholars based in United States, United Kingdom and China. Latisha Love‐Gregory's co-authors include Nada A. Abumrad, Samuel Klein, M. Alan Permutt, Marta Yanina Pepino, Erika L. Pearce, David O’Sullivan, Hong Du, Wandy L. Beatty, Christina M. O’Neill and Yulia Ivanova and has published in prestigious journals such as Nature Immunology, Gastroenterology and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Latisha Love‐Gregory

32 papers receiving 2.2k citations

Hit Papers

Cell-intrinsic lysosomal lipolysis is essential for alter... 2014 2026 2018 2022 2014 250 500 750

Peers

Latisha Love‐Gregory
Latisha Love‐Gregory
Citations per year, relative to Latisha Love‐Gregory Latisha Love‐Gregory (= 1×) peers Arne K. Sandvik

Countries citing papers authored by Latisha Love‐Gregory

Since Specialization
Citations

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

Fields of papers citing papers by Latisha Love‐Gregory

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Latisha Love‐Gregory. 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 Latisha Love‐Gregory. The network helps show where Latisha Love‐Gregory may publish in the future.

Co-authorship network of co-authors of Latisha Love‐Gregory

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

All Works

20 of 20 papers shown
1.
Fridman, Arthur, Latisha Love‐Gregory, Radha Railkar, et al.. (2025). P-2334. Clesrovimab Binding Site Conservation on the RSV F Protein: An Evaluation of RSV Molecular Sequencing Data from 2019-2023 and GenBank Sequence Analysis. Open Forum Infectious Diseases. 12(Supplement_1). 2 indexed citations
2.
Jácome-Sosa, Miriam, Zhi‐Feng Miao, Vivek S. Peche, et al.. (2021). CD36 maintains the gastric mucosa and associates with gastric disease. Communications Biology. 4(1). 1247–1247. 13 indexed citations
3.
Perkins, Stephen J., et al.. (2021). Clinicopathologic Implications of Complement Genetic Variants in Kidney Transplantation. Frontiers in Medicine. 8. 775280–775280. 15 indexed citations
4.
Parikh, Bijal A., Latisha Love‐Gregory, Eric J. Duncavage, & Jonathan W. Heusel. (2020). Identification of challenges and a framework for implementation of the AMP/ASCO/CAP classification guidelines for reporting somatic variants. Practical Laboratory Medicine. 21. e00170–e00170. 5 indexed citations
5.
Wilson, Parker C., et al.. (2020). Beyond Panel-Based Testing: Exome Analysis Increases Sensitivity for Diagnosis of Genetic Kidney Disease. Kidney360. 1(8). 772–780. 10 indexed citations
6.
McNulty, Samantha N., Latisha Love‐Gregory, Molly C. Schroeder, et al.. (2019). Diagnostic Utility of Next-Generation Sequencing for Disorders of Somatic Mosaicism: A Five-Year Cumulative Cohort. The American Journal of Human Genetics. 105(4). 734–746. 23 indexed citations
7.
Govindan, Ramaswamy, Siddhartha Devarakonda, Deepali Jain, et al.. (2019). Cancer Genomics for the Clinician. 3 indexed citations
8.
Barbarossa, Iole Tomassini, Mehmet Hakan Özdener, Melania Melis, et al.. (2017). Variant in a common odorant-binding protein gene is associated with bitter sensitivity in people. Behavioural Brain Research. 329. 200–204. 25 indexed citations
9.
Lawson, Heather A., Mohamed A. Zayed, Elisa Fabbrini, et al.. (2017). Physiologic and genetic evidence links hemopexin to triglycerides in mice and humans. International Journal of Obesity. 41(4). 631–638. 15 indexed citations
10.
Fabbrini, Elisa, Courtney Luecking, Latisha Love‐Gregory, et al.. (2015). Physiological Mechanisms of Weight Gain−Induced Steatosis in People With Obesity. Gastroenterology. 150(1). 79–81.e2. 38 indexed citations
11.
Huang, Stanley Ching‐Cheng, Bart Everts, Yulia Ivanova, et al.. (2014). Cell-intrinsic lysosomal lipolysis is essential for alternative activation of macrophages. Nature Immunology. 15(9). 846–855. 897 indexed citations breakdown →
12.
Pepino, Marta Yanina, Latisha Love‐Gregory, Samuel Klein, & Nada A. Abumrad. (2011). The fatty acid translocase gene CD36 and lingual lipase influence oral sensitivity to fat in obese subjects. Journal of Lipid Research. 53(3). 561–566. 221 indexed citations
13.
Love‐Gregory, Latisha & Nada A. Abumrad. (2011). CD36 genetics and the metabolic complications of obesity. Current Opinion in Clinical Nutrition & Metabolic Care. 14(6). 527–534. 80 indexed citations
14.
Love‐Gregory, Latisha, Richard Sherva, Timothy Schappe, et al.. (2010). Common CD36 SNPs reduce protein expression and may contribute to a protective atherogenic profile. Human Molecular Genetics. 20(1). 193–201. 119 indexed citations
15.
Love‐Gregory, Latisha, Richard Sherva, Lingwei Sun, et al.. (2008). Variants in the CD36 gene associate with the metabolic syndrome and high-density lipoprotein cholesterol. Human Molecular Genetics. 17(11). 1695–1704. 156 indexed citations
16.
Love‐Gregory, Latisha & M. Alan Permutt. (2007). HNF4A genetic variants: role in diabetes. Current Opinion in Clinical Nutrition & Metabolic Care. 10(4). 397–402. 31 indexed citations
17.
Muller, Yunhua L., Aniello M. Infante, Robert L. Hanson, et al.. (2005). Variants in Hepatocyte Nuclear Factor 4α Are Modestly Associated With Type 2 Diabetes in Pima Indians. Diabetes. 54(10). 3035–3039. 41 indexed citations
18.
Love‐Gregory, Latisha, et al.. (2003). Forbidden knowledge. Science and Engineering Ethics. 9(3). 409–418. 2 indexed citations
19.
Love‐Gregory, Latisha, et al.. (2002). Evidence of Common Ancestry for the Maple Syrup Urine Disease (MSUD) Y438N Allele in Non-Mennonite MSUD Patients. Molecular Genetics and Metabolism. 75(1). 79–90. 10 indexed citations
20.
Wasson, J., Latisha Love‐Gregory, Gary B. Skolnick, et al.. (2002). Searching for Type 2 Diabetes Genes on Chromosome 20. Diabetes. 51(suppl_3). S308–S315. 18 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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