Todd Schraw

3.0k total citations · 1 hit paper
16 papers, 2.4k citations indexed

About

Todd Schraw is a scholar working on Epidemiology, Physiology and Molecular Biology. According to data from OpenAlex, Todd Schraw has authored 16 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Epidemiology, 6 papers in Physiology and 5 papers in Molecular Biology. Recurrent topics in Todd Schraw's work include Adipokines, Inflammation, and Metabolic Diseases (7 papers), Adipose Tissue and Metabolism (6 papers) and Cellular transport and secretion (5 papers). Todd Schraw is often cited by papers focused on Adipokines, Inflammation, and Metabolic Diseases (7 papers), Adipose Tissue and Metabolism (6 papers) and Cellular transport and secretion (5 papers). Todd Schraw collaborates with scholars based in United States, Denmark and United Kingdom. Todd Schraw's co-authors include Philipp E. Scherer, Jayoung Kim, Zhao V. Wang, Sidney W. Whiteheart, Nils Halberg, Gary J. Schwartz, Mark F. Mehler, Guangyu Li, Jorge L. Durand and Mathieu Laplante and has published in prestigious journals such as Journal of Clinical Investigation, Blood and Molecular and Cellular Biology.

In The Last Decade

Todd Schraw

16 papers receiving 2.4k 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.

Obesity-associated improvements in metabolic profile through expansion of adipose tissue

2007 1.0k citations Jayoung Kim, Mathieu Laplante et al. Journal of Clinical Investigation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Todd Schraw United States	13	1.3k	1.2k	650	387	327	16	2.4k
Marek Strączkowski Poland	26	815 0.6×	927 0.8×	827 1.3×	298 0.8×	154 0.5×	76	2.4k
Caroline Tao United States	14	1.4k 1.0×	1.6k 1.4×	680 1.0×	461 1.2×	190 0.6×	16	2.6k
E Ceresi Spain	10	1.7k 1.3×	1.8k 1.6×	491 0.8×	569 1.5×	155 0.5×	14	2.9k
Florian W. Kiefer Austria	25	854 0.6×	1.2k 1.0×	653 1.0×	484 1.3×	212 0.6×	60	2.5k
Kathleen R. Markan United States	16	915 0.7×	1.6k 1.4×	1.3k 2.0×	398 1.0×	210 0.6×	19	2.9k
Mengle Shao United States	32	1.7k 1.3×	2.1k 1.8×	1.1k 1.7×	543 1.4×	546 1.7×	52	3.5k
Incoronata Murano Italy	14	1.9k 1.5×	2.1k 1.8×	886 1.4×	687 1.8×	141 0.4×	15	3.6k
Eva Klimčáková France	27	898 0.7×	1.3k 1.1×	645 1.0×	392 1.0×	134 0.4×	37	2.1k
Kristina Wallenius Sweden	19	919 0.7×	989 0.8×	582 0.9×	215 0.6×	98 0.3×	37	2.2k
Robert E. McGehee United States	27	1.3k 1.0×	1.5k 1.3×	1.6k 2.5×	387 1.0×	206 0.6×	48	3.6k

Countries citing papers authored by Todd Schraw

Since Specialization

Citations

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

Fields of papers citing papers by Todd Schraw

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Todd Schraw. 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 Todd Schraw. The network helps show where Todd Schraw may publish in the future.

Co-authorship network of co-authors of Todd Schraw

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

All Works

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16 of 16 papers shown

1.

Halberg, Nils, Todd Schraw, Zhao V. Wang, et al.. (2009). Systemic Fate of the Adipocyte-Derived Factor Adiponectin. Diabetes. 58(9). 1961–1970. 169 indexed citations

2.

Wang, Zhao V., James Mu, Todd Schraw, et al.. (2008). PANIC-ATTAC: A Mouse Model for Inducible and Reversible β-Cell Ablation. Diabetes. 57(8). 2137–2148. 52 indexed citations

3.

Schraw, Todd, Zhao V. Wang, Nils Halberg, Meredith Hawkins, & Philipp E. Scherer. (2008). Plasma Adiponectin Complexes Have Distinct Biochemical Characteristics. Endocrinology. 149(5). 2270–2282. 174 indexed citations

4.

Kim, Jayoung, Mathieu Laplante, Anthony V. Azzara, et al.. (2007). Obesity-associated improvements in metabolic profile through expansion of adipose tissue. Journal of Clinical Investigation. 117(9). 2621–2637. 1035 indexed citations breakdown →

5.

Kusminski, Christine M., Philip G. McTernan, Todd Schraw, et al.. (2007). Adiponectin complexes in human cerebrospinal fluid: distinct complex distribution from serum. Diabetologia. 50(3). 634–642. 178 indexed citations

6.

Wang, Zhao V., Todd Schraw, Jayoung Kim, et al.. (2007). Secretion of the Adipocyte-Specific Secretory Protein Adiponectin Critically Depends on Thiol-Mediated Protein Retention. Molecular and Cellular Biology. 27(10). 3716–3731. 251 indexed citations

7.

Sinha, Madhur K., Qiang Xiao, John H. Sloan, et al.. (2007). Analytical Validation and Biological Evaluation of a High–Molecular-Weight Adiponectin ELISA. Clinical Chemistry. 53(12). 2144–2151. 40 indexed citations

8.

Cnop, Miriam, Josép Vidal, Rebecca L. Hull, et al.. (2007). Progressive Loss of β-Cell Function Leads to Worsening Glucose Tolerance in First-Degree Relatives of Subjects With Type 2 Diabetes. Diabetes Care. 30(3). 677–682. 139 indexed citations

9.

Semple, Robert K., Nils Halberg, Keith Burling, et al.. (2007). Paradoxical Elevation of High–Molecular Weight Adiponectin in Acquired Extreme Insulin Resistance Due to Insulin Receptor Antibodies. Diabetes. 56(6). 1712–1717. 84 indexed citations

10.

Schraw, Todd & Sidney W. Whiteheart. (2005). The development of a quantitative enzyme‐linked immunosorbent assay to detect human platelet factor 4. Transfusion. 45(5). 717–724. 8 indexed citations

11.

Schraw, Todd, et al.. (2004). Platelets from Munc18c heterozygous mice exhibit normal stimulus-induced release. Thrombosis and Haemostasis. 92(10). 829–837. 11 indexed citations

12.

Schraw, Todd, Paula P. Lemons, William L. Dean, & Sidney W. Whiteheart. (2003). A role for Sec1/Munc18 proteins in platelet exocytosis. Biochemical Journal. 374(1). 207–217. 42 indexed citations

13.

Schraw, Todd, et al.. (2003). Granule stores from cellubrevin/VAMP-3 null mouse platelets exhibit normal stimulus-induced release. Blood. 102(5). 1716–1722. 45 indexed citations

14.

Whiteheart, Sidney W., Todd Schraw, & Elena A. Matveeva. (2001). N-ethylmaleimide sensitive factor (NSF) structure and function. International review of cytology. 207. 71–112. 96 indexed citations

15.

Chen, Dong, Paula P. Lemons, Todd Schraw, & Sidney W. Whiteheart. (2000). Molecular mechanisms of platelet exocytosis: role of SNAP-23 and syntaxin 2 and 4 in lysosome release. Blood. 96(5). 1782–1788. 3 indexed citations

16.

Chen, Dong, Paula P. Lemons, Todd Schraw, & Sidney W. Whiteheart. (2000). Molecular mechanisms of platelet exocytosis: role of SNAP-23 and syntaxin 2 and 4 in lysosome release. Blood. 96(5). 1782–1788. 97 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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