William E. Haskins

1.9k total citations
48 papers, 1.5k citations indexed

About

William E. Haskins is a scholar working on Molecular Biology, Spectroscopy and Neurology. According to data from OpenAlex, William E. Haskins has authored 48 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 12 papers in Spectroscopy and 11 papers in Neurology. Recurrent topics in William E. Haskins's work include Mass Spectrometry Techniques and Applications (9 papers), Traumatic Brain Injury and Neurovascular Disturbances (7 papers) and Metabolomics and Mass Spectrometry Studies (6 papers). William E. Haskins is often cited by papers focused on Mass Spectrometry Techniques and Applications (9 papers), Traumatic Brain Injury and Neurovascular Disturbances (7 papers) and Metabolomics and Mass Spectrometry Studies (6 papers). William E. Haskins collaborates with scholars based in United States, China and Mexico. William E. Haskins's co-authors include Shuming Nie, Steven R. Emory, David H. Powell, Robert T. Kennedy, Christopher J. Watson, Kevin Wang, Firas Kobeissy, Ronald L. Hayes, Nancy D. Denslow and Andrew K. Ottens and has published in prestigious journals such as Journal of the American Chemical Society, Angewandte Chemie International Edition and PLoS ONE.

In The Last Decade

William E. Haskins

48 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
William E. Haskins United States 21 735 287 280 226 172 48 1.5k
Marco Gaspari Italy 30 1.3k 1.8× 386 1.3× 387 1.4× 77 0.3× 182 1.1× 100 2.8k
Chunyu Zhao China 23 876 1.2× 51 0.2× 109 0.4× 176 0.8× 199 1.2× 68 2.3k
Marc Moniatte Switzerland 31 1.2k 1.6× 357 1.2× 133 0.5× 31 0.1× 122 0.7× 54 2.7k
András Micsonai Hungary 14 1.8k 2.4× 158 0.6× 153 0.5× 40 0.2× 358 2.1× 30 2.9k
Jeehyeon Bae South Korea 32 1.9k 2.5× 174 0.6× 293 1.0× 87 0.4× 315 1.8× 106 3.2k
Naoki Fujitani Japan 27 1.6k 2.1× 112 0.4× 58 0.2× 61 0.3× 110 0.6× 54 2.2k
Carlo Santambrogio Italy 24 612 0.8× 240 0.8× 243 0.9× 56 0.2× 288 1.7× 69 1.6k
Meritxell Teixidò Spain 29 1.8k 2.4× 54 0.2× 284 1.0× 71 0.3× 189 1.1× 80 2.8k
Hong‐Bo Pang United States 20 804 1.1× 46 0.2× 229 0.8× 33 0.1× 116 0.7× 44 1.5k

Countries citing papers authored by William E. Haskins

Since Specialization
Citations

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

Fields of papers citing papers by William E. Haskins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William E. Haskins. 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 William E. Haskins. The network helps show where William E. Haskins may publish in the future.

Co-authorship network of co-authors of William E. Haskins

This figure shows the co-authorship network connecting the top 25 collaborators of William E. Haskins. A scholar is included among the top collaborators of William E. Haskins 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 William E. Haskins. William E. Haskins 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.
Wang, Bang, Xiaoshu Pan, I‐Ting Teng, et al.. (2024). Functional Selection of Tau Oligomerization‐Inhibiting Aptamers. Angewandte Chemie International Edition. 63(18). e202402007–e202402007. 12 indexed citations
2.
Kobeissy, Firas, Deborah A. Shear, Janice Gilsdorf, et al.. (2024). The game changer: UCH-L1 and GFAP-based blood test as the first marketed in vitro diagnostic test for mild traumatic brain injury. Expert Review of Molecular Diagnostics. 24(1-2). 67–77. 24 indexed citations
3.
Yang, Zhihui, Tian Zhu, George Anis Sarkis, et al.. (2022). Characterization of Calpain and Caspase-6-Generated Glial Fibrillary Acidic Protein Breakdown Products Following Traumatic Brain Injury and Astroglial Cell Injury. International Journal of Molecular Sciences. 23(16). 8960–8960. 11 indexed citations
4.
Tsai, Tsung‐Heng, Zhiqi Hao, Qiuting Hong, et al.. (2017). Statistical characterization of therapeutic protein modifications. Scientific Reports. 7(1). 7896–7896. 3 indexed citations
5.
Raphael, Itay, Rishein Gupta, Bernard P. Arulanandam, et al.. (2017). Serum Neuroinflammatory Disease-Induced Central Nervous System Proteins Predict Clinical Onset of Experimental Autoimmune Encephalomyelitis. Frontiers in Immunology. 8. 812–812. 6 indexed citations
6.
Ortíz, Carmen, et al.. (2016). Cytotoxicity and Genotoxicity Assessment of Sandalwood Essential Oil in Human Breast Cell Lines MCF‐7 and MCF‐10A. Evidence-based Complementary and Alternative Medicine. 2016(1). 3696232–3696232. 21 indexed citations
7.
Raphael, Itay, et al.. (2014). Body fluid biomarkers in multiple sclerosis: how far we have come and how they could affect the clinic now and in the future. Expert Review of Clinical Immunology. 11(1). 69–91. 45 indexed citations
9.
Haskins, William E., et al.. (2013). Motility of Pseudomonas aeruginosa contributes to SOS-inducible biofilm formation. Research in Microbiology. 164(10). 1019–1027. 26 indexed citations
10.
Haskins, William E., et al.. (2013). Molecular Characteristics in MRI-Classified Group 1 Glioblastoma Multiforme. Frontiers in Oncology. 3. 182–182. 19 indexed citations
11.
Raphael, Itay, Swetha Mahesula, Manjushree Anjanappa, et al.. (2012). Microwave and magnetic (M2) proteomics of the experimental autoimmune encephalomyelitis animal model of multiple sclerosis. Electrophoresis. 33(24). 3810–3819. 20 indexed citations
12.
Haskins, William E., et al.. (2011). Insights on neoplastic stem cells from gel‐based proteomics of childhood germ cell tumors. Pediatric Blood & Cancer. 58(5). 722–728. 9 indexed citations
13.
Haskins, William E., et al.. (2010). Proteomic insights into the protective mechanisms of an in vitro oxidative stress model of early stage Parkinson's disease. Neuroscience Letters. 488(1). 11–16. 19 indexed citations
14.
Haskins, William E., et al.. (2010). ICPD-A New Peak Detection Algorithm for LC/MS. BMC Genomics. 11(Suppl 3). S8–S8. 9 indexed citations
15.
Zhao, Qian, et al.. (2009). The major antennal chemosensory protein of red imported fire ant workers. Insect Molecular Biology. 18(3). 395–404. 69 indexed citations
16.
Jiang, Daifeng, Harry W. Jarrett, & William E. Haskins. (2009). Methods for proteomic analysis of transcription factors. Journal of Chromatography A. 1216(41). 6881–6889. 42 indexed citations
17.
Zhang, Jianqiu, et al.. (2009). Review of Peak Detection Algorithms in Liquid-Chromatography-Mass Spectrometry. Current Genomics. 10(6). 388–401. 62 indexed citations
18.
Zamilpa, Rogelio, Rajesha Rupaimoole, Clyde F. Phelix, et al.. (2009). C-terminal fragment of transforming growth factor beta-induced protein (TGFBIp) is required for apoptosis in human osteosarcoma cells. Matrix Biology. 28(6). 347–353. 18 indexed citations
19.
Wang, Kevin, Andrew K. Ottens, William E. Haskins, et al.. (2004). Proteomics Studies of Traumatic Brain Injury. International review of neurobiology. 61. 215–240. 28 indexed citations
20.
Kennedy, Robert T., Christopher J. Watson, William E. Haskins, David H. Powell, & Robert E. Strecker. (2002). In vivo neurochemical monitoring by microdialysis and capillary separations. Current Opinion in Chemical Biology. 6(5). 659–665. 86 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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