Brad J. Williams

545 total citations
18 papers, 452 citations indexed

About

Brad J. Williams is a scholar working on Molecular Biology, Spectroscopy and Genetics. According to data from OpenAlex, Brad J. Williams has authored 18 papers receiving a total of 452 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 10 papers in Spectroscopy and 2 papers in Genetics. Recurrent topics in Brad J. Williams's work include Advanced Proteomics Techniques and Applications (9 papers), Mass Spectrometry Techniques and Applications (9 papers) and Metabolomics and Mass Spectrometry Studies (4 papers). Brad J. Williams is often cited by papers focused on Advanced Proteomics Techniques and Applications (9 papers), Mass Spectrometry Techniques and Applications (9 papers) and Metabolomics and Mass Spectrometry Studies (4 papers). Brad J. Williams collaborates with scholars based in United States, Malaysia and Australia. Brad J. Williams's co-authors include David H. Russell, William K. Russell, Matthew Lauber, Malcolm Anderson, Catalin E. Doneanu, Asish Chakraborty, Weibin Chen, Gregory G. Martin, Friedhelm Schroeder and Ann B. Kier and has published in prestigious journals such as Analytical Chemistry, Biochemistry and Frontiers in Plant Science.

In The Last Decade

Brad J. Williams

18 papers receiving 442 citations

Peers

Brad J. Williams

SPECT

EPIDE

RNMI

Alistair V.G. Edwards Australia

Emma McGregor United Kingdom

Richard J. Mehigh United States

Lisa G. McWilliams United States

Maurice Wong United States

Eyra Marien Belgium

Daotian Fu United States

Mark J. Sartain United States

Graham J. Hughes Switzerland

Alistair V.G. Edwards Australia

Brad J. Williams

507 ×1.6

237 ×2.0

SPECT

29 ×0.7

EPIDE

56 ×1.4

RNMI

11 ×0.3

Citations per year, relative to Brad J. Williams Brad J. Williams (= 1×) peers Alistair V.G. Edwards

Countries citing papers authored by Brad J. Williams

Since Specialization

Citations

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

Fields of papers citing papers by Brad J. Williams

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brad J. Williams. 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 Brad J. Williams. The network helps show where Brad J. Williams may publish in the future.

Co-authorship network of co-authors of Brad J. Williams

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

All Works

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18 of 18 papers shown

Zenaidee, Muhammad A., et al.. (2022). Top-down mass spectrometry and assigning internal fragments for determining disulfide bond positions in proteins. The Analyst. 148(1). 26–37. 13 indexed citations

Lin, Fan, Brad J. Williams, Athena Schepmoes, et al.. (2017). Proteomics Coupled with Metabolite and Cell Wall Profiling Reveal Metabolic Processes of a Developing Rice Stem Internode. Frontiers in Plant Science. 8. 1134–1134. 17 indexed citations

Chen, Liuxi, Jaromir Mikl, Ryan M. Fryer, et al.. (2017). A Multiplatform Approach for the Discovery of Novel Drug-Induced Kidney Injury Biomarkers. Chemical Research in Toxicology. 30(10). 1823–1834. 2 indexed citations

Williams, Brad J., Steven M. Cohn, Rong Xie, et al.. (2016). Multi‐mode acquisition (MMA): An MS/MS acquisition strategy for maximizing selectivity, specificity and sensitivity of DIA product ion spectra. PROTEOMICS. 16(15-16). 2284–2301. 11 indexed citations

Nassar, Ala F., et al.. (2015). Rapid label‐free profiling of oral cancer biomarker proteins using nano‐UPLC‐Q‐TOF ion mobility mass spectrometry. PROTEOMICS - CLINICAL APPLICATIONS. 10(3). 280–289. 17 indexed citations

Doneanu, Catalin E., Malcolm Anderson, Brad J. Williams, et al.. (2015). Enhanced Detection of Low-Abundance Host Cell Protein Impurities in High-Purity Monoclonal Antibodies Down to 1 ppm Using Ion Mobility Mass Spectrometry Coupled with Multidimensional Liquid Chromatography. Analytical Chemistry. 87(20). 10283–10291. 74 indexed citations

Blandin, Gaëlle, Christophe Béroud, Véronique Labelle, et al.. (2011). UMD-DYSF, a novel locus specific database for the compilation and interactive analysis of mutations in the dysferlin gene. Human Mutation. 33(3). E2317–E2331. 36 indexed citations

Cologna, Stephanie M., Brad J. Williams, William K. Russell, et al.. (2011). Studies of Histidine As a Suitable Isoelectric Buffer for Tryptic Digestion and Isoelectric Trapping Fractionation Followed by Capillary Electrophoresis–Mass Spectrometry for Proteomic Analysis. Analytical Chemistry. 83(21). 8108–8114. 7 indexed citations

Williams, Brad J., et al.. (2011). Negative Ion Fragmentation of Cysteic Acid Containing Peptides: Cysteic Acid as a Fixed Negative Charge. Journal of the American Society for Mass Spectrometry. 22(9). 1622–1630. 10 indexed citations

10.

Williams, Brad J., et al.. (2011). Effect of Cysteic Acid Position on the Negative Ion Fragmentation of Proteolytic Derived Peptides. Journal of the American Society for Mass Spectrometry. 22(1). 31–37. 1 indexed citations

11.

Williams, Brad J., William K. Russell, & David H. Russell. (2009). High‐throughput method for on‐target performic acid oxidation of MALDI‐deposited samples. Journal of Mass Spectrometry. 45(2). 157–166. 5 indexed citations

12.

Martin, Gregory G., Barbara P. Atshaves, Huan Huang, et al.. (2009). Hepatic phenotype of liver fatty acid binding protein gene-ablated mice. American Journal of Physiology-Gastrointestinal and Liver Physiology. 297(6). G1053–G1065. 59 indexed citations

13.

Soni, Kamlesh A., Palmy Jesudhasan, Martha Cepeda, et al.. (2008). Autoinducer AI-2 Is Involved in Regulating a Variety of Cellular Processes in Salmonella Typhimurium. Foodborne Pathogens and Disease. 5(2). 147–153. 27 indexed citations

14.

Mohamedmohaideen, Nilofar N., S.K. Palaninathan, P Morin, et al.. (2008). Structure and Function of the Virulence-Associated High-Temperature Requirement A of Mycobacterium tuberculosis. Biochemistry. 47(23). 6092–6102. 53 indexed citations

15.

Martin, Gregory G., Heather A. Hostetler, Avery L. McIntosh, et al.. (2008). Structure and Function of the Sterol Carrier Protein-2 N-Terminal Presequence. Biochemistry. 47(22). 5915–5934. 38 indexed citations

16.

Soni, Kamlesh A., Palmy Jesudhasan, Martha Cepeda, et al.. (2007). Proteomic Analysis to Identify the Role of LuxS/AI-2 Mediated Protein Expression in Escherichia coli O157:H7. Foodborne Pathogens and Disease. 4(4). 463–471. 12 indexed citations

17.

Williams, Brad J., et al.. (2007). Amino acid profiling in plant cell cultures: An inter‐laboratory comparison of CE‐MS and GC‐MS. Electrophoresis. 28(9). 1371–1379. 49 indexed citations

18.

Williams, Brad J., William K. Russell, & David H. Russell. (2007). Utility of CE−MS Data in Protein Identification. Analytical Chemistry. 79(10). 3850–3855. 21 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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