Tiffany E. Bias

42 total papers · 559 total citations
25 papers, 396 citations indexed

About

Tiffany E. Bias is a scholar working on Epidemiology, Infectious Diseases and Molecular Medicine. According to data from OpenAlex, Tiffany E. Bias has authored 25 papers receiving a total of 396 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Epidemiology, 10 papers in Infectious Diseases and 10 papers in Molecular Medicine. Recurrent topics in Tiffany E. Bias's work include Antibiotic Resistance in Bacteria (10 papers), Antibiotics Pharmacokinetics and Efficacy (7 papers) and Antibiotic Use and Resistance (5 papers). Tiffany E. Bias is often cited by papers focused on Antibiotic Resistance in Bacteria (10 papers), Antibiotics Pharmacokinetics and Efficacy (7 papers) and Antibiotic Use and Resistance (5 papers). Tiffany E. Bias collaborates with scholars based in United States and Australia. Tiffany E. Bias's co-authors include Alden Doyle, Elizabeth B. Hirsch, Clinton B. Mathias, Stacey Trooskin, Jeffrey Fong, Christopher L. Emery, Madeline King, Jon Hiles, Gregory Malat and Safia Kuriakose and has published in prestigious journals such as Journal of Clinical Microbiology, Antimicrobial Agents and Chemotherapy and Annals of Pharmacotherapy.

In The Last Decade

Tiffany E. Bias

24 papers receiving 390 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Tiffany E. Bias	196	175	140	101	83	25	396
Nicole Pagani	211 1.1×	203 1.2×	78 0.6×	105 1.0×	140 1.7×	23	421
T.N. Dhole	124 0.6×	154 0.9×	26 0.2×	93 0.9×	58 0.7×	20	444
Judith A. Anesi	97 0.5×	184 1.1×	58 0.4×	92 0.9×	47 0.6×	27	339
Ianick Souto Martins	224 1.1×	118 0.7×	81 0.6×	38 0.4×	63 0.8×	29	383
N. Galanakis	112 0.6×	168 1.0×	123 0.9×	62 0.6×	43 0.5×	16	366
C. K. Johnson	91 0.5×	106 0.6×	96 0.7×	66 0.7×	119 1.4×	12	390
Subasree Srinivasan	165 0.8×	148 0.8×	107 0.8×	54 0.5×	76 0.9×	18	407
Khurram Rana	131 0.7×	150 0.9×	85 0.6×	106 1.0×	64 0.8×	19	386
Concha Amador	92 0.5×	289 1.7×	31 0.2×	116 1.1×	33 0.4×	23	434
Derek N. Bremmer	95 0.5×	127 0.7×	96 0.7×	92 0.9×	114 1.4×	34	348

Countries citing papers authored by Tiffany E. Bias

Since Specialization

Citations

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

Fields of papers citing papers by Tiffany E. Bias

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tiffany E. Bias

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

All Works

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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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