Xiaoran Shang

421 total citations
9 papers, 288 citations indexed

About

Xiaoran Shang is a scholar working on Molecular Biology, Ecology and Infectious Diseases. According to data from OpenAlex, Xiaoran Shang has authored 9 papers receiving a total of 288 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Ecology and 2 papers in Infectious Diseases. Recurrent topics in Xiaoran Shang's work include Bacteriophages and microbial interactions (6 papers), Protein Structure and Dynamics (3 papers) and Bacterial Genetics and Biotechnology (2 papers). Xiaoran Shang is often cited by papers focused on Bacteriophages and microbial interactions (6 papers), Protein Structure and Dynamics (3 papers) and Bacterial Genetics and Biotechnology (2 papers). Xiaoran Shang collaborates with scholars based in United States, China and Australia. Xiaoran Shang's co-authors include Daniel Nelson, Sara B. Linden, Mona W. Orr, Fitnat H. Yildiz, Jonathan R. Goodson, Sarah R. Helman, Vincent T. Lee, Kevin Roelofs, Christopher J. Jones and Michael Y. Galperin and has published in prestigious journals such as Scientific Reports, Antimicrobial Agents and Chemotherapy and International Journal of Pharmaceutics.

In The Last Decade

Xiaoran Shang

9 papers receiving 287 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiaoran Shang United States	9	179	149	72	49	44	9	288
Diane Bona Canada	8	254 1.4×	216 1.4×	70 1.0×	44 0.9×	47 1.1×	10	349
Enea Maffei Switzerland	5	143 0.8×	166 1.1×	77 1.1×	37 0.8×	56 1.3×	7	282
Sofia Fernandes Portugal	9	155 0.9×	241 1.6×	60 0.8×	77 1.6×	16 0.4×	14	319
Chayan Kumar Saha Sweden	7	243 1.4×	107 0.7×	119 1.7×	26 0.5×	77 1.8×	9	395
Anne Caumont‐Sarcos France	10	194 1.1×	120 0.8×	76 1.1×	26 0.5×	24 0.5×	14	370
Victor Van Puyenbroeck Belgium	6	235 1.3×	264 1.8×	79 1.1×	90 1.8×	27 0.6×	6	429
Geoffrey Hutinet United States	11	303 1.7×	300 2.0×	58 0.8×	53 1.1×	45 1.0×	17	450
Steven Branston United Kingdom	8	165 0.9×	213 1.4×	58 0.8×	87 1.8×	20 0.5×	9	329
Lise Goltermann Denmark	10	238 1.3×	77 0.5×	70 1.0×	64 1.3×	36 0.8×	14	330
Maarten Boon Belgium	11	146 0.8×	199 1.3×	54 0.8×	43 0.9×	24 0.5×	23	264

Countries citing papers authored by Xiaoran Shang

Since Specialization

Citations

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

Fields of papers citing papers by Xiaoran Shang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoran Shang

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

All Works

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9 of 9 papers shown

Chao, Kinlin, et al.. (2022). Structure of Escherichia coli O157:H7 bacteriophage CBA120 tailspike protein 4 baseplate anchor and tailspike assembly domains (TSP4-N). Scientific Reports. 12(1). 2061–2061. 10 indexed citations

Moult, John, Reinhard Albrecht, Geoffrey Chang, et al.. (2021). Computational models in the service of X‐ray and cryo‐ electron microscopy structure determination. Proteins Structure Function and Bioinformatics. 89(12). 1633–1646. 31 indexed citations

Wang, Yuncheng, Dipesh Khanal, Rachel Yoon Kyung Chang, et al.. (2020). Can bacteriophage endolysins be nebulised for inhalation delivery against Streptococcus pneumoniae?. International Journal of Pharmaceutics. 591. 119982–119982. 10 indexed citations

Shang, Xiaoran, Yan Zhou, Sara B. Linden, et al.. (2020). Structure and function of bacteriophage CBA120 ORF211 (TSP2), the determinant of phage specificity towards E. coli O157:H7. Scientific Reports. 10(1). 15402–15402. 19 indexed citations

Shang, Xiaoran, et al.. (2019). Structure and tailspike glycosidase machinery of ORF212 from E. coli O157:H7 phage CBA120 (TSP3). Scientific Reports. 9(1). 7349–7349. 27 indexed citations

Shang, Xiaoran & Daniel Nelson. (2019). Contributions of Net Charge on the PlyC Endolysin CHAP Domain. Antibiotics. 8(2). 70–70. 15 indexed citations

Harhala, Marek, Daniel Nelson, Paulina Miernikiewicz, et al.. (2018). Safety Studies of Pneumococcal Endolysins Cpl-1 and Pal. Viruses. 10(11). 638–638. 44 indexed citations

Yang, Hang, Xiaoran Shang, Mengyue Wang, et al.. (2016). Antibiofilm Activities of a Novel Chimeolysin against Streptococcus mutans under Physiological and Cariogenic Conditions. Antimicrobial Agents and Chemotherapy. 60(12). 7436–7443. 40 indexed citations

Roelofs, Kevin, Christopher J. Jones, Sarah R. Helman, et al.. (2015). Systematic Identification of Cyclic-di-GMP Binding Proteins in Vibrio cholerae Reveals a Novel Class of Cyclic-di-GMP-Binding ATPases Associated with Type II Secretion Systems. PLoS Pathogens. 11(10). e1005232–e1005232. 92 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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