Shengbo Wang

9.1k total citations · 2 hit papers
6 papers, 4.3k citations indexed

About

Shengbo Wang is a scholar working on Molecular Biology, Spectroscopy and Information Systems. According to data from OpenAlex, Shengbo Wang has authored 6 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Spectroscopy and 1 paper in Information Systems. Recurrent topics in Shengbo Wang's work include Advanced Proteomics Techniques and Applications (5 papers), Genomics and Phylogenetic Studies (2 papers) and Molecular Biology Techniques and Applications (2 papers). Shengbo Wang is often cited by papers focused on Advanced Proteomics Techniques and Applications (5 papers), Genomics and Phylogenetic Studies (2 papers) and Molecular Biology Techniques and Applications (2 papers). Shengbo Wang collaborates with scholars based in United Kingdom, Luxembourg and Germany. Shengbo Wang's co-authors include Juan Antonio Vizcaíno, Ananth Prakash, Deepti J Kundu, Selvakumar Kamatchinathan, Suresh Hewapathirana, Mathias Walzer, Yasset Pérez‐Riverol, Jingwen Bai, Chakradhar Bandla and David García‐Seisdedos and has published in prestigious journals such as Nucleic Acids Research, PLoS Computational Biology and Journal of Proteome Research.

In The Last Decade

Shengbo Wang

6 papers receiving 4.3k 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.

The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences

2021 3.9k citations Yasset Pérez‐Riverol, Jingwen Bai et al. Nucleic Acids Research profile →
The PRIDE database at 20 years: 2025 update

2024 375 citations Yasset Pérez‐Riverol, Chakradhar Bandla et al. Nucleic Acids Research profile →

Peers

Shengbo Wang

MB

IMMUN

CB

SPECT

ONCOL

Chakradhar Bandla United Kingdom

Suresh Hewapathirana United Kingdom

Deepti J Kundu United Kingdom

Selvakumar Kamatchinathan United Kingdom

David García‐Seisdedos Spain

Jingwen Bai China

Ananth Prakash United Kingdom

Mathias Walzer Germany

Tobias Ternent United Kingdom

Noemí del‐Toro United Kingdom

Chakradhar Bandla United Kingdom

Shengbo Wang

2.7k ×1.0

MB

472 ×1.0

IMMUN

451 ×1.0

CB

417 ×1.0

SPECT

358 ×1.0

ONCOL

Citations per year, relative to Shengbo Wang Shengbo Wang (= 1×) peers Chakradhar Bandla

Countries citing papers authored by Shengbo Wang

Since Specialization

Citations

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

Fields of papers citing papers by Shengbo Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shengbo Wang

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

All Works

Sort: Min cites: Since: Top N: Style:

6 of 6 papers shown

1.

Wang, Shengbo, Satwant Kaur, Benoît J. Kunath, et al.. (2025). An Approach to Integrate Metagenomics, Metatranscriptomics and Metaproteomics Data in Public Data Resources. PROTEOMICS. 25(17-18). 33–42. 1 indexed citations

2.

Pérez‐Riverol, Yasset, Chakradhar Bandla, Deepti J Kundu, et al.. (2024). The PRIDE database at 20 years: 2025 update. Nucleic Acids Research. 53(D1). D543–D553. 375 indexed citations breakdown →

3.

Wang, Shengbo, Ananth Prakash, Silvie Fexová, et al.. (2024). Integrated Proteomics Analysis of Baseline Protein Expression in Pig Tissues. Journal of Proteome Research. 23(6). 1948–1959. 4 indexed citations

4.

Wang, Shengbo, David García‐Seisdedos, Ananth Prakash, et al.. (2022). Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues. PLoS Computational Biology. 18(6). e1010174–e1010174. 9 indexed citations

5.

Prakash, Ananth, David García‐Seisdedos, Shengbo Wang, et al.. (2022). Integrated View of Baseline Protein Expression in Human Tissues. Journal of Proteome Research. 22(3). 729–742. 12 indexed citations

6.

Pérez‐Riverol, Yasset, Jingwen Bai, Chakradhar Bandla, et al.. (2021). The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences. Nucleic Acids Research. 50(D1). D543–D552. 3918 indexed citations breakdown →

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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