De-Chang Wu

34 total papers · 699 total citations
21 papers, 566 citations indexed

About

De-Chang Wu is a scholar working on Molecular Biology, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, De-Chang Wu has authored 21 papers receiving a total of 566 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 4 papers in Oncology and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in De-Chang Wu's work include DNA Repair Mechanisms (5 papers), TGF-β signaling in diseases (3 papers) and PI3K/AKT/mTOR signaling in cancer (3 papers). De-Chang Wu is often cited by papers focused on DNA Repair Mechanisms (5 papers), TGF-β signaling in diseases (3 papers) and PI3K/AKT/mTOR signaling in cancer (3 papers). De-Chang Wu collaborates with scholars based in China, United States and Germany. De-Chang Wu's co-authors include Ping‐Kun Zhou, Hong Wu, Jing An, Zeng‐Fu Shang, Nora Rozengurt, Xin Liu, Gertraud W. Robinson, Kay‐Uwe Wagner, Gang Li and Hilda Martinez-Diaz and has published in prestigious journals such as Journal of Biological Chemistry, Development and Biochemical and Biophysical Research Communications.

In The Last Decade

De-Chang Wu

19 papers receiving 559 citations

Author Peers

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

Author						Papers	Cites
De-Chang Wu	453	169	103	48	45	21	566
Daniela Bossi	508 1.1×	182 1.1×	101 1.0×	30 0.6×	39 0.9×	18	685
Daniela Di Marcantonio	412 0.9×	148 0.9×	66 0.6×	36 0.8×	41 0.9×	29	562
Qian Wang	539 1.2×	146 0.9×	158 1.5×	32 0.7×	67 1.5×	22	668
Tiziana Tonini	432 1.0×	229 1.4×	144 1.4×	47 1.0×	47 1.0×	15	647
Jennifer Y. Lee	430 0.9×	100 0.6×	64 0.6×	45 0.9×	45 1.0×	21	643
Hui Liang	536 1.2×	122 0.7×	131 1.3×	44 0.9×	20 0.4×	17	625
Sabita Sankar	533 1.2×	152 0.9×	155 1.5×	42 0.9×	35 0.8×	15	667
Akio Iwai	320 0.7×	121 0.7×	88 0.9×	51 1.1×	37 0.8×	17	530
Olesya Chayka	377 0.8×	210 1.2×	129 1.3×	35 0.7×	38 0.8×	17	569
M. V. Viola	303 0.7×	193 1.1×	85 0.8×	27 0.6×	67 1.5×	21	608

Countries citing papers authored by De-Chang Wu

Since Specialization

Citations

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

Fields of papers citing papers by De-Chang Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by De-Chang Wu. 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 De-Chang Wu. The network helps show where De-Chang Wu may publish in the future.

Co-authorship network of co-authors of De-Chang Wu

This figure shows the co-authorship network connecting the top 25 collaborators of De-Chang Wu. A scholar is included among the top collaborators of De-Chang Wu 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 De-Chang Wu. De-Chang Wu 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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