Lili Xi

1.2k total citations
56 papers, 758 citations indexed

About

Lili Xi is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Lili Xi has authored 56 papers receiving a total of 758 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 15 papers in Oncology and 11 papers in Computational Theory and Mathematics. Recurrent topics in Lili Xi's work include Computational Drug Discovery Methods (11 papers), Drug Transport and Resistance Mechanisms (9 papers) and Machine Learning in Bioinformatics (8 papers). Lili Xi is often cited by papers focused on Computational Drug Discovery Methods (11 papers), Drug Transport and Resistance Mechanisms (9 papers) and Machine Learning in Bioinformatics (8 papers). Lili Xi collaborates with scholars based in China, Macao and United States. Lili Xi's co-authors include Xiaojun Yao, Huanxiang Liu, Jiazhong Li, Xinan Wu, Yuhui Wei, Huijun Sun, Juan Du, Shuyan Li, Yang Ying and Beilei Lei and has published in prestigious journals such as Scientific Reports, Chemical Engineering Journal and Physical Chemistry Chemical Physics.

In The Last Decade

Lili Xi

54 papers receiving 744 citations

Peers

Lili Xi
Comparison fields: 5 of 108
  • Molecular Biology 348
  • Computational Theory and Mathematics 144
  • Oncology 108
  • Epidemiology 79
  • Surgery 76
Replace Thomas J. Vidmar with:
Thomas J. Vidmar United States
Staffan Tavelin Sweden
Lucia Lazorova Sweden
Lili Chen China
Jonathan Cheong United States
Dieter M. Drexler United States
Chunyu Li China
Hongzong Si China
Jyoti Singh India
Hiroyuki Hirano Japan
Thomas J. Vidmar United States View profile →
Citations per field, relative to Lili Xi
Lili Xi · 1×
Citations per year, relative to Lili Xi
Lili Xi · 1×

Countries citing papers authored by Lili Xi

Since Specialization
Citations

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

Fields of papers citing papers by Lili Xi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lili Xi

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 3
3 6
4 1
5 0
6 3
7 26
8 8
9
A Practical Example of Bringing Computation to Data
1
10 39
11 6
12
Clinical effect of racecadotril tablets for acute diarrhea in adults
3
13 4
14 7
15 10
16 4
17 3
18 16
19 17
20 10

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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