Chunqiu Xia

492 total citations
10 papers, 309 citations indexed

About

Chunqiu Xia is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Chunqiu Xia has authored 10 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Computational Theory and Mathematics and 0 papers in Infectious Diseases. Recurrent topics in Chunqiu Xia's work include Protein Structure and Dynamics (8 papers), Machine Learning in Bioinformatics (5 papers) and RNA and protein synthesis mechanisms (5 papers). Chunqiu Xia is often cited by papers focused on Protein Structure and Dynamics (8 papers), Machine Learning in Bioinformatics (5 papers) and RNA and protein synthesis mechanisms (5 papers). Chunqiu Xia collaborates with scholars based in China, United States and Belgium. Chunqiu Xia's co-authors include Hong‐Bin Shen, Xiaoyong Pan, Ying Xia, Yang Yang, Aashiq H. Mirza, Ke Han, Yong Qi, Yang Zhang, Dong‐Jun Yu and Peidong Zhang and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS Computational Biology.

In The Last Decade

Chunqiu Xia

10 papers receiving 306 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chunqiu Xia China	8	271	102	35	22	17	10	309
Kunjie Fan United States	7	190 0.7×	104 1.0×	32 0.9×	5 0.2×	16 0.9×	12	248
De-Shuang Huang China	4	181 0.7×	61 0.6×	19 0.5×	14 0.6×	32 1.9×	6	214
Qijin Yin China	9	217 0.8×	70 0.7×	12 0.3×	4 0.2×	17 1.0×	11	267
Jiyun Zhou China	14	789 2.9×	102 1.0×	52 1.5×	6 0.3×	9 0.5×	22	859
Yihe Pang China	8	355 1.3×	60 0.6×	27 0.8×	10 0.5×	30 1.8×	11	401
Rabie Saidi United Kingdom	10	139 0.5×	48 0.5×	32 0.9×	8 0.4×	9 0.5×	14	231
Sangseon Lee South Korea	12	235 0.9×	93 0.9×	60 1.7×	5 0.2×	15 0.9×	40	363
Yixiao Zhai China	8	268 1.0×	48 0.5×	21 0.6×	9 0.4×	24 1.4×	15	341
Leslie O’Bray Switzerland	5	119 0.4×	44 0.4×	60 1.7×	15 0.7×	10 0.6×	5	195

Countries citing papers authored by Chunqiu Xia

Since Specialization

Citations

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

Fields of papers citing papers by Chunqiu Xia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chunqiu Xia

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

All Works

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10 of 10 papers shown

Xia, Chunqiu, et al.. (2022). High-accuracy protein model quality assessment using attention graph neural networks. Briefings in Bioinformatics. 24(2). 3 indexed citations

Xia, Chunqiu, et al.. (2022). Leveraging scaffold information to predict protein–ligand binding affinity with an empirical graph neural network. Briefings in Bioinformatics. 24(1). 15 indexed citations

Xia, Chunqiu, et al.. (2022). Fast protein structure comparison through effective representation learning with contrastive graph neural networks. PLoS Computational Biology. 18(3). e1009986–e1009986. 19 indexed citations

Xia, Ying, Chunqiu Xia, Xiaoyong Pan, & Hong‐Bin Shen. (2022). BindWeb: A web server for ligand binding residue and pocket prediction from protein structures. Protein Science. 31(12). e4462–e4462. 10 indexed citations

Xia, Ying, Chunqiu Xia, Xiaoyong Pan, & Hong‐Bin Shen. (2021). GraphBind: protein structural context embedded rules learned by hierarchical graph neural networks for recognizing nucleic-acid-binding residues. Nucleic Acids Research. 49(9). e51–e51. 106 indexed citations

Xia, Chunqiu, et al.. (2021). CoCoPRED: coiled-coil protein structural feature prediction from amino acid sequence using deep neural networks. Bioinformatics. 38(3). 720–729. 7 indexed citations

Xia, Chunqiu, Xiaoyong Pan, & Hong‐Bin Shen. (2020). Protein–ligand binding residue prediction enhancement through hybrid deep heterogeneous learning of sequence and structure data. Bioinformatics. 36(10). 3018–3027. 46 indexed citations

Xia, Chunqiu, et al.. (2020). Ab-Initio Membrane Protein Amphipathic Helix Structure Prediction Using Deep Neural Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(2). 795–805. 6 indexed citations

Pan, Xiaoyong, Yang Yang, Chunqiu Xia, Aashiq H. Mirza, & Hong‐Bin Shen. (2019). Recent methodology progress of deep learning for RNA–protein interaction prediction. Wiley Interdisciplinary Reviews - RNA. 10(6). e1544–e1544. 52 indexed citations

10.

Xia, Chunqiu, Ke Han, Yong Qi, Yang Zhang, & Dong‐Jun Yu. (2017). A Self-Training Subspace Clustering Algorithm under Low-Rank Representation for Cancer Classification on Gene Expression Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 15(4). 1315–1324. 45 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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