Chong Chu

706 total citations
11 papers, 323 citations indexed

About

Chong Chu is a scholar working on Molecular Biology, Plant Science and Artificial Intelligence. According to data from OpenAlex, Chong Chu has authored 11 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Plant Science and 2 papers in Artificial Intelligence. Recurrent topics in Chong Chu's work include Genomics and Phylogenetic Studies (10 papers), RNA and protein synthesis mechanisms (5 papers) and Gene expression and cancer classification (4 papers). Chong Chu is often cited by papers focused on Genomics and Phylogenetic Studies (10 papers), RNA and protein synthesis mechanisms (5 papers) and Gene expression and cancer classification (4 papers). Chong Chu collaborates with scholars based in United States, China and Denmark. Chong Chu's co-authors include Xiaowen Feng, Heng Li, Yufeng Wu, Rasmus Nielsen, Xin Li, Jin Zhang, Chunxue Guo, Yufeng Wu, Zijun Xiong and Xun Xu and has published in prestigious journals such as PLoS ONE, Genome biology and Molecular Biology and Evolution.

In The Last Decade

Chong Chu

10 papers receiving 318 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chong Chu United States	6	254	138	107	26	21	11	323
Nicholas Maurer United States	4	196 0.8×	109 0.8×	87 0.8×	9 0.3×	7 0.3×	6	271
Chuck McCallum United States	2	240 0.9×	89 0.6×	55 0.5×	9 0.3×	14 0.7×	2	307
Laurent Modolo France	11	309 1.2×	230 1.7×	98 0.9×	7 0.3×	7 0.3×	14	414
Maribel Hernández-Rosales Mexico	9	174 0.7×	72 0.5×	67 0.6×	22 0.8×	4 0.2×	23	274
Scott Cain United States	5	239 0.9×	101 0.7×	62 0.6×	12 0.5×	4 0.2×	9	309
Yanru Ren China	5	167 0.7×	101 0.7×	138 1.3×	9 0.3×	3 0.1×	6	288
John L. Van Hemert United States	6	202 0.8×	113 0.8×	62 0.6×	3 0.1×	15 0.7×	7	310
James P. B. Lloyd Australia	9	303 1.2×	247 1.8×	43 0.4×	7 0.3×	6 0.3×	13	427
Yannis Nevers Switzerland	8	267 1.1×	54 0.4×	89 0.8×	6 0.2×	3 0.1×	18	345
Snædís Kristmundsdóttir Iceland	7	212 0.8×	81 0.6×	166 1.6×	14 0.5×	2 0.1×	7	321

Countries citing papers authored by Chong Chu

Since Specialization

Citations

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

Fields of papers citing papers by Chong Chu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chong Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Chong Chu. A scholar is included among the top collaborators of Chong Chu 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 Chong Chu. Chong Chu 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:

11 of 11 papers shown

Li, Heng, Xiaowen Feng, & Chong Chu. (2020). The design and construction of reference pangenome graphs with minigraph. Genome biology. 21(1). 265–265. 205 indexed citations

Chu, Chong, Xin Li, & Yufeng Wu. (2019). GAPPadder: a sensitive approach for closing gaps on draft genomes with short sequence reads. BMC Genomics. 20(S5). 426–426. 15 indexed citations

Chu, Chong, et al.. (2018). An improved approach for reconstructing consensus repeats from short sequence reads. BMC Genomics. 19(S6). 566–566. 1 indexed citations

Cai, Lei, Chong Chu, Xiaodong Zhang, Yufeng Wu, & Jingyang Gao. (2017). Concod: an effective integration framework of consensus-based calling deletions from next-generation sequencing data. International Journal of Data Mining and Bioinformatics. 17(2). 153–153. 5 indexed citations

Cai, Lei, Jingyang Gao, Yufeng Wu, Xiaodong Zhang, & Chong Chu. (2017). Concod: an effective integration framework of consensus-based calling deletions from next-generation sequencing data. International Journal of Data Mining and Bioinformatics. 17(2). 153–153. 3 indexed citations

Chu, Chong, Rasmus Nielsen, & Yufeng Wu. (2016). REPdenovo: Inferring De Novo Repeat Motifs from Short Sequence Reads. PLoS ONE. 11(3). e0150719–e0150719. 35 indexed citations

Zhang, Xiaodong, Chong Chu, Yao Zhang, Yufeng Wu, & Jingyang Gao. (2016). Concod: Accurate consensus-based approach of calling deletions from high-throughput sequencing data. 72–77. 1 indexed citations

Chu, Chong, Xin Li, & Yufeng Wu. (2015). SpliceJumper: a classification-based approach for calling splicing junctions from RNA-seq data. BMC Bioinformatics. 16(S17). S10–S10. 3 indexed citations

Chu, Chong, Jin Zhang, & Yufeng Wu. (2014). GINDEL: Accurate Genotype Calling of Insertions and Deletions from Low Coverage Population Sequence Reads. PLoS ONE. 9(11). e113324–e113324. 16 indexed citations

10.

Rogers, Rebekah L., Long Zhou, Chong Chu, et al.. (2014). Genomic takeover by transposable elements in the Strawberry poison frog. Molecular Biology and Evolution. 35(12). 2913–2927. 38 indexed citations

11.

Chu, Chong & Yufeng Wu. (2014). An SVM-based approach for discovering splicing junctions with RNA-Seq. 1–1. 1 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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