Leina Lu

5.2k total citations
20 papers, 1.1k citations indexed

About

Leina Lu is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Leina Lu has authored 20 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 9 papers in Cancer Research and 5 papers in Genetics. Recurrent topics in Leina Lu's work include Cancer-related molecular mechanisms research (7 papers), RNA Research and Splicing (7 papers) and Genomics and Chromatin Dynamics (6 papers). Leina Lu is often cited by papers focused on Cancer-related molecular mechanisms research (7 papers), RNA Research and Splicing (7 papers) and Genomics and Chromatin Dynamics (6 papers). Leina Lu collaborates with scholars based in Hong Kong, United States and China. Leina Lu's co-authors include Huating Wang, Hao Sun, Liang Zhou, Peiyong Jiang, Kun Sun, Xiaona Chen, Lijun Wang, Yu Zhao, Lijun Wang and Lijun Wang and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Nature Genetics.

In The Last Decade

Leina Lu

20 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Leina Lu Hong Kong	14	998	620	129	100	68	20	1.1k
Eva Samal United States	5	1.3k 1.3×	959 1.5×	86 0.7×	56 0.6×	20 0.3×	7	1.5k
Diana L. Ramírez‐Bergeron United States	15	450 0.5×	227 0.4×	84 0.7×	61 0.6×	57 0.8×	19	668
Shu Hu China	15	814 0.8×	570 0.9×	121 0.9×	37 0.4×	21 0.3×	45	1.1k
Baojian Liao China	11	792 0.8×	160 0.3×	171 1.3×	85 0.8×	50 0.7×	21	933
Ioannis Bantounas United Kingdom	10	542 0.5×	250 0.4×	69 0.5×	62 0.6×	26 0.4×	16	676
Fernanda Gabriella De Angelis Italy	11	648 0.6×	216 0.3×	49 0.4×	174 1.7×	51 0.8×	13	766
Suwannee Thet United States	8	865 0.9×	157 0.3×	347 2.7×	92 0.9×	63 0.9×	15	1.1k
Maura Diamond United States	11	498 0.5×	436 0.7×	36 0.3×	155 1.6×	41 0.6×	14	914
Foad J. Rouhani United Kingdom	10	746 0.7×	87 0.1×	197 1.5×	153 1.5×	80 1.2×	14	994

Countries citing papers authored by Leina Lu

Since Specialization

Citations

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

Fields of papers citing papers by Leina Lu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leina Lu

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

All Works

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20 of 20 papers shown

Zhao, Yu, Mengqi Yang, Minghui Hu, et al.. (2024). Accelerating 3D genomics data analysis with Microcket. Communications Biology. 7(1). 675–675. 2 indexed citations

Weng, Chen, Shanshan Zhang, Leina Lu, et al.. (2023). Single cell multiomic analysis reveals diabetes-associated β-cell heterogeneity driven by HNF1A. Nature Communications. 14(1). 5400–5400. 19 indexed citations

Zhang, Shanshan, Leina Lu, Jian Cui, et al.. (2022). DeepLoop robustly maps chromatin interactions from sparse allele-resolved or single-cell Hi-C data at kilobase resolution. Nature Genetics. 54(7). 1013–1025. 32 indexed citations

Lu, Leina & Fulai Jin. (2022). Easy Hi-C: A Low-Input Method for Capturing Genome Organization. Methods in molecular biology. 2599. 113–125. 1 indexed citations

Fu, Chen, Justine Ngo, Shanshan Zhang, et al.. (2022). Novel correlative analysis identifies multiple genomic variations impacting ASD with macrocephaly. Human Molecular Genetics. 32(10). 1589–1606. 3 indexed citations

Shin, Sunyoung, Donnie S. Stapleton, Kathryn L. Schueler, et al.. (2021). INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants. Genome biology. 22(1). 241–241. 4 indexed citations

Li, Yuying, Jie Yuan, Fengyuan Chen, et al.. (2020). Long noncoding RNA SAM promotes myoblast proliferation through stabilizing Sugt1 and facilitating kinetochore assembly. Nature Communications. 11(1). 2725–2725. 20 indexed citations

Fang, Zhou, Chen Weng, Haiyan Li, et al.. (2019). Single-Cell Heterogeneity Analysis and CRISPR Screen Identify Key β-Cell-Specific Disease Genes. Cell Reports. 26(11). 3132–3144.e7. 78 indexed citations

Giusti‐Rodríguez, Paola, Leina Lu, Cheynna Crowley, et al.. (2019). A CHROMATIN CATALOG FOR THE INTERPRETATION OF GENETIC ASSOCIATIONS OF PSYCHIATRIC DISORDERS. European Neuropsychopharmacology. 29. S921–S922. 1 indexed citations

10.

Chen, Xiaona, Liangqiang He, Yu Zhao, et al.. (2017). Malat1 regulates myogenic differentiation and muscle regeneration through modulating MyoD transcriptional activity. Cell Discovery. 3(1). 17002–17002. 97 indexed citations

11.

Zhou, Liang, Kun Sun, Yu Zhao, et al.. (2015). Linc-YY1 promotes myogenic differentiation and muscle regeneration through an interaction with the transcription factor YY1. Nature Communications. 6(1). 10026–10026. 156 indexed citations

12.

Sun, Kun, Leina Lu, Huating Wang, & Hao Sun. (2014). Genome-wide profiling of YY1 binding sites during skeletal myogenesis. Genomics Data. 2. 89–91. 2 indexed citations

13.

Lu, Leina, Kun Sun, Xiaona Chen, et al.. (2013). Genome‐wide survey by ChIP‐seq reveals YY1 regulation of lincRNAs in skeletal myogenesis. The EMBO Journal. 32(19). 2575–2588. 125 indexed citations

14.

Diao, Yarui, Xing Guo, Yanfeng Li, et al.. (2012). Pax3/7BP Is a Pax7- and Pax3-Binding Protein that Regulates the Proliferation of Muscle Precursor Cells by an Epigenetic Mechanism. Cell stem cell. 11(2). 231–241. 89 indexed citations

15.

Lu, Leina, Liang Zhou, Eric Z. Chen, et al.. (2012). A Novel YY1-miR-1 Regulatory Circuit in Skeletal Myogenesis Revealed by Genome-Wide Prediction of YY1-miRNA Network. PLoS ONE. 7(2). e27596–e27596. 89 indexed citations

16.

Zhou, Liang, Lijun Wang, Leina Lu, et al.. (2012). A Novel Target of MicroRNA-29, Ring1 and YY1-binding Protein (Rybp), Negatively Regulates Skeletal Myogenesis. Journal of Biological Chemistry. 287(30). 25255–25265. 80 indexed citations

17.

Zhou, Liang, Lijun Wang, Leina Lu, et al.. (2012). Inhibition of miR-29 by TGF-beta-Smad3 Signaling through Dual Mechanisms Promotes Transdifferentiation of Mouse Myoblasts into Myofibroblasts. PLoS ONE. 7(3). e33766–e33766. 122 indexed citations

18.

Yang, Yihua, Liang Zhou, Leina Lu, et al.. (2012). A novel miR-193a-5p-YY1-APC regulatory axis in human endometrioid endometrial adenocarcinoma. Oncogene. 32(29). 3432–3442. 76 indexed citations

19.

Wang, Lijun, Liang Zhou, Peiyong Jiang, et al.. (2012). Loss of miR-29 in Myoblasts Contributes to Dystrophic Muscle Pathogenesis. Molecular Therapy. 20(6). 1222–1233. 101 indexed citations

20.

Wang, Shiyan, Yingduan Cheng, Wan Du, et al.. (2012). Zinc-finger protein 545 is a novel tumour suppressor that acts by inhibiting ribosomal RNA transcription in gastric cancer. Gut. 62(6). 833–841. 51 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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