K. D. Liu

860 total citations
11 papers, 679 citations indexed

About

K. D. Liu is a scholar working on Genetics, Plant Science and Molecular Biology. According to data from OpenAlex, K. D. Liu has authored 11 papers receiving a total of 679 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Genetics, 9 papers in Plant Science and 1 paper in Molecular Biology. Recurrent topics in K. D. Liu's work include Genetic Mapping and Diversity in Plants and Animals (9 papers), Rice Cultivation and Yield Improvement (8 papers) and Plant Disease Resistance and Genetics (6 papers). K. D. Liu is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (9 papers), Rice Cultivation and Yield Improvement (8 papers) and Plant Disease Resistance and Genetics (6 papers). K. D. Liu collaborates with scholars based in China and United States. K. D. Liu's co-authors include Chao Xu, Q. Zhang, Lizhong Xiong, M. A. Saghai Maroof, Qifa Zhang, X. H. Li, Jian Wang, Conghao Xu, Zhengqing Zhou and Jiaqiang Wang and has published in prestigious journals such as Theoretical and Applied Genetics, Biomedicine & Pharmacotherapy and Euphytica.

In The Last Decade

K. D. Liu

10 papers receiving 641 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
K. D. Liu China	9	589	522	154	26	18	11	679
Sang Nag Ahn South Korea	4	715 1.2×	491 0.9×	109 0.7×	24 0.9×	26 1.4×	6	758
Q. Zhang China	9	1.1k 1.8×	773 1.5×	148 1.0×	22 0.8×	45 2.5×	11	1.1k
Hanyong Yu China	15	670 1.1×	446 0.9×	126 0.8×	18 0.7×	18 1.0×	30	727
X. H. Li China	9	576 1.0×	435 0.8×	198 1.3×	14 0.5×	34 1.9×	12	648
David M. Wills United States	8	311 0.5×	195 0.4×	111 0.7×	43 1.7×	25 1.4×	10	388
Zu-Li Yang United States	9	708 1.2×	330 0.6×	134 0.9×	52 2.0×	46 2.6×	9	788
Mohamed Fergany Spain	6	419 0.7×	317 0.6×	174 1.1×	39 1.5×	7 0.4×	11	513
Katsuyuki Ichitani Japan	14	445 0.8×	288 0.6×	125 0.8×	26 1.0×	11 0.6×	39	515
José Luis Goicoechea United States	15	588 1.0×	226 0.4×	334 2.2×	42 1.6×	11 0.6×	24	678
B. C. Viraktamath India	13	532 0.9×	241 0.5×	132 0.9×	22 0.8×	12 0.7×	28	567

Countries citing papers authored by K. D. Liu

Since Specialization

Citations

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

Fields of papers citing papers by K. D. Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K. D. Liu. 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 K. D. Liu. The network helps show where K. D. Liu may publish in the future.

Co-authorship network of co-authors of K. D. Liu

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

All Works

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11 of 11 papers shown

1.

Zhang, Furong, Xiaohong Lu, Jiali Li, et al.. (2025). Identification of Immune Hub Genes in Obese Postmenopausal Women Using Microarray and Single-Cell RNA Seq Data. Genes. 16(7). 783–783.

2.

Lv, Peng, Ying Pan, Ang Li, et al.. (2024). Association of histone modification with the development of schizophrenia. Biomedicine & Pharmacotherapy. 175. 116747–116747. 4 indexed citations

3.

Xiong, Lizhong, et al.. (1999). Identification of genetic factors controlling domestication-related traits of rice using an F2 population of a cross between Oryza sativa and O. rufipogon. Theoretical and Applied Genetics. 98(2). 243–251. 214 indexed citations

4.

Wang, Jiaqiang, et al.. (1998). The high level of wide-compatibility of variety ‘Dular’ has a complex genetic basis. Theoretical and Applied Genetics. 97(3). 407–412. 68 indexed citations

5.

Zhang, Q., et al.. (1997). Molecularmarker diversity and hybrid sterility in indica-japonica rice crosses. Theoretical and Applied Genetics. 95(1-2). 112–118. 52 indexed citations

6.

Wang, Jian, et al.. (1997). Genetic basis of low-temperature-sensitive sterility in indica-japonica hybrids of rice as determined by RFLP analysis. Theoretical and Applied Genetics. 95(7). 1092–1097. 53 indexed citations

7.

Liu, K. D., et al.. (1997). A genome-wide analysis of wide compatibility in rice and the precise location of the S5 locus in the molecular map. Theoretical and Applied Genetics. 95(5-6). 809–814. 95 indexed citations

8.

Zhang, Qifa, et al.. (1996). Molecular marker heterozygosity and hybrid performance in indica and japonica rice. Theoretical and Applied Genetics. 93(8). 1218–1224. 92 indexed citations

9.

Liu, K. D., et al.. (1996). Extraordinarily polymorphic ribosomal DNA in wild and cultivated rice. Genome. 39(6). 1109–1116. 21 indexed citations

10.

Liu, K. D., et al.. (1996). An analysis of hybrid sterility in rice using a diallel cross of 21 parents involving indica, japonica and wide compatibility varieties. Euphytica. 90(3). 275–280. 60 indexed citations

11.

Xu, Conghao, et al.. (1996). Molecular marker heterozygosity and hybrid performance in indica and japonica rice. Theoretical and Applied Genetics. 93(8). 1218–1224. 20 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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