Meng Ma

661 total citations
30 papers, 467 citations indexed

About

Meng Ma is a scholar working on Animal Science and Zoology, Genetics and Molecular Biology. According to data from OpenAlex, Meng Ma has authored 30 papers receiving a total of 467 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Animal Science and Zoology, 17 papers in Genetics and 3 papers in Molecular Biology. Recurrent topics in Meng Ma's work include Genetic and phenotypic traits in livestock (17 papers), Animal Nutrition and Physiology (17 papers) and Genetic Mapping and Diversity in Plants and Animals (11 papers). Meng Ma is often cited by papers focused on Genetic and phenotypic traits in livestock (17 papers), Animal Nutrition and Physiology (17 papers) and Genetic Mapping and Diversity in Plants and Animals (11 papers). Meng Ma collaborates with scholars based in China. Meng Ma's co-authors include Taocun Dou, Manman Shen, Kehua Wang, Liang Qu, Ning Yang, Jun Guo, Jian Lü, Congjiao Sun, Jingwei Yuan and Lujiang Qu and has published in prestigious journals such as PLoS ONE, Scientific Reports and Gene.

In The Last Decade

Meng Ma

30 papers receiving 456 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Meng Ma China	13	256	253	56	49	46	30	467
Leonardo de Oliveira Seno Brazil	14	247 1.0×	254 1.0×	31 0.6×	80 1.6×	23 0.5×	82	559
Leandro Teixeira Barbosa Brazil	10	139 0.5×	115 0.5×	59 1.1×	87 1.8×	19 0.4×	48	363
S. R. de Medeiros Brazil	13	163 0.6×	198 0.8×	65 1.2×	54 1.1×	65 1.4×	50	465
Ranga Appuhamy United States	8	78 0.3×	112 0.4×	167 3.0×	16 0.3×	54 1.2×	21	443
Saman Lashkari Denmark	11	102 0.4×	48 0.2×	51 0.9×	50 1.0×	76 1.7×	42	311
K.-H. Südekum Germany	9	118 0.5×	127 0.5×	28 0.5×	35 0.7×	25 0.5×	18	377
J. C. Xu China	7	40 0.2×	64 0.3×	38 0.7×	38 0.8×	63 1.4×	9	260
Shigeru SHIOYA Japan	12	168 0.7×	67 0.3×	22 0.4×	36 0.7×	27 0.6×	33	385
Tapas Kumar Dutta India	12	121 0.5×	60 0.2×	20 0.4×	35 0.7×	29 0.6×	73	381

Countries citing papers authored by Meng Ma

Since Specialization

Citations

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

Fields of papers citing papers by Meng Ma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meng Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Meng Ma. A scholar is included among the top collaborators of Meng Ma 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 Meng Ma. Meng Ma 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

Lü, Jian, Meng Ma, Yongfeng Li, et al.. (2025). Influence of Body Weight at the End of the Brooding Period on the Productive Performance in Hyline Brown Laying Hens from 6 to 72 Weeks of Age. Animals. 15(9). 1292–1292. 1 indexed citations

Ma, Meng, F. H. Liu, Xu Guo, & Zhi Zhai. (2024). Incorporating Lasso Regression to Physics-Informed Neural Network for Inverse PDE Problem. Computer Modeling in Engineering & Sciences. 141(1). 385–399. 5 indexed citations

Shen, Manman, et al.. (2024). Genome-wide association analysis of eggshell color of an F2 generation population reveals candidate genes in chickens. animal. 18(6). 101167–101167. 1 indexed citations

Ma, Meng, et al.. (2022). Comparison of international standards for irrigation with reclaimed water. Agricultural Water Management. 274. 107974–107974. 28 indexed citations

Lü, Jian, Liang Qu, Meng Ma, et al.. (2021). Effects of energy-restricted feeding during rearing on sexual maturation and reproductive performance of Rugao layer breeders. Poultry Science. 100(8). 101225–101225. 17 indexed citations

Qu, Liang, Manman Shen, Taocun Dou, et al.. (2020). Genome-wide association studies for mottled eggs in chickens using a high-density single-nucleotide polymorphism array. animal. 15(1). 100051–100051. 7 indexed citations

Wang, Xingguo, Yongfeng Li, Liang Qu, et al.. (2020). Lipolytic gene DAGLA is targeted by miR-223 in chicken hepatocytes. Gene. 767. 145184–145184. 3 indexed citations

Lü, Jian, et al.. (2020). Efficacy evaluation of selenium-enriched yeast in laying hens: effects on performance, egg quality, organ development, and selenium deposition. Poultry Science. 99(11). 6267–6277. 37 indexed citations

Guo, Jun, et al.. (2019). Genetic evaluation of eggshell color based on additive and dominance models in laying hens. Asian-Australasian Journal of Animal Sciences. 33(8). 1217–1223. 6 indexed citations

10.

Ma, Meng, et al.. (2018). Genome-wide association of spleen weight in layer chicken.. Zhongguo nongye Kexue. 51(6). 1213–1222. 1 indexed citations

11.

Shen, Manman, Hongyan Sun, Liang Qu, et al.. (2017). Genetic Architecture and Candidate Genes Identified for Follicle Number in Chicken. Scientific Reports. 7(1). 16412–16412. 23 indexed citations

12.

Wang, Kehua, et al.. (2017). Random regression analyses to model the longitudinal measurements of yolk proportions in the laying chicken. Poultry Science. 96(11). 3852–3857. 4 indexed citations

13.

Sun, Congjiao, Liang Qu, Manman Shen, et al.. (2017). Genetic architecture of bone quality variation in layer chickens revealed by a genome-wide association study. Scientific Reports. 7(1). 45317–45317. 38 indexed citations

14.

Shen, Manman, Liang Qu, Meng Ma, et al.. (2017). A genome-wide study to identify genes responsible for oviduct development in chickens. PLoS ONE. 12(12). e0189955–e0189955. 13 indexed citations

15.

Shen, Manman, Liang Qu, Meng Ma, et al.. (2016). Genome-Wide Association Studies for Comb Traits in Chickens. PLoS ONE. 11(7). e0159081–e0159081. 29 indexed citations

16.

Yuan, Jingwei, Taocun Dou, Meng Ma, et al.. (2015). Genetic parameters of feed efficiency traits in laying period of chickens. Poultry Science. 94(7). 1470–1475. 37 indexed citations

17.

Yuan, Jingwei, Kehua Wang, Guoqiang Yi, et al.. (2015). Genome-wide association studies for feed intake and efficiency in two laying periods of chickens. Genetics Selection Evolution. 47(1). 82–82. 65 indexed citations

18.

Yi, Guoqiang, Manman Shen, Jingwei Yuan, et al.. (2015). Genome-wide association study dissects genetic architecture underlying longitudinal egg weights in chickens. BMC Genomics. 16(1). 746–746. 45 indexed citations

19.

Guo, Jun, et al.. (2015). Estimation of genetic parameters related to eggshell strength using random regression models. British Poultry Science. 56(6). 645–650. 5 indexed citations

20.

Hou, Yukun, Wenhai Chu, & Meng Ma. (2012). Carbonaceous and nitrogenous disinfection by-product formation in the surface and ground water treatment plants using Yellow River as water source. Journal of Environmental Sciences. 24(7). 1204–1209. 35 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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