Md Liakat Ali

4.3k total citations · 1 hit paper
54 papers, 2.9k citations indexed

About

Md Liakat Ali is a scholar working on Plant Science, Genetics and Information Systems. According to data from OpenAlex, Md Liakat Ali has authored 54 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Plant Science, 20 papers in Genetics and 7 papers in Information Systems. Recurrent topics in Md Liakat Ali's work include Genetic Mapping and Diversity in Plants and Animals (19 papers), Soybean genetics and cultivation (13 papers) and Rice Cultivation and Yield Improvement (13 papers). Md Liakat Ali is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (19 papers), Soybean genetics and cultivation (13 papers) and Rice Cultivation and Yield Improvement (13 papers). Md Liakat Ali collaborates with scholars based in United States, Philippines and Bangladesh. Md Liakat Ali's co-authors include Georgia C. Eizenga, Anna M. McClung, Susan R. McCouch, Mark H. Wright, Andy Reynolds, Chih‐Wei Tung, Keyan Zhao, Carlos D. Bustamante, Gareth J. Norton and Adam H. Price and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Md Liakat Ali

50 papers receiving 2.8k citations

Hit Papers

Genome-wide association m... 2011 2026 2016 2021 2011 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Md Liakat Ali United States 22 2.4k 1.5k 350 201 136 54 2.9k
David Grant United States 26 3.5k 1.4× 1.3k 0.9× 1.2k 3.3× 244 1.2× 61 0.4× 41 4.2k
Aili Li China 31 2.7k 1.1× 421 0.3× 1.4k 4.1× 158 0.8× 26 0.2× 67 3.1k
Xiaohui Yuan China 27 1.7k 0.7× 728 0.5× 610 1.7× 293 1.5× 66 0.5× 58 2.8k
Asheesh K. Singh United States 35 4.1k 1.7× 720 0.5× 397 1.1× 298 1.5× 1.0k 7.7× 130 4.9k
K. F. Schertz United States 24 1.6k 0.6× 1.0k 0.7× 612 1.7× 753 3.7× 46 0.3× 124 2.4k
Jens Keilwagen Germany 26 1.3k 0.6× 573 0.4× 1.7k 5.0× 48 0.2× 142 1.0× 77 2.9k
Tongming Yin China 28 1.2k 0.5× 473 0.3× 1.3k 3.8× 248 1.2× 80 0.6× 150 2.5k
Yuan Zhang China 19 431 0.2× 510 0.3× 439 1.3× 187 0.9× 40 0.3× 135 1.5k
Christian Klukas Germany 28 1.9k 0.8× 417 0.3× 1.2k 3.3× 133 0.7× 547 4.0× 56 3.1k
William D. Beavis United States 26 2.6k 1.1× 1.8k 1.2× 568 1.6× 288 1.4× 64 0.5× 60 3.3k

Countries citing papers authored by Md Liakat Ali

Since Specialization
Citations

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

Fields of papers citing papers by Md Liakat Ali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Md Liakat Ali. 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 Md Liakat Ali. The network helps show where Md Liakat Ali may publish in the future.

Co-authorship network of co-authors of Md Liakat Ali

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

All Works

20 of 20 papers shown
1.
Chen, Pengyin, Grover Shannon, Caio Canella Vieira, et al.. (2024). Registration of ‘S16‐16641R’: A glyphosate‐tolerant, high‐oleic soybean cultivar with multiple disease resistance. Journal of Plant Registrations. 18(1). 78–88.
2.
Eizenga, Georgia C., Ehsan Shakiba, Jeremy D. Edwards, et al.. (2023). Yield component QTLs identified by genome‐wide association mapping validated in a diverse tropical japonica × tropical japonica rice biparental mapping population. Crop Science. 63(4). 2371–2392. 1 indexed citations
3.
Shannon, Grover, Caio Canella Vieira, Md Liakat Ali, et al.. (2022). Registration of ‘S11‐16653C’ soybean: A high‐yielding conventional cultivar with broad resistance to diseases and nematodes. Journal of Plant Registrations. 17(1). 56–66.
4.
Zhou, Jing, Jing Zhou, Jianfeng Zhou, et al.. (2021). Qualification of Soybean Responses to Flooding Stress Using UAV-Based Imagery and Deep Learning. Plant Phenomics. 2021. 9892570–9892570. 37 indexed citations
5.
Islam, Md. Atiqul, et al.. (2021). Endoscopic Evaluation of Dyspeptic Patients. 12(1). 9–14.
6.
Chen, P., Grover Shannon, Andrew Scaboo, et al.. (2021). Registration of ‘S13‐3851C’ soybean as a high‐yielding conventional cultivar with high oil content and broad disease resistance and adaptation. Journal of Plant Registrations. 16(1). 21–28. 6 indexed citations
7.
Zhou, Jing, Jing Zhou, Jianfeng Zhou, et al.. (2020). Classification of soybean leaf wilting due to drought stress using UAV-based imagery. Computers and Electronics in Agriculture. 175. 105576–105576. 86 indexed citations
8.
Dai, Wenyun, et al.. (2020). DASC: A Privacy-Protected Data Access System with Cache Mechanism for Smartphones. 7. 1–6. 2 indexed citations
9.
Ali, Md Liakat & Charles C. Tappert. (2018). POHMM/SVM: A Hybrid Approach for Keystroke Biometric User Authentication. 612–617. 11 indexed citations
10.
Eizenga, Georgia C., Melissa H. Jia, Aaron K. Jackson, et al.. (2018). Validation of Yield Component Traits Identified by Genome‐Wide Association Mapping in a tropical japonica × tropical japonica Rice Biparental Mapping Population. The Plant Genome. 12(1). 14 indexed citations
11.
Shannon, Grover, Md Liakat Ali, Melissa G. Mitchum, et al.. (2018). Registration of ‘MO 5301D CONV’ Soybean. Journal of Plant Registrations. 13(2). 148–153. 2 indexed citations
12.
Thakur, Kutub, et al.. (2017). Cloud Computing and its Security Issues. 2(1). 1–10. 12 indexed citations
13.
Ali, Md Liakat, Kutub Thakur, Charles C. Tappert, & Meikang Qiu. (2016). Keystroke Biometric User Verification Using Hidden Markov Model. 204–209. 18 indexed citations
14.
Ali, Md Liakat, et al.. (2015). Screening genetic variation in maize for deep root mass in greenhouse and its association with grain yield under water-stressed field conditions. Maydica. 60(1). 1–13. 5 indexed citations
15.
Baenziger, P. Stephen, Kulvinder S. Gill, Kent M. Eskridge, et al.. (2011). Understanding grain yield: it is a journey, not a destination. Czech Journal of Genetics and Plant Breeding. 47(Special Issue). S77–S84. 4 indexed citations
16.
McCouch, Susan R., Keyan Zhao, Mark H. Wright, et al.. (2010). Development of genome-wide SNP assays for rice. Breeding Science. 60(5). 524–535. 144 indexed citations
17.
Procunier, J. D., Gang Chen, S. L. Fox, et al.. (2009). Rapid ID Technology (RIDT) in Plants: High-Speed DNA Fingerprinting in Grain Seeds for the Identification, Segregation, Purity, and Traceability of Varieties Using Labautomation Robotics. JALA Journal of the Association for Laboratory Automation. 14(4). 221–231. 3 indexed citations
18.
Kamoshita, Akihiko, Len J. Wade, Md Liakat Ali, et al.. (2002). Mapping QTLs for root morphology of a rice population adapted to rainfed lowland conditions. Theoretical and Applied Genetics. 104(5). 880–893. 131 indexed citations
19.
Ali, Md Liakat, S. Pravin Kumar, Knut Bjørnstad, & Carlos M.G. Durán. (1996). The Sheep as an Animal Model for Heart Valve Research. Cardiovascular Surgery. 4(4). 543–549. 3 indexed citations
20.
Ali, Md Liakat, et al.. (1986). Comparative performance of four types of testers for evaluating corn inbred lines from two populations.. Crop protection newsletter. 11(3). 175–179. 3 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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