Allah Ditta

506 total citations
30 papers, 267 citations indexed

About

Allah Ditta is a scholar working on Plant Science, Molecular Biology and Endocrinology. According to data from OpenAlex, Allah Ditta has authored 30 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Plant Science, 6 papers in Molecular Biology and 4 papers in Endocrinology. Recurrent topics in Allah Ditta's work include Research in Cotton Cultivation (24 papers), Plant Virus Research Studies (11 papers) and Plant Molecular Biology Research (5 papers). Allah Ditta is often cited by papers focused on Research in Cotton Cultivation (24 papers), Plant Virus Research Studies (11 papers) and Plant Molecular Biology Research (5 papers). Allah Ditta collaborates with scholars based in Pakistan, China and United States. Allah Ditta's co-authors include Muhammad Kashif Riaz Khan, Baohua Wang, Amjad Hameed, Ghulam Farid, Fang Liu, Muhammad Akhtar, Yuqing Hou, Yanchao Xu, Xingxing Wang and Kunbo Wang and has published in prestigious journals such as International Journal of Molecular Sciences, Frontiers in Plant Science and Theoretical and Applied Genetics.

In The Last Decade

Allah Ditta

27 papers receiving 262 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Allah Ditta Pakistan 9 237 73 14 14 13 30 267
Ayaz Ali Keerio Pakistan 7 240 1.0× 72 1.0× 17 1.2× 13 0.9× 5 0.4× 11 280
Muhammad Awais Farooq Pakistan 11 329 1.4× 130 1.8× 32 2.3× 15 1.1× 13 1.0× 23 395
Masataka Aino Japan 14 502 2.1× 31 0.4× 10 0.7× 6 0.4× 10 0.8× 24 523
Muhammad Khuram Razzaq China 11 254 1.1× 128 1.8× 8 0.6× 24 1.7× 24 1.8× 22 325
F. Lanza Brazil 13 349 1.5× 38 0.5× 23 1.6× 16 1.1× 7 0.5× 35 383
Shiguftah Khalid China 5 303 1.3× 83 1.1× 26 1.9× 9 0.6× 5 0.4× 7 321
Gopal Saha Bangladesh 12 435 1.8× 248 3.4× 24 1.7× 13 0.9× 5 0.4× 28 482
Zunaira Afzal Naveed United States 6 416 1.8× 151 2.1× 7 0.5× 17 1.2× 8 0.6× 9 450
Ting Xiang Neik Australia 10 278 1.2× 80 1.1× 10 0.7× 31 2.2× 3 0.2× 23 338
Blessing Chidinma Nwachukwu South Africa 7 170 0.7× 53 0.7× 13 0.9× 5 0.4× 8 0.6× 12 232

Countries citing papers authored by Allah Ditta

Since Specialization
Citations

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

Fields of papers citing papers by Allah Ditta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Allah Ditta

This figure shows the co-authorship network connecting the top 25 collaborators of Allah Ditta. A scholar is included among the top collaborators of Allah Ditta 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 Allah Ditta. Allah Ditta 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.
2.
Khan, Muhammad Kashif Riaz, et al.. (2025). Genetic diversity and phylogenetic relationship through the use of microsatellites in Gossypium hirsutum L.. BMC Plant Biology. 25(1). 355–355.
3.
Anwar, Zunaira, Allah Ditta, & Muhammad Kashif Riaz Khan. (2025). Multivariate screening of upland cotton genotypes reveals key traits for salt tolerance at the seedling stage. BMC Plant Biology. 25(1). 1448–1448.
4.
Fang, Hui, Teame Gereziher Mehari, Ying Wu, et al.. (2024). Transcriptomic profiling reveals salt-responsive long non-coding RNAs and their putative target genes for improving salt tolerance in upland cotton (Gossypium hirsutum). Industrial Crops and Products. 216. 118744–118744. 4 indexed citations
5.
Fayyaz, Muhammad, Amjad Hameed, Rehana Kausar, et al.. (2024). Quercetin in semen extender improves frozen-thawed spermatozoa quality and in-vivo fertility in crossbred Kamori goats. Frontiers in Veterinary Science. 11. 1385642–1385642. 3 indexed citations
6.
Gong, Zhaolong, et al.. (2024). Identification and function analysis of GABA branch three gene families in the cotton related to abiotic stresses. BMC Plant Biology. 24(1). 57–57. 8 indexed citations
7.
Anwar, Zunaira, et al.. (2024). Unraveling the genetic and molecular basis of heat stress in cotton. Frontiers in Genetics. 15. 1296622–1296622. 8 indexed citations
8.
Fang, Hui, Junyi Li, Yixuan Yang, et al.. (2024). Genome-wide identification and analysis of the cotton ALDH gene family. BMC Genomics. 25(1). 513–513. 4 indexed citations
9.
Ditta, Allah, Xiaoyan Cai, Shafeeq Ur Rahman, et al.. (2023). Identification of salt stress-tolerant candidate genes in the BC2F2 population at the seedling stages of G. hirsutum and G. darwinii using NGS-based bulked segregant analysis. Frontiers in Plant Science. 14. 1125805–1125805. 1 indexed citations
10.
Anwar, Zunaira, et al.. (2023). Genomic Dynamics and Functional Insights under Salt Stress in Gossypium hirsutum L.. Genes. 14(5). 1103–1103. 13 indexed citations
11.
Deng, Tingting, Wei Wang, Yingying Tang, et al.. (2023). Genome-wide analysis of the LAZ1 gene family in Gossypium hirsutum. Molecular Biology Reports. 50(11). 9273–9282. 1 indexed citations
12.
Mehari, Teame Gereziher, Hui Fang, Jinlei Han, et al.. (2023). Transcriptome, proteome and functional characterization reveals salt stress tolerance mechanisms in upland cotton (Gossypium hirsutum L.). Frontiers in Plant Science. 14. 1092616–1092616. 8 indexed citations
13.
Gong, Zhaolong, et al.. (2023). The Correlation of Machine-Picked Cotton Defoliant in Different Gossypium hirsutum Varieties. Agronomy. 13(8). 2151–2151. 7 indexed citations
14.
Mehari, Teame Gereziher, Hui Fang, Muhammad Jawad Umer, et al.. (2023). Genome-wide identification and expression analysis of terpene synthases in Gossypium species in response to gossypol biosynthesis. Functional & Integrative Genomics. 23(2). 197–197. 7 indexed citations
15.
Wang, Baohua, et al.. (2022). An overview of salinity stress, mechanism of salinity tolerance and strategies for its management in cotton. Frontiers in Plant Science. 13. 59 indexed citations
16.
Tang, Yingying, Haodong Chen, Tingting Deng, et al.. (2022). Genome-wide identification and analysis of the GUB_WAK_bind gene family in Gossypium hirsutum. Molecular Biology Reports. 49(7). 6405–6413. 6 indexed citations
17.
Khan, Muhammad Kashif Riaz, et al.. (2021). Dissection of Drought Tolerance in Upland Cotton Through Morpho-Physiological and Biochemical Traits at Seedling Stage. Frontiers in Plant Science. 12. 627107–627107. 45 indexed citations
18.
19.
Aslam, Muhammad, et al.. (2012). Genetic diversity among upland cotton genotypes for different economic traits and response to cotton leaf curl virus (CLCV) disease. Pakistan Journal of Botany. 44(5). 1779–1784. 7 indexed citations
20.
Akhtar, Khalid Pervaiz, et al.. (2010). Short communication. Partial resistance of a cotton mutant to Cotton leaf curl Burewala virus. Spanish Journal of Agricultural Research. 8(4). 1098–1104. 5 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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