Mohammad Ferdosi

519 total citations
20 papers, 338 citations indexed

About

Mohammad Ferdosi is a scholar working on Genetics, Plant Science and Cancer Research. According to data from OpenAlex, Mohammad Ferdosi has authored 20 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Genetics, 6 papers in Plant Science and 5 papers in Cancer Research. Recurrent topics in Mohammad Ferdosi's work include Genetic and phenotypic traits in livestock (13 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and Genetics and Plant Breeding (6 papers). Mohammad Ferdosi is often cited by papers focused on Genetic and phenotypic traits in livestock (13 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and Genetics and Plant Breeding (6 papers). Mohammad Ferdosi collaborates with scholars based in Australia, Iran and United States. Mohammad Ferdosi's co-authors include Cedric Gondro, Paul Kwan, Sam Clark, Ross L. Tellam, Hawlader Abdullah Al-Mamun, J. H. J. van der Werf, Brian Kinghorn, Seung Hwan Lee, Bruce Tier and Ramin Abdoli and has published in prestigious journals such as BMC Bioinformatics, Journal of Animal Science and Process Safety and Environmental Protection.

In The Last Decade

Mohammad Ferdosi

18 papers receiving 329 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Ferdosi Australia 10 263 94 53 42 41 20 338
Yuhua Fu China 14 201 0.8× 157 1.7× 22 0.4× 50 1.2× 304 7.4× 30 518
Jian Miao China 10 216 0.8× 65 0.7× 29 0.5× 59 1.4× 48 1.2× 18 294
Tianpeng Chang China 14 389 1.5× 147 1.6× 61 1.2× 63 1.5× 77 1.9× 24 500
Rongrong Ding China 15 465 1.8× 230 2.4× 39 0.7× 49 1.2× 129 3.1× 37 598
Wenlei Fan China 12 117 0.4× 40 0.4× 17 0.3× 29 0.7× 93 2.3× 34 278
Yunfei Ma China 7 77 0.3× 50 0.5× 5 0.1× 16 0.4× 105 2.6× 18 210
Rayner González-Prendes Spain 13 200 0.8× 103 1.1× 29 0.5× 20 0.5× 126 3.1× 24 350
Diogo Anastácio Garcia Brazil 11 252 1.0× 52 0.6× 81 1.5× 48 1.1× 32 0.8× 25 320
Ghodrat Rahimi-Mianji Iran 11 187 0.7× 60 0.6× 32 0.6× 45 1.1× 51 1.2× 26 331
Yangyang Bai China 12 134 0.5× 54 0.6× 41 0.8× 78 1.9× 110 2.7× 34 297

Countries citing papers authored by Mohammad Ferdosi

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Ferdosi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Ferdosi

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Ferdosi. A scholar is included among the top collaborators of Mohammad Ferdosi 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 Mohammad Ferdosi. Mohammad Ferdosi 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.
Ferdosi, Mohammad, et al.. (2025). Opportunities and computational challenges in large-scale whole genome sequencing data analysis. Journal of Animal Science.
2.
Khansefid, Majid, Mohammad Ferdosi, Michael E. Goddard, et al.. (2022). 171. Application of haplotype relationship matrices for genomic prediction in purebred and crossbred cows. 737–740.
3.
Moore, Kirsty, et al.. (2022). 290. A new metric to assess reference populations for genomic selection in Australian beef breeds. 1221–1224. 1 indexed citations
4.
Ferdosi, Mohammad, Natalie K. Connors, & Bruce Tier. (2019). An Efficient Method to Calculate Genomic Prediction Accuracy for New Individuals. Frontiers in Genetics. 10. 596–596. 4 indexed citations
5.
Abdoli, Ramin, Seyed Ziaeddin Mirhoseini, Navid Ghavi Hossein‐Zadeh, et al.. (2019). Genome-wide association study of first lambing age and lambing interval in sheep. Small Ruminant Research. 178. 43–45. 21 indexed citations
6.
Abdoli, Ramin, Seyed Ziaeddin Mirhoseini, Navid Ghavi Hossein‐Zadeh, et al.. (2019). Genome-wide association study of four composite reproductive traits in Iranian fat-tailed sheep. Reproduction Fertility and Development. 31(6). 1127–1133. 21 indexed citations
7.
Johnston, D. J., et al.. (2018). Implementation of single-step genomic BREEDPLAN evaluations in Australian beef cattle. RUNE (Research UNE). 269. 2 indexed citations
8.
Connors, Natalie K., et al.. (2017). Development of the beef genomic pipeline for breedplan single step evaluation.. RUNE (Research UNE). 317–320. 1 indexed citations
9.
Gao, Wei, et al.. (2017). Combination of fuzzy based on a meta-heuristic algorithm to predict electricity price in an electricity markets. Process Safety and Environmental Protection. 131. 333–345. 28 indexed citations
10.
Strucken, Eva M., et al.. (2016). Local and global patterns of admixture and population structure in Iranian native cattle. BMC Genetics. 17(1). 108–108. 22 indexed citations
11.
Ferdosi, Mohammad, John Henshall, & Bruce Tier. (2016). Study of the optimum haplotype length to build genomic relationship matrices. Genetics Selection Evolution. 48(1). 75–75. 15 indexed citations
12.
Al-Mamun, Hawlader Abdullah, Paul Kwan, Sam Clark, et al.. (2015). Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight. Genetics Selection Evolution. 47(1). 66–66. 125 indexed citations
13.
Tier, Bruce, Karin Meyer, & Mohammad Ferdosi. (2015). Which Genomic Relationship Matrix. RUNE (Research UNE). 4 indexed citations
14.
Ferdosi, Mohammad, Brian Kinghorn, J. H. J. van der Werf, Seung Hwan Lee, & Cedric Gondro. (2014). hsphase: an R package for pedigree reconstruction, detection of recombination events, phasing and imputation of half-sib family groups. BMC Bioinformatics. 15(1). 172–172. 32 indexed citations
15.
Ferdosi, Mohammad, Brian Kinghorn, J. H. J. van der Werf, & Cedric Gondro. (2014). Detection of recombination events, haplotype reconstruction and imputation of sires using half-sib SNP genotypes. Genetics Selection Evolution. 46(1). 11–11. 12 indexed citations
16.
Strucken, Eva M., Mohammad Ferdosi, John P. Gibson, et al.. (2014). Performance of different SNP panels for parentage testing in two East Asian cattle breeds. Animal Genetics. 45(4). 572–575. 21 indexed citations
17.
Ferdosi, Mohammad, et al.. (2014). A fast method for evaluating opposing homozygosity in large SNP data sets. Livestock Science. 166. 35–37. 5 indexed citations
18.
Ferdosi, Mohammad, Brian Kinghorn, J. H. J. van der Werf, & Cedric Gondro. (2013). Effect of genotype and pedigree error on detection of recombination events, sire imputation and haplotype inference using the HSPhase algorithm.. RUNE (Research UNE). 546–549. 1 indexed citations
19.
Ferdosi, Mohammad, et al.. (2012). AN EXAMINATION OF ENERGY INTENSITY AND URBANIZATION EFFECT ON ENVIRONMENTAL DEGRADATION IN IRAN (A COINTEGRATION ANALYSIS). 37(60). 13–22. 1 indexed citations
20.
Derakhshanfar, Amin, et al.. (2011). Protective effect of kombucha tea against acetaminophen-induced hepatotoxicity in mice: a biochemical and histopathological study. Comparative Clinical Pathology. 21(6). 1243–1248. 22 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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