Nasir Moghaddar

767 citations

34 papers · 434 indexed · h-index 12

Co-authors: J. H. J. van der Werf Andrew Swan Hans D. Daetwyler Naomi Duijvesteijn Sunduimijid Bolormaa Iona M. MacLeod Sam Clark Majid Khansefid
Topics: Genetic and phenotypic traits in livestock (34 papers)Genetic Mapping and Diversity in Plants and Animals (26 papers)Cancer-related molecular mechanisms research (7 papers)
Cited by: Genetics Agronomy and Crop Science Cancer Research
Journals: PLoS ONE Journal of Animal Science Frontiers in Genetics
Partner nations: Australia South Korea Canada

In The Last Decade

Nasir Moghaddar

33 papers receiving 431 citations

Peers

Countries citing papers authored by Nasir Moghaddar

Since Specialization

Citations

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

Fields of papers citing papers by Nasir Moghaddar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nasir Moghaddar

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

#	Work	Indexed citations
1	724. Impact of the order of polynomials in random regression model on the accuracy of genetic evaluation for weight traits 2022 ·(unknown),D. J. Brown,Nasir Moghaddar,J. H. J. van der Werf	2
2	Genomic analysis of the slope of the reaction norm for body weight in Australian sheep 2022 ·Genetics Selection Evolution ·(unknown),Sam Clark,Nasir Moghaddar,J. H. J. van der Werf	8
3	Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes 2021 ·Frontiers in Genetics ·(unknown),(unknown),Naomi Duijvesteijn,Nasir Moghaddar,J. H. J. van der Werf	9
4	A conditional multi-trait sequence GWAS discovers pleiotropic candidate genes and variants for sheep wool, skin wrinkle and breech cover traits 2021 ·Genetics Selection Evolution ·Sunduimijid Bolormaa,Andrew Swan,Paul Stothard,Majid Khansefid,Nasir Moghaddar,Naomi Duijvesteijn,J. H. J. van der Werf,Hans D. Daetwyler,Iona M. MacLeod	15
5	Use of gene expression and whole-genome sequence information to improve the accuracy of genomic prediction for carcass traits in Hanwoo cattle 2020 ·Genetics Selection Evolution ·(unknown),Bryan Irvine Lopez,Nasir Moghaddar,Woncheoul Park,Jong‐Eun Park,Ki Yong Chung,Dajeong Lim,Seung Hwan Lee,Donghyun Shin,J. H. J. van der Werf	32
6	Accuracy of imputation to whole-genome sequence in sheep 2019 ·Genetics Selection Evolution ·Sunduimijid Bolormaa,Amanda J. Chamberlain,Majid Khansefid,Paul Stothard,Andrew Swan,Brett Mason,Claire Prowse-Wilkins,Naomi Duijvesteijn,Nasir Moghaddar,J. H. J. van der Werf,Hans D. Daetwyler,Iona M. MacLeod	43
7	Using imputed whole-genome sequence data to improve the accuracy of genomic prediction for parasite resistance in Australian sheep 2019 ·Genetics Selection Evolution ·(unknown),John P. Gibson,Naomi Duijvesteijn,Hans D. Daetwyler,Iona M. MacLeod,Nasir Moghaddar,Sang Lee,J. H. J. van der Werf	31
8	Genomic prediction based on selected variants from imputed whole-genome sequence data in Australian sheep populations 2019 ·Genetics Selection Evolution ·Nasir Moghaddar,Majid Khansefid,J. H. J. van der Werf,Sunduimijid Bolormaa,Naomi Duijvesteijn,Sam Clark,Andrew Swan,Hans D. Daetwyler,Iona M. MacLeod	59
9	Optimising bias and accuracy in genomic prediction of breeding values 2018 ·RUNE (Research UNE) ·G. R. Gowane,Sang Lee,Sam Clark,Nasir Moghaddar,(unknown),J. H. J. van der Werf	1
10	Exploiting sequence variants for genomic prediction in Australian sheep using Bayesian models 2018 ·RUNE (Research UNE) ·Majid Khansefid,Sunduimijid Bolormaa,Andrew Swan,J. H. J. van der Werf,Nasir Moghaddar,Naomi Duijvesteijn,Hans D. Daetwyler,Iona M. MacLeod	2
11	Genomic evaluation based on selected variants from imputed whole-genome sequence data in Australian sheep populations 2018 ·RUNE (Research UNE) ·Nasir Moghaddar,Iona M. MacLeod,Naomi Duijvesteijn,Sunduimijid Bolormaa,Majid Khansefid,Hawlader Abdullah Al-Mamun,Sam Clark,Andrew Swan,Hans D. Daetwyler,J. H. J. van der Werf	4
12	Genome-wide association study of meat quality traits using whole-genome sequence data in a multi-breed sheep population 2018 ·Proceedings of the World Congress on Genetics Applied to Livestock Production ·Naomi Duijvesteijn,Sunduimijid Bolormaa,Cedric Gondro,Sam Clark,Majid Khansefid,Nasir Moghaddar,Andrew Swan,Paul Stothard,Hans D. Daetwyler,J. H. J. van der Werf,Iona M. MacLeod	4
13	Multiple-trait QTL mapping and genomic prediction for wool traits in sheep 2017 ·Genetics Selection Evolution ·Sunduimijid Bolormaa,Andrew Swan,D. J. Brown,S. Hatcher,Nasir Moghaddar,J. H. J. van der Werf,Michael E. Goddard,Hans D. Daetwyler	33
14	Genomic prediction from observed and imputed high-density ovine genotypes 2017 ·Genetics Selection Evolution ·Nasir Moghaddar,Andrew Swan,J. H. J. van der Werf	10
15	Gene by Birth Type Interaction in Merino Lamb 2017 ·(unknown),Nasir Moghaddar,Cedric Gondro,J. H. J. van der Werf	1
16	Genomic estimation of additive and dominance effects and impact of accounting for dominance on accuracy of genomic evaluation in sheep populations 2017 ·Journal of Animal Breeding and Genetics ·Nasir Moghaddar,J. H. J. van der Werf	24
17	Local and global patterns of admixture and population structure in Iranian native cattle 2016 ·BMC Genetics ·(unknown),Eva M. Strucken,Nasir Moghaddar,Mohammad Ferdosi,Ali Esmailizadeh,Cedric Gondro	22
18	Accuracy of genotype imputation based on random and selected reference sets in purebred and crossbred sheep populations and its effect on accuracy of genomic prediction 2015 ·Genetics Selection Evolution ·Nasir Moghaddar,(unknown),Hans D. Daetwyler,Ben J. Hayes,J. H. J. van der Werf	28
19	Comparing genomic prediction accuracy from purebred, crossbred and combined purebred and crossbred reference populations in sheep 2014 ·Genetics Selection Evolution ·Nasir Moghaddar,Andrew Swan,J. H. J. van der Werf	30
20	Quantitative trait loci mapping for growth and wool traits in Australian Merino sheep. 2006 ·RUNE (Research UNE) ·Nasir Moghaddar,K. Marshall,J. H. J. van der Werf	1

About Nasir Moghaddar

Nasir Moghaddar is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology, having authored 34 papers that have together received 434 indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (34 papers), Genetic Mapping and Diversity in Plants and Animals (26 papers) and Cancer-related molecular mechanisms research (7 papers). The work is most often cited by research in Genetics (404 citations), Agronomy and Crop Science (80 citations) and Cancer Research (94 citations). Nasir Moghaddar has collaborated with scholars based in Australia, South Korea and Canada. Frequent co-authors include J. H. J. van der Werf, Andrew Swan, Hans D. Daetwyler, Naomi Duijvesteijn, Sunduimijid Bolormaa, Iona M. MacLeod, Sam Clark, Majid Khansefid, Sang Lee and D. J. Brown. Their work appears in journals such as PLoS ONE, Journal of Animal Science and Frontiers in Genetics.

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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