N. Long

472 total citations
8 papers, 331 citations indexed

About

N. Long is a scholar working on Genetics, Plant Science and Animal Science and Zoology. According to data from OpenAlex, N. Long has authored 8 papers receiving a total of 331 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Genetics, 3 papers in Plant Science and 2 papers in Animal Science and Zoology. Recurrent topics in N. Long's work include Genetic Mapping and Diversity in Plants and Animals (6 papers), Genetic and phenotypic traits in livestock (6 papers) and Genetics and Plant Breeding (3 papers). N. Long is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (6 papers), Genetic and phenotypic traits in livestock (6 papers) and Genetics and Plant Breeding (3 papers). N. Long collaborates with scholars based in United States, Australia and Tanzania. N. Long's co-authors include Daniel Gianola, Guilherme J. M. Rosa, K.A. Weigel, Santiago Avendaño, Hugo Naya, X.‐L. Wu, G. de los Campos, Óscar González-Recio, Lúcia Galvão de Albuquerque and Arione Augusti Boligon and has published in prestigious journals such as Journal of Dairy Science, Journal of Animal Science and Heredity.

In The Last Decade

N. Long

7 papers receiving 319 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
N. Long United States	7	276	202	29	26	20	8	331
Torsten Pook Germany	10	267 1.0×	179 0.9×	29 1.0×	59 2.3×	21 1.1×	33	345
Simon Teyssèdre France	13	385 1.4×	346 1.7×	28 1.0×	22 0.8×	43 2.1×	14	486
Chuanyu Sun United States	5	296 1.1×	124 0.6×	17 0.6×	60 2.3×	38 1.9×	10	330
Luís Gustavo Girardi Figueiredo Brazil	10	158 0.6×	36 0.2×	75 2.6×	13 0.5×	81 4.0×	26	271
Manfred Mayer Germany	11	266 1.0×	259 1.3×	7 0.2×	55 2.1×	31 1.6×	17	352
Xiaopeng Wang China	10	261 0.9×	125 0.6×	50 1.7×	36 1.4×	41 2.0×	18	315
Olga Kostyunina Russia	8	217 0.8×	52 0.3×	57 2.0×	33 1.3×	29 1.4×	65	302
Hassan Aliloo Australia	10	293 1.1×	75 0.4×	65 2.2×	17 0.7×	91 4.5×	21	314
M. İ. Soysal Türkiye	11	217 0.8×	21 0.1×	69 2.4×	30 1.2×	67 3.4×	55	324
Jinlong He China	6	280 1.0×	138 0.7×	27 0.9×	59 2.3×	30 1.5×	12	337

Countries citing papers authored by N. Long

Since Specialization

Citations

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

Fields of papers citing papers by N. Long

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of N. Long

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Roe, Dilys, et al.. (2025). Safe, sustainable, legal use and trade in wild species: testing a new five-dimensional sustainability assessment. One Health. 21. 101245–101245.

2.

Ornella, Leonardo, Elizabeth Tapia, Juan Manuel González‐Camacho, et al.. (2014). Genomic-enabled prediction with classification algorithms. Heredity. 112(6). 616–626. 54 indexed citations

3.

Boligon, Arione Augusti, N. Long, Lúcia Galvão de Albuquerque, et al.. (2012). Comparison of selective genotyping strategies for prediction of breeding values in a population undergoing selection. Journal of Animal Science. 90(13). 4716–4722. 35 indexed citations

4.

Long, N., Daniel Gianola, Guilherme J. M. Rosa, & K.A. Weigel. (2011). Dimension reduction and variable selection for genomic selection: application to predicting milk yield in Holsteins. Journal of Animal Breeding and Genetics. 128(4). 247–257. 44 indexed citations

5.

Weigel, K.A., G. de los Campos, Óscar González-Recio, et al.. (2009). Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers. Journal of Dairy Science. 92(10). 5248–5257. 98 indexed citations

6.

Long, N., Daniel Gianola, Guilherme J. M. Rosa, K.A. Weigel, & Santiago Avendaño. (2008). Machine Learning Classification Procedure for Selecting SNPs in Genomic Selection: Application to Early Mortality in Broilers. PubMed. 132. 373–376. 72 indexed citations

7.

Long, N., Daniel Gianola, Guilherme J. M. Rosa, K.A. Weigel, & Santiago Avendaño. (2008). Marker-assisted assessment of genotype by environment interaction: A case study of single nucleotide polymorphism-mortality association in broilers in two hygiene environments1. Journal of Animal Science. 86(12). 3358–3366. 9 indexed citations

8.

Long, N.. (1999). Exploring Local/global Transformations: A view from anthropology. Socio-Environmental Systems Modeling. 184–201. 19 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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