Luanne Lukes

1.2k total citations
17 papers, 878 citations indexed

About

Luanne Lukes is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Luanne Lukes has authored 17 papers receiving a total of 878 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 4 papers in Oncology and 3 papers in Genetics. Recurrent topics in Luanne Lukes's work include Molecular Biology Techniques and Applications (5 papers), RNA Research and Splicing (4 papers) and Gene expression and cancer classification (4 papers). Luanne Lukes is often cited by papers focused on Molecular Biology Techniques and Applications (5 papers), RNA Research and Splicing (4 papers) and Gene expression and cancer classification (4 papers). Luanne Lukes collaborates with scholars based in United States, Poland and Slovenia. Luanne Lukes's co-authors include Kent W. Hunter, Nigel P.S. Crawford, Renard C. Walker, Danny R. Welch, Haiyan Yang, Howard H. Yang, Dragoș Cozma, Jude Alsarraj, Keiko Ozato and Maxwell P. Lee and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Cancer Research and Genome Research.

In The Last Decade

Luanne Lukes

16 papers receiving 867 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luanne Lukes United States 13 665 269 226 128 84 17 878
Chaoting Liu United States 7 609 0.9× 126 0.5× 195 0.9× 96 0.8× 55 0.7× 12 804
Sophia X. Pfister United Kingdom 9 831 1.2× 139 0.5× 216 1.0× 60 0.5× 93 1.1× 11 959
Massimo Bogliolo Spain 16 608 0.9× 165 0.6× 122 0.5× 170 1.3× 37 0.4× 28 740
Sriganesh Jammula United Kingdom 12 917 1.4× 196 0.7× 142 0.6× 105 0.8× 125 1.5× 14 1.2k
Kelsey Breslin Australia 12 725 1.1× 170 0.6× 296 1.3× 177 1.4× 109 1.3× 17 942
Crissy Dudgeon United States 14 760 1.1× 192 0.7× 417 1.8× 107 0.8× 44 0.5× 19 981
Alper Yetil United States 5 951 1.4× 208 0.8× 322 1.4× 59 0.5× 47 0.6× 5 1.2k
Toshinori Hyodo Japan 21 781 1.2× 171 0.6× 225 1.0× 69 0.5× 91 1.1× 47 1.1k
Andrew J. Fritz United States 17 704 1.1× 203 0.8× 145 0.6× 91 0.7× 47 0.6× 38 868
Ariel Pribluda Israel 7 688 1.0× 135 0.5× 190 0.8× 96 0.8× 54 0.6× 11 912

Countries citing papers authored by Luanne Lukes

Since Specialization
Citations

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

Fields of papers citing papers by Luanne Lukes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luanne Lukes

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

All Works

17 of 17 papers shown
1.
Winter, Scott F., Luanne Lukes, Renard C. Walker, Danny R. Welch, & Kent W. Hunter. (2012). Allelic Variation and Differential Expression of the mSIN3A Histone Deacetylase Complex Gene Arid4b Promote Mammary Tumor Growth and Metastasis. PLoS Genetics. 8(5). e1002735–e1002735. 40 indexed citations
2.
Hu, Ying, Gang Wu, Michael Rusch, et al.. (2012). Integrated cross-species transcriptional network analysis of metastatic susceptibility. Proceedings of the National Academy of Sciences. 109(8). 3184–3189. 44 indexed citations
3.
Hu, Ying, Gang Wu, Michael Rusch, et al.. (2012). Abstract 2980: An integrated cross-species transcriptional network analysis of metastatic susceptibility. Cancer Research. 72(8_Supplement). 2980–2980. 1 indexed citations
4.
Winter, Scott F., Luanne Lukes, & Kent W. Hunter. (2010). Abstract 2371: Arid4b is a potential breast cancer progression modifier gene. Cancer Research. 70(8_Supplement). 2371–2371. 2 indexed citations
5.
Korde, Larissa A., Lara Lusa, Lisa M. McShane, et al.. (2009). Gene expression pathway analysis to predict response to neoadjuvant docetaxel and capecitabine for breast cancer. Breast Cancer Research and Treatment. 119(3). 685–699. 79 indexed citations
6.
Lukes, Luanne, Nigel P.S. Crawford, Renard C. Walker, & Kent W. Hunter. (2008). The Origins of Breast Cancer Prognostic Gene Expression Profiles. Cancer Research. 69(1). 310–318. 29 indexed citations
7.
Crawford, Nigel P.S., et al.. (2008). The Diasporin Pathway: a tumor progression-related transcriptional network that predicts breast cancer survival. Clinical & Experimental Metastasis. 25(4). 357–369. 54 indexed citations
8.
Crawford, Nigel P.S., Jude Alsarraj, Luanne Lukes, et al.. (2008). Bromodomain 4 activation predicts breast cancer survival. Proceedings of the National Academy of Sciences. 105(17). 6380–6385. 147 indexed citations
9.
Crawford, Nigel P.S., Xiaolan Qian, Argyrios Ziogas, et al.. (2007). Rrp1b, a New Candidate Susceptibility Gene for Breast Cancer Progression and Metastasis. PLoS Genetics. 3(11). e214–e214. 68 indexed citations
10.
Yang, Haiyan, Li‐Rong Yu, Ming Yi, et al.. (2006). Parallel Analysis of Transcript and Translation Profiles:  Identification of Metastasis-Related Signal Pathways Differentially Regulated by Drug and Genetic Modifications. Journal of Proteome Research. 5(7). 1555–1567. 9 indexed citations
11.
Yang, Haiyan, et al.. (2005). Metastasis Predictive Signature Profiles Pre-exist in Normal Tissues. Clinical & Experimental Metastasis. 22(7). 593–603. 91 indexed citations
12.
Yang, Haiyan, Luanne Lukes, Timothy D. Veenstra, et al.. (2005). Caffeine suppresses metastasis in a transgenic mouse model: a prototype molecule for prophylaxis of metastasis. Clinical & Experimental Metastasis. 21(8). 719–735. 58 indexed citations
13.
Qian, Xiaolan, Argyrios Ziogas, Alex G. Papageorge, et al.. (2005). Rrp1b, a new candidate susceptibility gene for breast cancer progression and metastasis. PLoS Genetics. preprint(2007). e214–e214.
14.
Montagna, Cristina, Kent W. Hunter, Luanne Lukes, et al.. (2003). The Septin 9 (MSF) gene is amplified and overexpressed in mouse mammary gland adenocarcinomas and human breast cancer cell lines.. PubMed. 63(9). 2179–87. 119 indexed citations
15.
Cozma, Dragoș, et al.. (2002). A Bioinformatics-Based Strategy Identifies c-Myc and Cdc25A as Candidates for the Apmt Mammary Tumor Latency Modifiers. Genome Research. 12(6). 969–975. 28 indexed citations
16.
Lukes, Luanne, Howard H. Yang, Michael T. Debies, et al.. (2002). Comparative sequence analysis in eight inbred strains of the metastasis modifier QTL candidate gene Brms1. Mammalian Genome. 13(6). 289–292. 12 indexed citations
17.
Hunter, Kent W., Karl W. Broman, Luanne Lukes, et al.. (2001). Predisposition to efficient mammary tumor metastatic progression is linked to the breast cancer metastasis suppressor gene Brms1.. PubMed. 61(24). 8866–72. 97 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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