Longlong Yang

1.5k total citations
19 papers, 1.1k citations indexed

About

Longlong Yang is a scholar working on Molecular Biology, Cancer Research and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Longlong Yang has authored 19 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 7 papers in Cancer Research and 5 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Longlong Yang's work include Gene expression and cancer classification (7 papers), Carcinogens and Genotoxicity Assessment (6 papers) and Diptera species taxonomy and behavior (4 papers). Longlong Yang is often cited by papers focused on Gene expression and cancer classification (7 papers), Carcinogens and Genotoxicity Assessment (6 papers) and Diptera species taxonomy and behavior (4 papers). Longlong Yang collaborates with scholars based in United States, Australia and Canada. Longlong Yang's co-authors include Russell S. Thomas, Bruce C. Allen, Melvin E. Andersen, Harvey J. Clewell, Linda Pluta, Eric W. Healy, Andy Nong, Edilberto Bermudez, Todd J. Page and David K. Yeates and has published in prestigious journals such as Bioinformatics, Genome biology and Virology.

In The Last Decade

Longlong Yang

19 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Longlong Yang United States 15 585 366 277 165 92 19 1.1k
Frank Boellmann United States 9 966 1.7× 151 0.4× 87 0.3× 76 0.5× 68 0.7× 11 1.3k
Jason M. O’Brien Canada 21 329 0.6× 676 1.8× 209 0.8× 129 0.8× 102 1.1× 59 1.3k
Robert G. Halgren United States 19 795 1.4× 196 0.5× 72 0.3× 31 0.2× 23 0.3× 20 1.5k
Richard E. Morrissey United States 21 241 0.4× 380 1.0× 263 0.9× 8 0.0× 64 0.7× 54 1.2k
Amar V. Singh United States 14 472 0.8× 408 1.1× 195 0.7× 207 1.3× 166 1.8× 30 1.3k
David B. Carlson United States 21 451 0.8× 258 0.7× 153 0.6× 7 0.0× 86 0.9× 36 1.6k
Alan D. MacNicoll United Kingdom 23 308 0.5× 263 0.7× 217 0.8× 15 0.1× 21 0.2× 58 1.5k
B. Kureleć Croatia 23 371 0.6× 517 1.4× 113 0.4× 16 0.1× 79 0.9× 73 1.5k
M. Bittner United States 4 360 0.6× 98 0.3× 73 0.3× 75 0.5× 32 0.3× 5 574
S. Zimmering United States 19 729 1.2× 316 0.9× 669 2.4× 12 0.1× 26 0.3× 99 1.6k

Countries citing papers authored by Longlong Yang

Since Specialization
Citations

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

Fields of papers citing papers by Longlong Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Longlong Yang

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

All Works

19 of 19 papers shown
1.
Wheeler, Matthew W., John S. House, Keith R. Shockley, et al.. (2022). ToxicR: A computational platform in R for computational toxicology and dose–response analyses. Computational Toxicology. 25. 100259–100259. 9 indexed citations
2.
Phillips, Jason, Daniel Svoboda, Arpit Tandon, et al.. (2018). BMDExpress 2: enhanced transcriptomic dose-response analysis workflow. Bioinformatics. 35(10). 1780–1782. 153 indexed citations
3.
Jackson, Marcus, Longlong Yang, Isabel A. Lea, et al.. (2017). The TGx‐28.65 biomarker online application for analysis of transcriptomics data to identify DNA damage‐inducing chemicals in human cell cultures. Environmental and Molecular Mutagenesis. 58(7). 529–535. 15 indexed citations
4.
Gao, Li, Lianghai Wang, Chen Huang, et al.. (2015). HP-PRRSV is attenuated by de-optimization of codon pair bias in its RNA-dependent RNA polymerase nsp9 gene. Virology. 485. 135–144. 29 indexed citations
5.
Winterton, Shaun L., Nate B. Hardy, Stephen D. Gaimari, et al.. (2015). The phylogeny of stiletto flies ( D iptera: T herevidae). Systematic Entomology. 41(1). 144–161. 9 indexed citations
6.
Thomas, Russell S., Scott C. Wesselkamper, Nina Ching Y. Wang, et al.. (2013). Temporal Concordance Between Apical and Transcriptional Points of Departure for Chemical Risk Assessment. Toxicological Sciences. 134(1). 180–194. 154 indexed citations
7.
8.
Thomas, Russell S., Harvey J. Clewell, Bruce C. Allen, et al.. (2012). Integrating pathway-based transcriptomic data into quantitative chemical risk assessment: A five chemical case study. Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 746(2). 135–143. 72 indexed citations
9.
Woods, Courtney G., Jingqi Fu, Peng Xue, et al.. (2009). Dose-dependent transitions in Nrf2-mediated adaptive response and related stress responses to hypochlorous acid in mouse macrophages. Toxicology and Applied Pharmacology. 238(1). 27–36. 77 indexed citations
10.
11.
Yang, Longlong, John R. Walker, John B. Hogenesch, & Russell S. Thomas. (2008). NetAtlas: A Cytoscape Plugin to Examine Signaling Networks Based on Tissue Gene Expression. In Silico Biology. 8(1). 47–52. 7 indexed citations
12.
Halsey, Thomas A., Longlong Yang, John R. Walker, John B. Hogenesch, & Russell S. Thomas. (2007). A functional map of NFκB signaling identifies novel modulators and multiple system controls. Genome biology. 8(6). R104–R104. 18 indexed citations
13.
Yang, Longlong, Bruce C. Allen, & Russell S. Thomas. (2007). BMDExpress: a software tool for the benchmark dose analyses of genomic data. BMC Genomics. 8(1). 387–387. 165 indexed citations
14.
Thomas, Russell S., Linda Pluta, Longlong Yang, & Thomas A. Halsey. (2007). Application of Genomic Biomarkers to Predict Increased Lung Tumor Incidence in 2-Year Rodent Cancer Bioassays. Toxicological Sciences. 97(1). 55–64. 43 indexed citations
15.
Thomas, Russell S., Bruce C. Allen, Andy Nong, et al.. (2007). A Method to Integrate Benchmark Dose Estimates with Genomic Data to Assess the Functional Effects of Chemical Exposure. Toxicological Sciences. 98(1). 240–248. 154 indexed citations
16.
Thomas, Russell S., Thomas M. O’Connell, Linda Pluta, et al.. (2006). A Comparison of Transcriptomic and Metabonomic Technologies for Identifying Biomarkers Predictive of Two-Year Rodent Cancer Bioassays. Toxicological Sciences. 96(1). 40–46. 33 indexed citations
17.
Page, Todd J., Devanjan Sikder, Longlong Yang, et al.. (2006). Genome-wide analysis of human HSF1 signaling reveals a transcriptional program linked to cellular adaptation and survival. Molecular BioSystems. 2(12). 627–639. 104 indexed citations
18.
Winterton, Shaun L., Longlong Yang, Brian M. Wiegmann, & David K. Yeates. (2001). Phylogenetic revision of Agapophytinae subf.n. (Diptera: Therevidae) based on molecular and morphological evidence. Systematic Entomology. 26(2). 173–211. 38 indexed citations
19.
Yang, Longlong, Brian M. Wiegmann, David K. Yeates, & Michael E. Irwin. (2000). Higher-Level Phylogeny of the Therevidae (Diptera: Insecta) Based on 28S Ribosomal and Elongation Factor-1α Gene Sequences. Molecular Phylogenetics and Evolution. 15(3). 440–451. 37 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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