Laurence Yang

3.2k total citations
68 papers, 1.9k citations indexed

About

Laurence Yang is a scholar working on Molecular Biology, Computer Networks and Communications and Biomedical Engineering. According to data from OpenAlex, Laurence Yang has authored 68 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 14 papers in Computer Networks and Communications and 13 papers in Biomedical Engineering. Recurrent topics in Laurence Yang's work include Microbial Metabolic Engineering and Bioproduction (31 papers), Gene Regulatory Network Analysis (14 papers) and Biofuel production and bioconversion (11 papers). Laurence Yang is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (31 papers), Gene Regulatory Network Analysis (14 papers) and Biofuel production and bioconversion (11 papers). Laurence Yang collaborates with scholars based in United States, Canada and Denmark. Laurence Yang's co-authors include Bernhard Ø. Palsson, Colton J. Lloyd, Radhakrishnan Mahadevan, James T. Yurkovich, W.R. Cluett, Anand V. Sastry, Zachary A. King, Ye Gao, Jonathan M. Monk and Ali Ebrahim and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Laurence Yang

66 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Laurence Yang United States 26 1.4k 436 297 128 104 68 1.9k
Zilong Zhang China 20 1.8k 1.3× 443 1.0× 125 0.4× 49 0.4× 86 0.8× 84 2.5k
Shamim Ahmad Bangladesh 22 829 0.6× 115 0.3× 224 0.8× 55 0.4× 229 2.2× 122 2.0k
Liqian Zhou China 27 1.1k 0.8× 423 1.0× 55 0.2× 43 0.3× 96 0.9× 69 2.0k
Athanasia Pavlopoulou Greece 22 946 0.7× 174 0.4× 86 0.3× 66 0.5× 56 0.5× 75 1.9k
David Levine United States 26 867 0.6× 349 0.8× 157 0.5× 517 4.0× 136 1.3× 60 2.2k
Sophia Tsoka United Kingdom 25 1.3k 0.9× 108 0.2× 100 0.3× 40 0.3× 180 1.7× 86 2.4k
Lihong Li China 25 1.4k 1.0× 176 0.4× 102 0.3× 46 0.4× 147 1.4× 113 2.2k
Jorng‐Tzong Horng Taiwan 28 1.4k 1.0× 63 0.1× 123 0.4× 123 1.0× 224 2.2× 135 2.6k
Isabel Rocha Portugal 32 2.6k 1.9× 1.2k 2.8× 224 0.8× 46 0.4× 74 0.7× 147 3.3k
Guozhong Li China 12 921 0.7× 74 0.2× 99 0.3× 39 0.3× 106 1.0× 28 1.7k

Countries citing papers authored by Laurence Yang

Since Specialization
Citations

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

Fields of papers citing papers by Laurence Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laurence Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Laurence Yang. A scholar is included among the top collaborators of Laurence 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 Laurence Yang. Laurence Yang 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.
Luo, Changqing, et al.. (2025). DRL-Based Joint Optimization of Wireless Charging and Computation Offloading for Multi-Access Edge Computing. IEEE Transactions on Services Computing. 18(3). 1352–1367. 1 indexed citations
2.
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Pan, Shirui, et al.. (2023). Neighbor Contrastive Learning on Learnable Graph Augmentation. Proceedings of the AAAI Conference on Artificial Intelligence. 37(8). 9782–9791. 55 indexed citations
5.
Park, Joon Young, Sang‐Mok Lee, Ali Ebrahim, et al.. (2023). Model-driven experimental design workflow expands understanding of regulatory role of Nac in Escherichia coli. NAR Genomics and Bioinformatics. 5(1). lqad006–lqad006. 4 indexed citations
6.
Rychel, Kevin, Justin Tan, Cameron Lamoureux, et al.. (2023). Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance. Cell Reports. 42(9). 113105–113105. 13 indexed citations
7.
Yu, Hang, Qingchen Zhang, & Laurence Yang. (2023). An Edge-Cloud-Aided Private High-Order Fuzzy C-Means Clustering Algorithm in Smart Healthcare. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 21(4). 1083–1092. 8 indexed citations
8.
Lachance, Jean‐Christophe, Colton J. Lloyd, Jonathan M. Monk, et al.. (2019). BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data. PLoS Computational Biology. 15(4). e1006971–e1006971. 72 indexed citations
9.
Du, Bin, Laurence Yang, Colton J. Lloyd, Xin Fang, & Bernhard Ø. Palsson. (2019). Genome-scale model of metabolism and gene expression provides a multi-scale description of acid stress responses in Escherichia coli. PLoS Computational Biology. 15(12). e1007525–e1007525. 41 indexed citations
10.
Gao, Ye, James T. Yurkovich, Sang Woo Seo, et al.. (2018). Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655. Nucleic Acids Research. 46(20). 10682–10696. 68 indexed citations
11.
Lloyd, Colton J., Ali Ebrahim, Laurence Yang, et al.. (2018). COBRAme: A computational framework for genome-scale models of metabolism and gene expression. PLoS Computational Biology. 14(7). e1006302–e1006302. 107 indexed citations
12.
Kavvas, Erol, Edward Catoiu, Nathan Mih, et al.. (2018). Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance. Nature Communications. 9(1). 4306–4306. 129 indexed citations
13.
Yang, Laurence, José Bento, Jean‐Christophe Lachance, & Bernhard Ø. Palsson. (2018). Genome-scale estimation of cellular objectives.. arXiv (Cornell University). 1 indexed citations
14.
Fang, Xin, Anand V. Sastry, Nathan Mih, et al.. (2017). Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities. Proceedings of the National Academy of Sciences. 114(38). 10286–10291. 74 indexed citations
15.
Yurkovich, James T., Daniel C. Zielinski, Laurence Yang, et al.. (2017). Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks. Journal of Biological Chemistry. 292(48). 19556–19564. 45 indexed citations
16.
Yurkovich, James T., Laurence Yang, & Bernhard Ø. Palsson. (2017). Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells. PLoS Computational Biology. 13(3). e1005424–e1005424. 9 indexed citations
17.
Yang, Laurence, et al.. (2012). Handbook on Mobile and Ubiquitous Computing: Status and Perspective. CERN Document Server (European Organization for Nuclear Research). 2 indexed citations
18.
Hsu, Ching‐Hsien, et al.. (2010). An Efficient Peer Collaboration Strategy for Optimizing P2P Services in BitTorrent-Like File Sharing Networks. 網際網路技術學刊. 11(1). 79–88.
19.
Yang, Laurence, et al.. (2006). Autonomic and Trusted Computing : Third International Conference, ATC 2006, Wuhan, China, September 3-6, 2006 : proceedings. Springer eBooks. 1 indexed citations
20.
Ho, Michael, Weng-Long Chang, Minyi Guo, & Laurence Yang. (2004). Fast Parallel Solution for Set-Packing and Clique Problems by DNA-Based Computing. IEICE Transactions on Information and Systems. 87(7). 1782–1788. 7 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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