Daniel Lai

7.7k total citations
21 papers, 877 citations indexed

About

Daniel Lai is a scholar working on Molecular Biology, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Daniel Lai has authored 21 papers receiving a total of 877 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 7 papers in Cancer Research and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Daniel Lai's work include Cancer Genomics and Diagnostics (7 papers), Single-cell and spatial transcriptomics (6 papers) and Genomics and Phylogenetic Studies (4 papers). Daniel Lai is often cited by papers focused on Cancer Genomics and Diagnostics (7 papers), Single-cell and spatial transcriptomics (6 papers) and Genomics and Phylogenetic Studies (4 papers). Daniel Lai collaborates with scholars based in Canada, United States and France. Daniel Lai's co-authors include Irmtraud M. Meyer, Renée K. Margolis, C. Preti, R. U. Margolis, Jing Zhu, Sohrab P. Shah, Samuel Aparício, Donald R. Love, Alexander Stuckey and Jonathan R. Skinner and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Advanced Materials.

In The Last Decade

Daniel Lai

20 papers receiving 856 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Lai Canada 13 632 198 119 80 76 21 877
Felix Kraus United States 14 965 1.5× 139 0.7× 98 0.8× 146 1.8× 29 0.4× 20 1.3k
Ezequiel Lacunza Argentina 20 656 1.0× 278 1.4× 81 0.7× 63 0.8× 57 0.8× 64 1.0k
Chiung‐Yuan Ko Taiwan 24 697 1.1× 252 1.3× 82 0.7× 72 0.9× 32 0.4× 43 1.2k
Jukka Kallijärvi Finland 19 753 1.2× 134 0.7× 126 1.1× 95 1.2× 42 0.6× 41 1.1k
Brenda Kostelecky United Kingdom 11 1.2k 1.9× 92 0.5× 50 0.4× 201 2.5× 35 0.5× 11 1.4k
Annamaria Bevilacqua Italy 18 798 1.3× 157 0.8× 51 0.4× 58 0.7× 53 0.7× 29 1.1k
Ana Fernández‐Marmiesse Spain 17 460 0.7× 75 0.4× 219 1.8× 43 0.5× 36 0.5× 33 842
Jikhyon Han South Korea 13 478 0.8× 199 1.0× 55 0.5× 107 1.3× 27 0.4× 27 733
Qi Guo China 18 483 0.8× 190 1.0× 97 0.8× 77 1.0× 31 0.4× 61 887
Hriday K. Das United States 18 676 1.1× 104 0.5× 147 1.2× 97 1.2× 19 0.3× 46 1.2k

Countries citing papers authored by Daniel Lai

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Lai

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Lai. A scholar is included among the top collaborators of Daniel Lai 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 Daniel Lai. Daniel Lai 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.
Jeon, Jueun, Seok Ho Song, Daniel Lai, et al.. (2025). Enzymatically Switchable Pyroptosis‐Inducing Polymer Conjugate to Coordinate Host Immune Responses in Cancer Immunotherapy. Advanced Materials. 38(8). e10103–e10103.
2.
Sarkozy, Clémentine, Shaocheng Wu, Tomohiro Aoki, et al.. (2024). Integrated single cell analysis reveals co-evolution of malignant B cells and tumor micro-environment in transformed follicular lymphoma. Cancer Cell. 42(6). 1003–1017.e6. 9 indexed citations
3.
Cao, Jiannong, et al.. (2024). Modeling Behavior Change for Multi-model At-Risk Students Early Prediction. 54–58. 1 indexed citations
4.
Salehi, Sohrab, Farhia Kabeer, Nicole Rusk, et al.. (2023). Cancer phylogenetic tree inference at scale from 1000s of single cell genomes. SHILAP Revista de lepidopterología. 3. 9 indexed citations
5.
Todeschini, Anne‐Laure, Dawn R. Cochrane, Daniel Lai, et al.. (2021). FOXL2 in adult‐type granulosa cell tumour of the ovary: oncogene or tumour suppressor gene?. The Journal of Pathology. 255(3). 225–231. 13 indexed citations
6.
Souza, Camila P. E. de, Mirela Andronescu, Tehmina Masud, et al.. (2020). Epiclomal: Probabilistic clustering of sparse single-cell DNA methylation data. PLoS Computational Biology. 16(9). e1008270–e1008270. 15 indexed citations
7.
Campbell, Kieran R., Adi Steif, Emma Laks, et al.. (2019). clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers. Genome biology. 20(1). 54–54. 69 indexed citations
8.
Farahani, Hossein, Camila P. E. de Souza, Damian Yap, et al.. (2017). Engineered in-vitro cell line mixtures and robust evaluation of computational methods for clonal decomposition and longitudinal dynamics in cancer. Scientific Reports. 7(1). 13467–13467. 3 indexed citations
9.
Leung, Kaston, Emma Laks, Justina Biele, et al.. (2016). Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates. Proceedings of the National Academy of Sciences. 113(30). 8484–8489. 34 indexed citations
10.
Lai, Daniel & Irmtraud M. Meyer. (2015). A comprehensive comparison of general RNA–RNA interaction prediction methods. Nucleic Acids Research. 44(7). e61–e61. 42 indexed citations
11.
Leong, Ivone, Alexander Stuckey, Daniel Lai, Jonathan R. Skinner, & Donald R. Love. (2015). Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations. BMC Medical Genetics. 16(1). 34–34. 71 indexed citations
12.
Lai, Daniel & Irmtraud M. Meyer. (2014). e-RNA: a collection of web servers for comparative RNA structure prediction and visualisation. Nucleic Acids Research. 42(W1). W373–W376. 5 indexed citations
13.
Lai, Daniel, et al.. (2013). On the importance of cotranscriptional RNA structure formation. RNA. 19(11). 1461–1473. 119 indexed citations
14.
Lai, Daniel, Tudor G. Jovin, & Ashutosh P. Jadhav. (2013). Cortical Vein Air Emboli With Gyriform Infarcts. JAMA Neurology. 70(7). 939–939. 12 indexed citations
15.
Ha, Gavin, Andrew Roth, Daniel Lai, et al.. (2012). Integrative analysis of genome-wide loss of heterozygosity and monoallelic expression at nucleotide resolution reveals disrupted pathways in triple-negative breast cancer. Genome Research. 22(10). 1995–2007. 152 indexed citations
16.
Lai, Daniel, et al.. (2012). R- chie : a web server and R package for visualizing RNA secondary structures. Nucleic Acids Research. 40(12). e95–e95. 93 indexed citations
17.
Popescu, Alexandra, Daniel Lai, Angela Lu, & Kathy Gardner. (2011). Stroke following Epidural Injections—Case Report and Review of Literature. Journal of Neuroimaging. 23(1). 118–121. 26 indexed citations
18.
Chun, Hon Wai, et al.. (2005). Scheduling engineering works for the MTR corporation in Hong Kong. Innovative Applications of Artificial Intelligence. 1467–1474. 5 indexed citations
19.
Volinn, Ernest, Daniel Lai, Steven McKinney, & John D. Loeser. (1988). When back pain becomes disabling: a regional analysis. Pain. 33(1). 33–39. 45 indexed citations
20.
Margolis, Renée K., R. U. Margolis, C. Preti, & Daniel Lai. (1975). Distribution and metabolism of glycoproteins and glycosaminoglycans in subcellular fractions of brain. Biochemistry. 14(22). 4797–4804. 99 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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