Laura Islas

581 total citations · 1 hit paper
9 papers, 415 citations indexed

About

Laura Islas is a scholar working on Immunology, Computer Networks and Communications and Molecular Biology. According to data from OpenAlex, Laura Islas has authored 9 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Immunology, 2 papers in Computer Networks and Communications and 2 papers in Molecular Biology. Recurrent topics in Laura Islas's work include IoT and Edge/Fog Computing (1 paper), Chemical Synthesis and Analysis (1 paper) and Latin American Urban Studies (1 paper). Laura Islas is often cited by papers focused on IoT and Edge/Fog Computing (1 paper), Chemical Synthesis and Analysis (1 paper) and Latin American Urban Studies (1 paper). Laura Islas collaborates with scholars based in United States, Mexico and Spain. Laura Islas's co-authors include Jonathan Himmelfarb, Hongxia Fu, Randall T. Moon, Jennifer L. Harder, Jeffrey W. Pippin, Nelly M. Cruz, Yong Kyun Kim, Ramila E. Gulieva, James Annis and Stuart J. Shankland and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and The Journal of Immunology.

In The Last Decade

Laura Islas

8 papers receiving 408 citations

Hit Papers

High-Throughput Screening Enhances Kidney Organoid Differ... 2018 2026 2020 2023 2018 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. High-Throughput Screening Enhances Kidney Organoid Differentiation from Human Pluripotent Stem Cells and Enables Automated Multidimensional Phenotyping
    2018 329 citations Stefan Czerniecki, Nelly M. Cruz et al. Cell stem cell profile →

Peers

Laura Islas
Qinghua Huang China
Kristen Roberts United States
Marianne K. Vormann Netherlands
Bowen Xu China
Anna Baccei United States
Takahide Aburatani Japan
Jennifer A. Hollywood New Zealand
Qinghua Huang China
Laura Islas
Citations per year, relative to Laura Islas Laura Islas (= 1×) peers Qinghua Huang

Countries citing papers authored by Laura Islas

Since Specialization
Citations

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

Fields of papers citing papers by Laura Islas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laura Islas

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

All Works

9 of 9 papers shown
1.
Shasha, Carolyn, David R. Glass, Laura Islas, et al.. (2025). Hallmarks of T-cell exhaustion and antigen experience are absent in multiple myeloma from diagnosis to maintenance therapy. Blood. 145(26). 3113–3123. 2 indexed citations
2.
Maurice, Nicholas J., Jami R. Erickson, Caitlin S. DeJong, et al.. (2025). Cytokine and metabolite networks shape T cell residency and functionality at the term human maternal-fetal interface. The Journal of Immunology. 214(9). 2221–2237.
3.
Glass, David R., Nirasha Ramchurren, K. Rachael Parks, et al.. (2024). Multi-omic profiling reveals the endogenous and neoplastic responses to immunotherapies in cutaneous T cell lymphoma. Cell Reports Medicine. 5(5). 101527–101527. 3 indexed citations
4.
Li, Shamin, Yannick Simoni, Austin M. Gabel, et al.. (2021). Characterization of neoantigen-specific T cells in cancer resistant to immune checkpoint therapies. Proceedings of the National Academy of Sciences. 118(30). 40 indexed citations
5.
Islas, Laura, Sebastián Gutiérrez, & Francisco Chávez. (2019). Wireless Sensor Network Prototype to Monitor the Condition of Holding Furnaces in the Aluminum Casting Plant. 1–8. 5 indexed citations
6.
Gutiérrez, Sebastián, Laura Islas, Federico Martín Ibáñez, et al.. (2019). Wireless Ammeter Based on ZigBee for Continuous Monitoring of Induction Motors. 91. 1–6. 4 indexed citations
7.
Czerniecki, Stefan, Nelly M. Cruz, Jennifer L. Harder, et al.. (2018). High-Throughput Screening Enhances Kidney Organoid Differentiation from Human Pluripotent Stem Cells and Enables Automated Multidimensional Phenotyping. Cell stem cell. 22(6). 929–940.e4. 329 indexed citations breakdown →
8.
Islas, Laura, et al.. (2015). Videovigilancia en el Centro Histórico de la Ciudad de México. 4(13). 29–34. 1 indexed citations
9.
Islas, Laura, et al.. (1995). Gentamicin Formation in Micromonospora purpurea: Stimulatory Effect of Ammonium.. The Journal of Antibiotics. 48(6). 479–483. 31 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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