Deepak A. Lamba

4.0k total citations · 1 hit paper
49 papers, 2.9k citations indexed

About

Deepak A. Lamba is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Ophthalmology. According to data from OpenAlex, Deepak A. Lamba has authored 49 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Molecular Biology, 22 papers in Cellular and Molecular Neuroscience and 5 papers in Ophthalmology. Recurrent topics in Deepak A. Lamba's work include Retinal Development and Disorders (36 papers), Pluripotent Stem Cells Research (14 papers) and Neuroscience and Neural Engineering (13 papers). Deepak A. Lamba is often cited by papers focused on Retinal Development and Disorders (36 papers), Pluripotent Stem Cells Research (14 papers) and Neuroscience and Neural Engineering (13 papers). Deepak A. Lamba collaborates with scholars based in United States, Portugal and Mexico. Deepak A. Lamba's co-authors include Thomas A. Reh, Michael Karl, Juliane Gust, Carol B. Ware, Pei-Rong Wang, Roli K. Hirata, David W. Russell, Joseph C. Reynolds, Shereen Chew and Jie Zhu and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Deepak A. Lamba

47 papers receiving 2.9k citations

Hit Papers

Efficient generation of retinal progenitor cells from hum... 2006 2026 2012 2019 2006 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deepak A. Lamba United States 26 2.5k 1.1k 346 334 232 49 2.9k
David M. Gamm United States 38 4.4k 1.7× 1.8k 1.7× 893 2.6× 682 2.0× 252 1.1× 78 5.0k
Alan J. Mears Canada 26 2.7k 1.1× 1.1k 1.0× 646 1.9× 226 0.7× 311 1.3× 53 3.1k
Cheryl Y. Gregory‐Evans Canada 28 2.0k 0.8× 420 0.4× 668 1.9× 319 1.0× 330 1.4× 67 2.7k
Alice Pébay Australia 37 2.5k 1.0× 575 0.5× 202 0.6× 153 0.5× 332 1.4× 111 3.2k
Ani V. Das United States 22 1.2k 0.5× 350 0.3× 168 0.5× 301 0.9× 110 0.5× 37 1.4k
Dyonne T. Hartong Netherlands 11 2.1k 0.8× 810 0.8× 1.1k 3.1× 356 1.1× 207 0.9× 27 2.6k
Carla Mellough United Kingdom 17 914 0.4× 397 0.4× 252 0.7× 173 0.5× 54 0.2× 26 1.1k
Raffaella Scardigli Italy 21 1.9k 0.7× 549 0.5× 96 0.3× 88 0.3× 315 1.4× 42 2.4k
Sigrid Henke‐Fahle Germany 21 922 0.4× 853 0.8× 457 1.3× 435 1.3× 349 1.5× 37 2.1k
Emeline F. Nandrot France 25 1.6k 0.6× 401 0.4× 826 2.4× 200 0.6× 175 0.8× 52 2.2k

Countries citing papers authored by Deepak A. Lamba

Since Specialization
Citations

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

Fields of papers citing papers by Deepak A. Lamba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deepak A. Lamba. 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 Deepak A. Lamba. The network helps show where Deepak A. Lamba may publish in the future.

Co-authorship network of co-authors of Deepak A. Lamba

This figure shows the co-authorship network connecting the top 25 collaborators of Deepak A. Lamba. A scholar is included among the top collaborators of Deepak A. Lamba 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 Deepak A. Lamba. Deepak A. Lamba 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.
Arthur, Peggy, Sangeetha Kandoi, Anil Kumar Kalvala, et al.. (2025). Cannabidiol-Loaded Retinal Organoid-Derived Extracellular Vesicles Protect Oxidatively Stressed ARPE-19 Cells. Biomedicines. 13(5). 1167–1167.
2.
Kandoi, Sangeetha, Hannah M. Follett, Phyllis Summerfelt, et al.. (2024). Human iPSC-derived photoreceptor transplantation in the cone dominant 13-lined ground squirrel. Stem Cell Reports. 19(3). 331–342. 9 indexed citations
4.
Kandoi, Sangeetha & Deepak A. Lamba. (2023). Retinal Organoids: A Human Model System for Development, Diseases, and Therapies. Advances in experimental medicine and biology. 1415. 549–554. 5 indexed citations
5.
Bachu, Vismaya S., et al.. (2022). An enhancer located in a Pde6c intron drives transient expression in the cone photoreceptors of developing mouse and human retinas. Developmental Biology. 488. 131–150. 3 indexed citations
6.
Kandoi, Sangeetha, et al.. (2021). Differentiation of tree shrew iPSC-derived retinal ganglion cells using 3D organoid approach. Investigative Ophthalmology & Visual Science. 62(8). 3150–3150. 1 indexed citations
7.
Kramer, Joshua, et al.. (2021). Dpp/TGFβ-superfamily play a dual conserved role in mediating the damage response in the retina. PLoS ONE. 16(10). e0258872–e0258872.
8.
Meyer, Jesse G., et al.. (2019). Proteome and Secretome Dynamics of Human Retinal Pigment Epithelium in Response to Reactive Oxygen Species. Scientific Reports. 9(1). 15440–15440. 23 indexed citations
9.
Kaufman, Michael L., Noah Goodson, Shereen Chew, et al.. (2019). Transcriptional profiling of murine retinas undergoing semi-synchronous cone photoreceptor differentiation. Developmental Biology. 453(2). 155–167. 17 indexed citations
10.
Sousa‐Victor, Pedro, Joana Neves, Patrick Ventura, et al.. (2019). MANF regulates metabolic and immune homeostasis in ageing and protects against liver damage. Nature Metabolism. 1(2). 276–290. 97 indexed citations
11.
Kramer, Joshua, Kathleen R. Chirco, & Deepak A. Lamba. (2019). Immunological Considerations for Retinal Stem Cell Therapy. Advances in experimental medicine and biology. 1186. 99–119. 9 indexed citations
13.
Zhu, Jie & Deepak A. Lamba. (2018). Small Molecule-Based Retinal Differentiation of Human Embryonic Stem Cells and Induced Pluripotent Stem Cells. BIO-PROTOCOL. 8(12). 4 indexed citations
14.
Chao, Jennifer R., Deepak A. Lamba, Todd R. Klesert, et al.. (2017). Transplantation of Human Embryonic Stem Cell-Derived Retinal Cells into the Subretinal Space of a Non-Human PrimateChao et al.. eScholarship (California Digital Library). 63 indexed citations
15.
Agrawal, Pooja, Joseph C. Reynolds, Shereen Chew, Deepak A. Lamba, & Robert E. Hughes. (2014). DEPTOR Is a Stemness Factor That Regulates Pluripotency of Embryonic Stem Cells. Journal of Biological Chemistry. 289(46). 31818–31826. 30 indexed citations
16.
Lamba, Deepak A., et al.. (2010). Generation, Purification and Transplantation of Photoreceptors Derived from Human Induced Pluripotent Stem Cells. PLoS ONE. 5(1). e8763–e8763. 303 indexed citations
17.
Lamba, Deepak A., Michael Karl, & Thomas A. Reh. (2009). Strategies for retinal repair: cell replacement and regeneration. Progress in brain research. 175. 23–31. 62 indexed citations
18.
Ware, Carol B., Linlin Wang, Brigham H. Mecham, et al.. (2009). Histone Deacetylase Inhibition Elicits an Evolutionarily Conserved Self-Renewal Program in Embryonic Stem Cells. Cell stem cell. 4(4). 359–369. 134 indexed citations
19.
Lamba, Deepak A., Juliane Gust, & Thomas A. Reh. (2009). Transplantation of Human Embryonic Stem Cell-Derived Photoreceptors Restores Some Visual Function in Crx-Deficient Mice. Cell stem cell. 4(1). 73–79. 445 indexed citations
20.
Lamba, Deepak A., Michael Karl, & Thomas A. Reh. (2008). Neural Regeneration and Cell Replacement: A View from the Eye. Cell stem cell. 2(6). 538–549. 138 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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