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.
Glia–neuron interactions in the mammalian retina
2015609 citationsElena Vecino, Francisco D. Rodríguez et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Elena Vecino'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 Elena Vecino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Elena Vecino more than expected).
This network shows the impact of papers produced by Elena Vecino. 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 Elena Vecino. The network helps show where Elena Vecino may publish in the future.
Co-authorship network of co-authors of Elena Vecino
This figure shows the co-authorship network connecting the top 25 collaborators of Elena Vecino.
A scholar is included among the top collaborators of Elena Vecino 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 Elena Vecino. Elena Vecino is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Fonollosa, Alex, Joseba Artaraz, María Valcárcel, Clarisa Salado, & Elena Vecino. (2014). Effects of Interferon-alpha2a on the expression of tight junctions in ARPE-19 cells. Investigative Ophthalmology & Visual Science. 55(13). 99–99.
10.
Urcola, Aritz, et al.. (2014). Postoperative IOP is not related to intrascleral lake morphology after Non Penetrating Deep Sclerectomy without scleral implant. Investigative Ophthalmology & Visual Science. 55(13). 6131–6131.1 indexed citations
11.
Vecino, Elena, et al.. (2011). Retrobulbar Optic Nerve Section In Pig: Optical Coherence Tomography (oct) And Multifocal Electroretinography (mferg) Study. Investigative Ophthalmology & Visual Science. 52(14). 4683–4683.2 indexed citations
Galdós, Marta, et al.. (2010). Funduscopic and Ultrastructural Evaluation in Experimental Glaucoma Model in Minipigs. Investigative Ophthalmology & Visual Science. 51(13). 6392–6392.3 indexed citations
14.
Hernández, Mercè, et al.. (2007). Recovery of Molecular Marker Expression in RPE65 Mutant Dog Retinas After Gene Therapy using Adeno-Associated Virus. Investigative Ophthalmology & Visual Science. 48(13). 4616–4616.
15.
Hernández, Mercè, et al.. (2005). Selective Fluorogold and Dextranamine Retrograde Labeling of Retinal Ganglion Cells in Glaucoma. Investigative Ophthalmology & Visual Science. 46(13). 4017–4017.1 indexed citations
16.
Vecino, Elena, et al.. (2004). Topography Of Retinal Ganglion Cells Of The Pig Retina – Cell Size Distribution. Investigative Ophthalmology & Visual Science. 45(13). 5434–5434.1 indexed citations
17.
Vecino, Elena, et al.. (2003). Retinal ganglion cells from human and porcine retina. Many similarities and few differences. UEA Digital Repository (University of East Anglia).2 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.