Lara Perryman

1.9k citations
19 papers · 850 indexed · h-index 13

Impact in

  • Genetics top 5%
    • Glioma Diagnosis and Treatment
    • Cancer, Hypoxia, and Metabolism
    • MicroRNA in disease regulation

Papers in

    • Glioma Diagnosis and Treatment 9
    • Cancer, Hypoxia, and Metabolism 3
    • MicroRNA in disease regulation 2

Lara Perryman

19 papers receiving 839 citations

Peers

Lara Perryman
Comparison fields: 5 of 71
  • Genetics 327
  • Cancer Research 204
  • Neurology 124
  • Molecular Biology 516
  • Oncology 170
Replace Marco Lodrini with:
Marco Lodrini Germany
Demirkan Gursel United States
Andrea M. Griesinger United States
Markus Bredel United States
Kah Suan Lim United States
Alexandra Borodovsky United States
Xingfu Wang China
Christopher R. Edwards United States
Esther Andion Spain
Nazanin Majd United States
Lara Perryman relative to Marco Lodrini Germany Marco Lodrini's profile →
Citations per field
00.5×1.5×2.0×
Marco Lodrini · 1×
Citations per year

Countries citing papers authored by Lara Perryman

Since Specialization
Citations

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

Fields of papers citing papers by Lara Perryman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lara Perryman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lara Perryman Line = papers co-authored together Lara Perryman links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 20251
2 202319
3 20225
4 201883
5 201716
6 201611
7 2015121
8 20158
9 201436
10 2012136
11 201228
12 201141
13 2010136
14 200971
15 200993
16 20091
17
Differential mechanisms of temozolomide resistance in pediatric glioma cell lines
20081
18 200612
19 197531

About Lara Perryman

Lara Perryman is a scholar working on Genetics, Cancer Research, Neurology, Molecular Biology and Biochemistry, having authored 19 papers that have together received 850 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (9 papers), Microbial metabolism and enzyme function (4 papers), Cancer, Hypoxia, and Metabolism (3 papers), Neuroblastoma Research and Treatments (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), MRI in cancer diagnosis (2 papers), MicroRNA in disease regulation (2 papers) and Protein Degradation and Inhibitors (2 papers). The work is most often cited by research in Genetics (327 citations), Cancer Research (204 citations), Neurology (124 citations), Molecular Biology (516 citations) and Oncology (170 citations). Lara Perryman has collaborated with scholars based in United Kingdom, Australia and Denmark. Frequent co-authors include Chris Jones, Darren Hargrave, Janine T. Erler, Nathalie Gaspar, Lynley V. Marshall, Dorine A. Bax, Suzanne E. Little, Paul Workman, Marta Viana‐Pereira and Gilles Vassal. Their work appears in journals such as Molecular Cancer Therapeutics, Clinical Cancer Research, Nature Reviews Clinical Oncology, Neoplasia and Scientific Reports.

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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