M.W. Day

507 citations
13 papers · 312 · h-index 9

Impact in

    • PARP inhibition in cancer therapy
    • Cancer-related Molecular Pathways
    • DNA Repair Mechanisms
    • Genomics and Chromatin Dynamics
    • CRISPR and Genetic Engineering
    • RNA Research and Splicing
    • Cancer therapeutics and mechanisms

Papers in

    • DNA Repair Mechanisms 10
    • Genomics and Chromatin Dynamics 4
    • CRISPR and Genetic Engineering 4
    • RNA and protein synthesis mechanisms 1
    • PARP inhibition in cancer therapy 4
    • Cancer-related Molecular Pathways 2

M.W. Day

10 papers receiving 310 citations

Peers

M.W. Day
Comparison fields: 5 of 47
  • Oncology 114
  • Molecular Biology 268
  • Cell Biology 60
  • Cancer Research 35
  • Aging 2
Replace Valéria Szukacsov with:
Valéria Szukacsov Hungary
Shaokai Ning China
Caroline Davis United States
Yixi Xu China
Ronan Broderick United Kingdom
Géraldine Buhagiar‐Labarchède France
Benoit Fischer France
Marcos A. Carpio Argentina
Papia Ghosh United States
Rosine Onclercq-Delic France
M.W. Day relative to Valéria Szukacsov Hungary Valéria Szukacsov's profile →
Citations per field
00.5×3.9×
Valéria Szukacsov · 1×
Citations per year

Countries citing papers authored by M.W. Day

Since Specialization
Citations

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

Fields of papers citing papers by M.W. Day

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.W. Day. 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 M.W. Day. The network helps show where M.W. Day may publish in the future.

Co-authors

The 25 scholars most cited alongside M.W. Day, 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 M.W. Day Line = papers co-authored together M.W. Day links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 201984
2 201559
3 201940
4 201830
5 202124
6 201322
7 202121
8 202219
9 20219
10 20244
11 20250
12 20250
13 20250

About M.W. Day

M.W. Day is a scholar working on Molecular Biology, Oncology, Cell Biology, Epidemiology and Materials Chemistry, having authored 13 papers that have together received 312 indexed citations. Recurring topics across this work include DNA Repair Mechanisms (10 papers), Genomics and Chromatin Dynamics (4 papers), PARP inhibition in cancer therapy (4 papers), CRISPR and Genetic Engineering (4 papers), Microtubule and mitosis dynamics (3 papers), Cancer-related Molecular Pathways (2 papers), Cytomegalovirus and herpesvirus research (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Oncology (114 citations), Molecular Biology (268 citations), Cell Biology (60 citations), Cancer Research (35 citations) and Aging (2 citations). M.W. Day has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Laurence H. Pearl, Antony W. Oliver, Robert A. Baldock, Felicity Z. Watts, Nicolas Bigot, Ross Cloney, Mathieu Rappas, Penelope A. Jeggo, Mara De Marco Zompit and Manuel Stucki. Their work appears in journals such as Nature Communications, eLife, Molecular Cell, mBio and DNA repair.

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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