Mark V. Silva

20 papers receiving 946 citations

Mark V. Silva's Hit Papers

Tumor Evolution and Drug Response in Patient-Derived Organoid Models of Bladder Cancer 2018 · 690 citations
6900+2+5Years since publication200400600

Peers

Mark V. Silva
Comparison fields: 5 of 83
  • Geriatrics and Gerontology 69
  • Oncology 322
  • Biomedical Engineering 189
  • Surgery 211
  • Cancer Research 64
Replace Bang-li Hu with:
Bang-li Hu China
Leonardo D’Urso Italy
Idoia Morilla Spain
David J. Byun United States
António Pedro Gomes Portugal
Yongqiang Zheng China
Ilaria Marinoni Switzerland
Sadafumi Kawamura Japan
Mirosław Śnietura Poland
Kenneth C. Fan United States
Mark V. Silva relative to Bang-li Hu China Bang-li Hu's profile →
Citations per field
00.5×2×4×6×8.6×
Bang-li Hu · 1×
Citations per year

Countries citing papers authored by Mark V. Silva

Since Specialization
Citations

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

Fields of papers citing papers by Mark V. Silva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark V. Silva. 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 Mark V. Silva. The network helps show where Mark V. Silva may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Tumor Evolution and Drug Response in Patient-Derived Organoid Models of Bladder Cancer
Hit paper breakdown →
2018690
2 201596
3 201627
4 201522
5 201621
6 201920
7 201417
8 201110
9 201210
10 20139
11 20158
12 20198
13 20205
14 20154
15 20194
16 19932
17 20162
18 20151
19 20151
20 20181

About Mark V. Silva

Mark V. Silva is a scholar working on Pediatrics, Perinatology and Child Health, Geriatrics and Gerontology, Surgery, Cellular and Molecular Neuroscience and Pulmonary and Respiratory Medicine, having authored 22 papers that have together received 958 indexed citations. Recurring topics across this work include Pediatric Urology and Nephrology Studies (4 papers), Bladder and Urothelial Cancer Treatments (4 papers), Kidney Stones and Urolithiasis Treatments (3 papers), Frailty in Older Adults (2 papers), Multiple Sclerosis Research Studies (1 paper), Innovations in Medical Education (1 paper), Hearing Loss and Rehabilitation (1 paper) and Acute Kidney Injury Research (1 paper). The work is most often cited by research in Geriatrics and Gerontology (69 citations), Oncology (322 citations), Biomedical Engineering (189 citations), Surgery (211 citations) and Cancer Research (64 citations). Mark V. Silva has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Julia Beth Finkelstein, Arindam RoyChoudhury, Mitchell C. Benson, Jamie Sungmin Pak, Pasquale Casale, Max Kates, Guarionex Joel DeCastro, Trinity Jude Bivalacqua, Danny Lascano and Sarah M. Lambert. Their work appears in journals such as The Journal of Urology, Urology, Journal of Endourology, Cell and Value in Health.

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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