Mark D’Souza

4.9k citations
29 papers · 2.1k indexed · 1 hit paper · h-index 15

Mark D’Souza

28 papers receiving 2.1k citations

Hit Papers

The use of gene clusters to infer functional coupling9461999202620082017250500750

Peers

Mark D’Souza
Comparison fields: 5 of 137
  • Molecular Biology 1.7k
  • Genetics 282
  • Ecology 246
  • Neurology 66
  • Physiology 34
Replace Noemí del‐Toro with:
Noemí del‐Toro United Kingdom
Hongzhan Huang United States
Steffen Möller Germany
Fredrik Levander Sweden
Antonio J. Pérez‐Pulido Spain
Vadim Demichev Germany
Laurent Gatto Belgium
Nicolas Hulo Switzerland
Brigitte Boeckmann Switzerland
Jingfa Xiao China
Mark D’Souza relative to Noemí del‐Toro United Kingdom Noemí del‐Toro's profile →
Citations per field
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Noemí del‐Toro · 1×
Citations per year

Countries citing papers authored by Mark D’Souza

Since Specialization
Citations

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

Fields of papers citing papers by Mark D’Souza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark D’Souza. 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 D’Souza. The network helps show where Mark D’Souza may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202312
2 20231
3 20230
4 202214
5 202155
6 202116
7 202114
8 20173
9 20156
10 201556
11 201468
12 201311
13 201263
14 201227
15 200513
16 200370
17 200062
18 1999100
19 1997248
20
Coherent Backscattering of a Scalar Wave off a Rough Surface
19961

About Mark D’Souza

Mark D’Souza is a scholar working on Ophthalmology, Molecular Biology, Radiology, Nuclear Medicine and Imaging, Neurology and Periodontics, having authored 29 papers that have together received 2.1k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (10 papers), Retinal Diseases and Treatments (8 papers), RNA and protein synthesis mechanisms (6 papers), Gut microbiota and health (5 papers), Gene expression and cancer classification (5 papers), Bioinformatics and Genomic Networks (4 papers), Retinal Imaging and Analysis (4 papers) and Machine Learning in Bioinformatics (3 papers). The work is most often cited by research in Molecular Biology (1.7k citations), Genetics (282 citations), Ecology (246 citations), Neurology (66 citations) and Physiology (34 citations). Mark D’Souza has collaborated with scholars based in United States, Italy and India. Frequent co-authors include Ross Overbeek, Michael Fonstein, Natalia Maltsev, Gordon D. Pusch, Niels Larsen, Folker Meyer, Andreas Wilke, Sabino Liuni, Graziano Pesole and Kevin Keegan. Their work appears in journals such as International Journal of Molecular Sciences, Translational Vision Science & Technology, PLoS Computational Biology, Cells and Investigative Ophthalmology & Visual Science.

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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